diff --git a/cope2n-ai-fi/modules/sdsvkie/._bit/COMMIT_EDITMSG b/cope2n-ai-fi/modules/sdsvkie/._bit/COMMIT_EDITMSG new file mode 100755 index 0000000..436c316 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/._bit/COMMIT_EDITMSG @@ -0,0 +1 @@ +modify init_predictor diff --git a/cope2n-ai-fi/modules/sdsvkie/._bit/FETCH_HEAD b/cope2n-ai-fi/modules/sdsvkie/._bit/FETCH_HEAD new file mode 100755 index 0000000..e69de29 diff --git a/cope2n-ai-fi/modules/sdsvkie/._bit/HEAD b/cope2n-ai-fi/modules/sdsvkie/._bit/HEAD new file mode 100755 index 0000000..b870d82 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/._bit/HEAD @@ -0,0 +1 @@ +ref: refs/heads/main diff --git a/cope2n-ai-fi/modules/sdsvkie/._bit/config b/cope2n-ai-fi/modules/sdsvkie/._bit/config new file mode 100755 index 0000000..043886f --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/._bit/config @@ -0,0 +1,14 @@ +[core] + repositoryformatversion = 0 + filemode = true + bare = false + logallrefupdates = true +[user] + email = lehoang2797@gmail.com + name = LeHoang +[remote "origin"] + url = http://107.120.133.27:801/henryle97/sdsvkie.git + fetch = +refs/heads/*:refs/remotes/origin/* +[branch "main"] + remote = origin + merge = refs/heads/main diff --git a/cope2n-ai-fi/modules/sdsvkie/._bit/description b/cope2n-ai-fi/modules/sdsvkie/._bit/description new file mode 100755 index 0000000..498b267 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/._bit/description @@ -0,0 +1 @@ +Unnamed repository; edit this file 'description' to name the repository. diff --git a/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/applypatch-msg.sample b/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/applypatch-msg.sample new file mode 100755 index 0000000..a5d7b84 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/applypatch-msg.sample @@ -0,0 +1,15 @@ +#!/bin/sh +# +# An example hook script to check the commit log message taken by +# applypatch from an e-mail message. +# +# The hook should exit with non-zero status after issuing an +# appropriate message if it wants to stop the commit. The hook is +# allowed to edit the commit message file. +# +# To enable this hook, rename this file to "applypatch-msg". + +. git-sh-setup +commitmsg="$(git rev-parse --git-path hooks/commit-msg)" +test -x "$commitmsg" && exec "$commitmsg" ${1+"$@"} +: diff --git a/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/commit-msg.sample b/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/commit-msg.sample new file mode 100755 index 0000000..b58d118 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/commit-msg.sample @@ -0,0 +1,24 @@ +#!/bin/sh +# +# An example hook script to check the commit log message. +# Called by "git commit" with one argument, the name of the file +# that has the commit message. The hook should exit with non-zero +# status after issuing an appropriate message if it wants to stop the +# commit. The hook is allowed to edit the commit message file. +# +# To enable this hook, rename this file to "commit-msg". + +# Uncomment the below to add a Signed-off-by line to the message. +# Doing this in a hook is a bad idea in general, but the prepare-commit-msg +# hook is more suited to it. +# +# SOB=$(git var GIT_AUTHOR_IDENT | sed -n 's/^\(.*>\).*$/Signed-off-by: \1/p') +# grep -qs "^$SOB" "$1" || echo "$SOB" >> "$1" + +# This example catches duplicate Signed-off-by lines. + +test "" = "$(grep '^Signed-off-by: ' "$1" | + sort | uniq -c | sed -e '/^[ ]*1[ ]/d')" || { + echo >&2 Duplicate Signed-off-by lines. + exit 1 +} diff --git a/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/fsmonitor-watchman.sample b/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/fsmonitor-watchman.sample new file mode 100755 index 0000000..ef94fa2 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/fsmonitor-watchman.sample @@ -0,0 +1,109 @@ +#!/usr/bin/perl + +use strict; +use warnings; +use IPC::Open2; + +# An example hook script to integrate Watchman +# (https://facebook.github.io/watchman/) with git to speed up detecting +# new and modified files. +# +# The hook is passed a version (currently 1) and a time in nanoseconds +# formatted as a string and outputs to stdout all files that have been +# modified since the given time. Paths must be relative to the root of +# the working tree and separated by a single NUL. +# +# To enable this hook, rename this file to "query-watchman" and set +# 'git config core.fsmonitor .git/hooks/query-watchman' +# +my ($version, $time) = @ARGV; + +# Check the hook interface version + +if ($version == 1) { + # convert nanoseconds to seconds + # subtract one second to make sure watchman will return all changes + $time = int ($time / 1000000000) - 1; +} else { + die "Unsupported query-fsmonitor hook version '$version'.\n" . + "Falling back to scanning...\n"; +} + +my $git_work_tree; +if ($^O =~ 'msys' || $^O =~ 'cygwin') { + $git_work_tree = Win32::GetCwd(); + $git_work_tree =~ tr/\\/\//; +} else { + require Cwd; + $git_work_tree = Cwd::cwd(); +} + +my $retry = 1; + +launch_watchman(); + +sub launch_watchman { + + my $pid = open2(\*CHLD_OUT, \*CHLD_IN, 'watchman -j --no-pretty') + or die "open2() failed: $!\n" . + "Falling back to scanning...\n"; + + # In the query expression below we're asking for names of files that + # changed since $time but were not transient (ie created after + # $time but no longer exist). + # + # To accomplish this, we're using the "since" generator to use the + # recency index to select candidate nodes and "fields" to limit the + # output to file names only. + + my $query = <<" END"; + ["query", "$git_work_tree", { + "since": $time, + "fields": ["name"] + }] + END + + print CHLD_IN $query; + close CHLD_IN; + my $response = do {local $/; }; + + die "Watchman: command returned no output.\n" . + "Falling back to scanning...\n" if $response eq ""; + die "Watchman: command returned invalid output: $response\n" . + "Falling back to scanning...\n" unless $response =~ /^\{/; + + my $json_pkg; + eval { + require JSON::XS; + $json_pkg = "JSON::XS"; + 1; + } or do { + require JSON::PP; + $json_pkg = "JSON::PP"; + }; + + my $o = $json_pkg->new->utf8->decode($response); + + if ($retry > 0 and $o->{error} and $o->{error} =~ m/unable to resolve root .* directory (.*) is not watched/) { + print STDERR "Adding '$git_work_tree' to watchman's watch list.\n"; + $retry--; + qx/watchman watch "$git_work_tree"/; + die "Failed to make watchman watch '$git_work_tree'.\n" . + "Falling back to scanning...\n" if $? != 0; + + # Watchman will always return all files on the first query so + # return the fast "everything is dirty" flag to git and do the + # Watchman query just to get it over with now so we won't pay + # the cost in git to look up each individual file. + print "/\0"; + eval { launch_watchman() }; + exit 0; + } + + die "Watchman: $o->{error}.\n" . + "Falling back to scanning...\n" if $o->{error}; + + binmode STDOUT, ":utf8"; + local $, = "\0"; + print @{$o->{files}}; +} diff --git a/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/post-update.sample b/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/post-update.sample new file mode 100755 index 0000000..ec17ec1 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/post-update.sample @@ -0,0 +1,8 @@ +#!/bin/sh +# +# An example hook script to prepare a packed repository for use over +# dumb transports. +# +# To enable this hook, rename this file to "post-update". + +exec git update-server-info diff --git a/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/pre-applypatch.sample b/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/pre-applypatch.sample new file mode 100755 index 0000000..4142082 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/pre-applypatch.sample @@ -0,0 +1,14 @@ +#!/bin/sh +# +# An example hook script to verify what is about to be committed +# by applypatch from an e-mail message. +# +# The hook should exit with non-zero status after issuing an +# appropriate message if it wants to stop the commit. +# +# To enable this hook, rename this file to "pre-applypatch". + +. git-sh-setup +precommit="$(git rev-parse --git-path hooks/pre-commit)" +test -x "$precommit" && exec "$precommit" ${1+"$@"} +: diff --git a/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/pre-commit.sample b/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/pre-commit.sample new file mode 100755 index 0000000..6a75641 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/pre-commit.sample @@ -0,0 +1,49 @@ +#!/bin/sh +# +# An example hook script to verify what is about to be committed. +# Called by "git commit" with no arguments. The hook should +# exit with non-zero status after issuing an appropriate message if +# it wants to stop the commit. +# +# To enable this hook, rename this file to "pre-commit". + +if git rev-parse --verify HEAD >/dev/null 2>&1 +then + against=HEAD +else + # Initial commit: diff against an empty tree object + against=$(git hash-object -t tree /dev/null) +fi + +# If you want to allow non-ASCII filenames set this variable to true. +allownonascii=$(git config --bool hooks.allownonascii) + +# Redirect output to stderr. +exec 1>&2 + +# Cross platform projects tend to avoid non-ASCII filenames; prevent +# them from being added to the repository. We exploit the fact that the +# printable range starts at the space character and ends with tilde. +if [ "$allownonascii" != "true" ] && + # Note that the use of brackets around a tr range is ok here, (it's + # even required, for portability to Solaris 10's /usr/bin/tr), since + # the square bracket bytes happen to fall in the designated range. + test $(git diff --cached --name-only --diff-filter=A -z $against | + LC_ALL=C tr -d '[ -~]\0' | wc -c) != 0 +then + cat <<\EOF +Error: Attempt to add a non-ASCII file name. + +This can cause problems if you want to work with people on other platforms. + +To be portable it is advisable to rename the file. + +If you know what you are doing you can disable this check using: + + git config hooks.allownonascii true +EOF + exit 1 +fi + +# If there are whitespace errors, print the offending file names and fail. +exec git diff-index --check --cached $against -- diff --git a/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/pre-merge-commit.sample b/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/pre-merge-commit.sample new file mode 100755 index 0000000..399eab1 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/pre-merge-commit.sample @@ -0,0 +1,13 @@ +#!/bin/sh +# +# An example hook script to verify what is about to be committed. +# Called by "git merge" with no arguments. The hook should +# exit with non-zero status after issuing an appropriate message to +# stderr if it wants to stop the merge commit. +# +# To enable this hook, rename this file to "pre-merge-commit". + +. git-sh-setup +test -x "$GIT_DIR/hooks/pre-commit" && + exec "$GIT_DIR/hooks/pre-commit" +: diff --git a/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/pre-push.sample b/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/pre-push.sample new file mode 100755 index 0000000..6187dbf --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/pre-push.sample @@ -0,0 +1,53 @@ +#!/bin/sh + +# An example hook script to verify what is about to be pushed. Called by "git +# push" after it has checked the remote status, but before anything has been +# pushed. If this script exits with a non-zero status nothing will be pushed. +# +# This hook is called with the following parameters: +# +# $1 -- Name of the remote to which the push is being done +# $2 -- URL to which the push is being done +# +# If pushing without using a named remote those arguments will be equal. +# +# Information about the commits which are being pushed is supplied as lines to +# the standard input in the form: +# +# +# +# This sample shows how to prevent push of commits where the log message starts +# with "WIP" (work in progress). + +remote="$1" +url="$2" + +z40=0000000000000000000000000000000000000000 + +while read local_ref local_sha remote_ref remote_sha +do + if [ "$local_sha" = $z40 ] + then + # Handle delete + : + else + if [ "$remote_sha" = $z40 ] + then + # New branch, examine all commits + range="$local_sha" + else + # Update to existing branch, examine new commits + range="$remote_sha..$local_sha" + fi + + # Check for WIP commit + commit=`git rev-list -n 1 --grep '^WIP' "$range"` + if [ -n "$commit" ] + then + echo >&2 "Found WIP commit in $local_ref, not pushing" + exit 1 + fi + fi +done + +exit 0 diff --git a/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/pre-rebase.sample b/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/pre-rebase.sample new file mode 100755 index 0000000..6cbef5c --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/pre-rebase.sample @@ -0,0 +1,169 @@ +#!/bin/sh +# +# Copyright (c) 2006, 2008 Junio C Hamano +# +# The "pre-rebase" hook is run just before "git rebase" starts doing +# its job, and can prevent the command from running by exiting with +# non-zero status. +# +# The hook is called with the following parameters: +# +# $1 -- the upstream the series was forked from. +# $2 -- the branch being rebased (or empty when rebasing the current branch). +# +# This sample shows how to prevent topic branches that are already +# merged to 'next' branch from getting rebased, because allowing it +# would result in rebasing already published history. + +publish=next +basebranch="$1" +if test "$#" = 2 +then + topic="refs/heads/$2" +else + topic=`git symbolic-ref HEAD` || + exit 0 ;# we do not interrupt rebasing detached HEAD +fi + +case "$topic" in +refs/heads/??/*) + ;; +*) + exit 0 ;# we do not interrupt others. + ;; +esac + +# Now we are dealing with a topic branch being rebased +# on top of master. Is it OK to rebase it? + +# Does the topic really exist? +git show-ref -q "$topic" || { + echo >&2 "No such branch $topic" + exit 1 +} + +# Is topic fully merged to master? +not_in_master=`git rev-list --pretty=oneline ^master "$topic"` +if test -z "$not_in_master" +then + echo >&2 "$topic is fully merged to master; better remove it." + exit 1 ;# we could allow it, but there is no point. +fi + +# Is topic ever merged to next? If so you should not be rebasing it. +only_next_1=`git rev-list ^master "^$topic" ${publish} | sort` +only_next_2=`git rev-list ^master ${publish} | sort` +if test "$only_next_1" = "$only_next_2" +then + not_in_topic=`git rev-list "^$topic" master` + if test -z "$not_in_topic" + then + echo >&2 "$topic is already up to date with master" + exit 1 ;# we could allow it, but there is no point. + else + exit 0 + fi +else + not_in_next=`git rev-list --pretty=oneline ^${publish} "$topic"` + /usr/bin/perl -e ' + my $topic = $ARGV[0]; + my $msg = "* $topic has commits already merged to public branch:\n"; + my (%not_in_next) = map { + /^([0-9a-f]+) /; + ($1 => 1); + } split(/\n/, $ARGV[1]); + for my $elem (map { + /^([0-9a-f]+) (.*)$/; + [$1 => $2]; + } split(/\n/, $ARGV[2])) { + if (!exists $not_in_next{$elem->[0]}) { + if ($msg) { + print STDERR $msg; + undef $msg; + } + print STDERR " $elem->[1]\n"; + } + } + ' "$topic" "$not_in_next" "$not_in_master" + exit 1 +fi + +<<\DOC_END + +This sample hook safeguards topic branches that have been +published from being rewound. + +The workflow assumed here is: + + * Once a topic branch forks from "master", "master" is never + merged into it again (either directly or indirectly). + + * Once a topic branch is fully cooked and merged into "master", + it is deleted. If you need to build on top of it to correct + earlier mistakes, a new topic branch is created by forking at + the tip of the "master". This is not strictly necessary, but + it makes it easier to keep your history simple. + + * Whenever you need to test or publish your changes to topic + branches, merge them into "next" branch. + +The script, being an example, hardcodes the publish branch name +to be "next", but it is trivial to make it configurable via +$GIT_DIR/config mechanism. + +With this workflow, you would want to know: + +(1) ... if a topic branch has ever been merged to "next". Young + topic branches can have stupid mistakes you would rather + clean up before publishing, and things that have not been + merged into other branches can be easily rebased without + affecting other people. But once it is published, you would + not want to rewind it. + +(2) ... if a topic branch has been fully merged to "master". + Then you can delete it. More importantly, you should not + build on top of it -- other people may already want to + change things related to the topic as patches against your + "master", so if you need further changes, it is better to + fork the topic (perhaps with the same name) afresh from the + tip of "master". + +Let's look at this example: + + o---o---o---o---o---o---o---o---o---o "next" + / / / / + / a---a---b A / / + / / / / + / / c---c---c---c B / + / / / \ / + / / / b---b C \ / + / / / / \ / + ---o---o---o---o---o---o---o---o---o---o---o "master" + + +A, B and C are topic branches. + + * A has one fix since it was merged up to "next". + + * B has finished. It has been fully merged up to "master" and "next", + and is ready to be deleted. + + * C has not merged to "next" at all. + +We would want to allow C to be rebased, refuse A, and encourage +B to be deleted. + +To compute (1): + + git rev-list ^master ^topic next + git rev-list ^master next + + if these match, topic has not merged in next at all. + +To compute (2): + + git rev-list master..topic + + if this is empty, it is fully merged to "master". + +DOC_END diff --git a/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/pre-receive.sample b/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/pre-receive.sample new file mode 100755 index 0000000..a1fd29e --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/pre-receive.sample @@ -0,0 +1,24 @@ +#!/bin/sh +# +# An example hook script to make use of push options. +# The example simply echoes all push options that start with 'echoback=' +# and rejects all pushes when the "reject" push option is used. +# +# To enable this hook, rename this file to "pre-receive". + +if test -n "$GIT_PUSH_OPTION_COUNT" +then + i=0 + while test "$i" -lt "$GIT_PUSH_OPTION_COUNT" + do + eval "value=\$GIT_PUSH_OPTION_$i" + case "$value" in + echoback=*) + echo "echo from the pre-receive-hook: ${value#*=}" >&2 + ;; + reject) + exit 1 + esac + i=$((i + 1)) + done +fi diff --git a/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/prepare-commit-msg.sample b/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/prepare-commit-msg.sample new file mode 100755 index 0000000..10fa14c --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/prepare-commit-msg.sample @@ -0,0 +1,42 @@ +#!/bin/sh +# +# An example hook script to prepare the commit log message. +# Called by "git commit" with the name of the file that has the +# commit message, followed by the description of the commit +# message's source. The hook's purpose is to edit the commit +# message file. If the hook fails with a non-zero status, +# the commit is aborted. +# +# To enable this hook, rename this file to "prepare-commit-msg". + +# This hook includes three examples. The first one removes the +# "# Please enter the commit message..." help message. +# +# The second includes the output of "git diff --name-status -r" +# into the message, just before the "git status" output. It is +# commented because it doesn't cope with --amend or with squashed +# commits. +# +# The third example adds a Signed-off-by line to the message, that can +# still be edited. This is rarely a good idea. + +COMMIT_MSG_FILE=$1 +COMMIT_SOURCE=$2 +SHA1=$3 + +/usr/bin/perl -i.bak -ne 'print unless(m/^. Please enter the commit message/..m/^#$/)' "$COMMIT_MSG_FILE" + +# case "$COMMIT_SOURCE,$SHA1" in +# ,|template,) +# /usr/bin/perl -i.bak -pe ' +# print "\n" . `git diff --cached --name-status -r` +# if /^#/ && $first++ == 0' "$COMMIT_MSG_FILE" ;; +# *) ;; +# esac + +# SOB=$(git var GIT_COMMITTER_IDENT | sed -n 's/^\(.*>\).*$/Signed-off-by: \1/p') +# git interpret-trailers --in-place --trailer "$SOB" "$COMMIT_MSG_FILE" +# if test -z "$COMMIT_SOURCE" +# then +# /usr/bin/perl -i.bak -pe 'print "\n" if !$first_line++' "$COMMIT_MSG_FILE" +# fi diff --git a/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/update.sample b/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/update.sample new file mode 100755 index 0000000..80ba941 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/._bit/hooks/update.sample @@ -0,0 +1,128 @@ +#!/bin/sh +# +# An example hook script to block unannotated tags from entering. +# Called by "git receive-pack" with arguments: refname sha1-old sha1-new +# +# To enable this hook, rename this file to "update". +# +# Config +# ------ +# hooks.allowunannotated +# This boolean sets whether unannotated tags will be allowed into the +# repository. By default they won't be. +# hooks.allowdeletetag +# This boolean sets whether deleting tags will be allowed in the +# repository. By default they won't be. +# hooks.allowmodifytag +# This boolean sets whether a tag may be modified after creation. By default +# it won't be. +# hooks.allowdeletebranch +# This boolean sets whether deleting branches will be allowed in the +# repository. By default they won't be. +# hooks.denycreatebranch +# This boolean sets whether remotely creating branches will be denied +# in the repository. By default this is allowed. +# + +# --- Command line +refname="$1" +oldrev="$2" +newrev="$3" + +# --- Safety check +if [ -z "$GIT_DIR" ]; then + echo "Don't run this script from the command line." >&2 + echo " (if you want, you could supply GIT_DIR then run" >&2 + echo " $0 )" >&2 + exit 1 +fi + +if [ -z "$refname" -o -z "$oldrev" -o -z "$newrev" ]; then + echo "usage: $0 " >&2 + exit 1 +fi + +# --- Config +allowunannotated=$(git config --bool hooks.allowunannotated) +allowdeletebranch=$(git config --bool hooks.allowdeletebranch) +denycreatebranch=$(git config --bool hooks.denycreatebranch) +allowdeletetag=$(git config --bool hooks.allowdeletetag) +allowmodifytag=$(git config --bool hooks.allowmodifytag) + +# check for no description +projectdesc=$(sed -e '1q' "$GIT_DIR/description") +case "$projectdesc" in +"Unnamed repository"* | "") + echo "*** Project description file hasn't been set" >&2 + exit 1 + ;; +esac + +# --- Check types +# if $newrev is 0000...0000, it's a commit to delete a ref. +zero="0000000000000000000000000000000000000000" +if [ "$newrev" = "$zero" ]; then + newrev_type=delete +else + newrev_type=$(git cat-file -t $newrev) +fi + +case "$refname","$newrev_type" in + refs/tags/*,commit) + # un-annotated tag + short_refname=${refname##refs/tags/} + if [ "$allowunannotated" != "true" ]; then + echo "*** The un-annotated tag, $short_refname, is not allowed in this repository" >&2 + echo "*** Use 'git tag [ -a | -s ]' for tags you want to propagate." >&2 + exit 1 + fi + ;; + refs/tags/*,delete) + # delete tag + if [ "$allowdeletetag" != "true" ]; then + echo "*** Deleting a tag is not allowed in this repository" >&2 + exit 1 + fi + ;; + refs/tags/*,tag) + # annotated tag + if [ "$allowmodifytag" != "true" ] && git rev-parse $refname > /dev/null 2>&1 + then + echo "*** Tag '$refname' already exists." >&2 + echo "*** Modifying a tag is not allowed in this repository." >&2 + exit 1 + fi + ;; + refs/heads/*,commit) + # branch + if [ "$oldrev" = "$zero" -a "$denycreatebranch" = "true" ]; then + echo "*** Creating a branch is not allowed in this repository" >&2 + exit 1 + fi + ;; + refs/heads/*,delete) + # delete branch + if [ "$allowdeletebranch" != "true" ]; then + echo "*** Deleting a branch is not allowed in this repository" >&2 + exit 1 + fi + ;; + refs/remotes/*,commit) + # tracking branch + ;; + refs/remotes/*,delete) + # delete tracking branch + if [ "$allowdeletebranch" != "true" ]; then + echo "*** Deleting a tracking branch is not allowed in this repository" >&2 + exit 1 + fi + ;; + *) + # Anything else (is there anything else?) + echo "*** Update hook: unknown type of update to ref $refname of type $newrev_type" >&2 + exit 1 + ;; +esac + +# --- Finished +exit 0 diff --git a/cope2n-ai-fi/modules/sdsvkie/._bit/index b/cope2n-ai-fi/modules/sdsvkie/._bit/index new file mode 100755 index 0000000..d38c1d3 Binary files /dev/null and b/cope2n-ai-fi/modules/sdsvkie/._bit/index differ diff --git a/cope2n-ai-fi/modules/sdsvkie/._bit/info/exclude b/cope2n-ai-fi/modules/sdsvkie/._bit/info/exclude new file mode 100755 index 0000000..a5196d1 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/._bit/info/exclude @@ -0,0 +1,6 @@ +# git ls-files --others --exclude-from=.git/info/exclude +# Lines that start with '#' are comments. +# For a project mostly in C, the following would be a good set of +# exclude patterns (uncomment them if you want to use them): +# *.[oa] +# *~ diff --git a/cope2n-ai-fi/modules/sdsvkie/._bit/logs/HEAD b/cope2n-ai-fi/modules/sdsvkie/._bit/logs/HEAD new file mode 100755 index 0000000..c8c5efa --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/._bit/logs/HEAD @@ -0,0 +1,4 @@ +0000000000000000000000000000000000000000 6d46ca18144cdffe56a7ed991ffc28b9a42ff548 LeHoang 1684298127 +0700 commit (initial): Initial commit +6d46ca18144cdffe56a7ed991ffc28b9a42ff548 eaff1f59719f9816d2ddddef9b852e34c601dec6 LeHoang 1684305338 +0700 commit: ver: 1.0.1 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8349a89de7fd8c9e6958907047d16bdc23a77adf LeHoang 1684467298 +0700 commit: modify init_predictor diff --git a/cope2n-ai-fi/modules/sdsvkie/._bit/logs/refs/remotes/origin/main b/cope2n-ai-fi/modules/sdsvkie/._bit/logs/refs/remotes/origin/main new file mode 100755 index 0000000..8537273 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/._bit/logs/refs/remotes/origin/main @@ -0,0 +1,4 @@ +0000000000000000000000000000000000000000 6d46ca18144cdffe56a7ed991ffc28b9a42ff548 LeHoang 1684304091 +0700 update by push +6d46ca18144cdffe56a7ed991ffc28b9a42ff548 eaff1f59719f9816d2ddddef9b852e34c601dec6 LeHoang 1684305362 +0700 update by push +eaff1f59719f9816d2ddddef9b852e34c601dec6 308ece8e82dea6ee7833b4652a4417f3590c3dea LeHoang 1684305478 +0700 update by push +308ece8e82dea6ee7833b4652a4417f3590c3dea 8349a89de7fd8c9e6958907047d16bdc23a77adf LeHoang 1684467343 +0700 update by push diff --git a/cope2n-ai-fi/modules/sdsvkie/._bit/objects/02/89d252b8a8a06a0abc6fe4a8ddf918dfeca66a 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newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/README.md b/cope2n-ai-fi/modules/sdsvkie/README.md new file mode 100755 index 0000000..42a8b28 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/README.md @@ -0,0 +1,75 @@ +

+

SDSVKIE

+

+ +***Feature*** +- Extract information from documents: VAT Invoice, Receipt +- Language: VI + EN + +***What's news*** +### - Ver 1.0.1: +- Improve postprocessing for receipts +- Support handling multiple pages for PDF files +- Lastest weight: /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/exp_9_lr5e_6_no_scheduler/best +- Lastest config: /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/exp_9_lr5e_6_no_scheduler/config.yaml + + +## I. Setup +***Dependencies*** +- Python: 3.8 +- Torch: 1.10.2 +- CUDA: 11.6 +- transformers: 4.28.1 +``` +pip install -v -e . +``` + + +## II. Inference +``` +from sdsvkie import Predictor +import cv2 + +predictor = Predictor( + cfg="./workdirs/training/sdsap_receipt/exp_3/config.yaml", + weights="./workdirs/training/sdsap_receipt/exp_3/best", + device="cpu", +) +img = cv2.imread("./demos/4 Sep OPC to Home.jpg") +out = predictor(img) +output = out['end2end_results'] + +``` + + +## III. Training +- Prepare dataset: The structure of the dataset directory is organized as follows: + +└── base_dataset \ + ├── train \ + ├──── sub_dir_1 \ + ├────── img1.txt \ + ├────── img1.txt \ + ├────── ... \ + ├──── sub_dir_2 \ + ├────── img2.txt \ + ├────── img2.txt \ + ├── test \ + ├──── imgn.jpg \ + ├──── imgn.txt + +- Edit and run scripts: +``` +sh ./scripts/train.sh +``` + +# TODO + +- [ ] Add more fields: sub_total, tips, seller_address, item list +- [x] Support muliple pages +- [x] Review result KIE for invoice (vnpt_exp_4_model) +- [x] Fix unnormalize box error in some cases +- [x] Support multiple pages +- [x] Create 200 multiple pages invoice +- [ ] Finalize multi page testset +- [ ] Eval result \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/arial.ttf b/cope2n-ai-fi/modules/sdsvkie/arial.ttf new file mode 100755 index 0000000..ff0815c Binary files /dev/null and b/cope2n-ai-fi/modules/sdsvkie/arial.ttf differ diff --git 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180 8 +49 309 66 334 3 +1165 155 1182 180 7 +49 257 67 281 2 +49 360 68 385 4 +50 412 67 437 5 +51 515 67 539 7 +878 154 896 180 5 +52 156 65 178 1 +52 206 64 229 1 +321 155 339 179 2 diff --git a/cope2n-ai-fi/modules/sdsvkie/demos/test.py b/cope2n-ai-fi/modules/sdsvkie/demos/test.py new file mode 100755 index 0000000..2f6ea26 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/demos/test.py @@ -0,0 +1,948 @@ +# Ultralytics YOLO 🚀, GPL-3.0 license +""" +Model validation metrics +""" +import math +import warnings +from pathlib import Path + +import matplotlib.pyplot as plt +import numpy as np +import torch +import torch.nn as nn + +from sklearn.metrics import confusion_matrix + +# boxes +def box_area(box): + # box = xyxy(4,n) + return (box[2] - box[0]) * (box[3] - box[1]) + + +def bbox_ioa(box1, box2, eps=1e-7): + """Returns the intersection over box2 area given box1, box2. Boxes are x1y1x2y2 + box1: np.array of shape(nx4) + box2: np.array of shape(mx4) + returns: np.array of shape(nxm) + """ + + # Get the coordinates of bounding boxes + b1_x1, b1_y1, b1_x2, b1_y2 = box1.T + b2_x1, b2_y1, b2_x2, b2_y2 = box2.T + + # Intersection area + inter_area = ( + np.minimum(b1_x2[:, None], b2_x2) - np.maximum(b1_x1[:, None], b2_x1) + ).clip(0) * ( + np.minimum(b1_y2[:, None], b2_y2) - np.maximum(b1_y1[:, None], b2_y1) + ).clip( + 0 + ) + + # box2 area + box2_area = (b2_x2 - b2_x1) * (b2_y2 - b2_y1) + eps + + # Intersection over box2 area + return inter_area / box2_area + + +def box_iou(box1, box2, eps=1e-7): + # https://github.com/pytorch/vision/blob/master/torchvision/ops/boxes.py + """ + Return intersection-over-union (Jaccard index) of boxes. + Both sets of boxes are expected to be in (x1, y1, x2, y2) format. + Arguments: + box1 (Tensor[N, 4]) + box2 (Tensor[M, 4]) + Returns: + iou (Tensor[N, M]): the NxM matrix containing the pairwise + IoU values for every element in boxes1 and boxes2 + """ + + # inter(N,M) = (rb(N,M,2) - lt(N,M,2)).clamp(0).prod(2) + (a1, a2), (b1, b2) = box1.unsqueeze(1).chunk(2, 2), box2.unsqueeze(0).chunk(2, 2) + inter = (torch.min(a2, b2) - torch.max(a1, b1)).clamp(0).prod(2) + + # IoU = inter / (area1 + area2 - inter) + return inter / ((a2 - a1).prod(2) + (b2 - b1).prod(2) - inter + eps) + + +def bbox_iou(box1, box2, xywh=True, GIoU=False, DIoU=False, CIoU=False, eps=1e-7): + # Returns Intersection over Union (IoU) of box1(1,4) to box2(n,4) + + # Get the coordinates of bounding boxes + if xywh: # transform from xywh to xyxy + (x1, y1, w1, h1), (x2, y2, w2, h2) = box1.chunk(4, -1), box2.chunk(4, -1) + w1_, h1_, w2_, h2_ = w1 / 2, h1 / 2, w2 / 2, h2 / 2 + b1_x1, b1_x2, b1_y1, b1_y2 = x1 - w1_, x1 + w1_, y1 - h1_, y1 + h1_ + b2_x1, b2_x2, b2_y1, b2_y2 = x2 - w2_, x2 + w2_, y2 - h2_, y2 + h2_ + else: # x1, y1, x2, y2 = box1 + b1_x1, b1_y1, b1_x2, b1_y2 = box1.chunk(4, -1) + b2_x1, b2_y1, b2_x2, b2_y2 = box2.chunk(4, -1) + w1, h1 = b1_x2 - b1_x1, b1_y2 - b1_y1 + eps + w2, h2 = b2_x2 - b2_x1, b2_y2 - b2_y1 + eps + + # Intersection area + inter = (b1_x2.minimum(b2_x2) - b1_x1.maximum(b2_x1)).clamp(0) * ( + b1_y2.minimum(b2_y2) - b1_y1.maximum(b2_y1) + ).clamp(0) + + # Union Area + union = w1 * h1 + w2 * h2 - inter + eps + + # IoU + iou = inter / union + if CIoU or DIoU or GIoU: + cw = b1_x2.maximum(b2_x2) - b1_x1.minimum( + b2_x1 + ) # convex (smallest enclosing box) width + ch = b1_y2.maximum(b2_y2) - b1_y1.minimum(b2_y1) # convex height + if CIoU or DIoU: # Distance or Complete IoU https://arxiv.org/abs/1911.08287v1 + c2 = cw**2 + ch**2 + eps # convex diagonal squared + rho2 = ( + (b2_x1 + b2_x2 - b1_x1 - b1_x2) ** 2 + + (b2_y1 + b2_y2 - b1_y1 - b1_y2) ** 2 + ) / 4 # center dist ** 2 + if ( + CIoU + ): # https://github.com/Zzh-tju/DIoU-SSD-pytorch/blob/master/utils/box/box_utils.py#L47 + v = (4 / math.pi**2) * ( + torch.atan(w2 / h2) - torch.atan(w1 / h1) + ).pow(2) + with torch.no_grad(): + alpha = v / (v - iou + (1 + eps)) + return iou - (rho2 / c2 + v * alpha) # CIoU + return iou - rho2 / c2 # DIoU + c_area = cw * ch + eps # convex area + return ( + iou - (c_area - union) / c_area + ) # GIoU https://arxiv.org/pdf/1902.09630.pdf + return iou # IoU + + +def mask_iou(mask1, mask2, eps=1e-7): + """ + mask1: [N, n] m1 means number of predicted objects + mask2: [M, n] m2 means number of gt objects + Note: n means image_w x image_h + return: masks iou, [N, M] + """ + intersection = torch.matmul(mask1, mask2.t()).clamp(0) + union = ( + mask1.sum(1)[:, None] + mask2.sum(1)[None] + ) - intersection # (area1 + area2) - intersection + return intersection / (union + eps) + + +def masks_iou(mask1, mask2, eps=1e-7): + """ + mask1: [N, n] m1 means number of predicted objects + mask2: [N, n] m2 means number of gt objects + Note: n means image_w x image_h + return: masks iou, (N, ) + """ + intersection = (mask1 * mask2).sum(1).clamp(0) # (N, ) + union = (mask1.sum(1) + mask2.sum(1))[ + None + ] - intersection # (area1 + area2) - intersection + return intersection / (union + eps) + + +def smooth_BCE( + eps=0.1, +): # https://github.com/ultralytics/yolov3/issues/238#issuecomment-598028441 + # return positive, negative label smoothing BCE targets + return 1.0 - 0.5 * eps, 0.5 * eps + + +# losses +class FocalLoss(nn.Module): + # Wraps focal loss around existing loss_fcn(), i.e. criteria = FocalLoss(nn.BCEWithLogitsLoss(), gamma=1.5) + def __init__(self, loss_fcn, gamma=1.5, alpha=0.25): + super().__init__() + self.loss_fcn = loss_fcn # must be nn.BCEWithLogitsLoss() + self.gamma = gamma + self.alpha = alpha + self.reduction = loss_fcn.reduction + self.loss_fcn.reduction = "none" # required to apply FL to each element + + def forward(self, pred, true): + loss = self.loss_fcn(pred, true) + # p_t = torch.exp(-loss) + # loss *= self.alpha * (1.000001 - p_t) ** self.gamma # non-zero power for gradient stability + + # TF implementation https://github.com/tensorflow/addons/blob/v0.7.1/tensorflow_addons/losses/focal_loss.py + pred_prob = torch.sigmoid(pred) # prob from logits + p_t = true * pred_prob + (1 - true) * (1 - pred_prob) + alpha_factor = true * self.alpha + (1 - true) * (1 - self.alpha) + modulating_factor = (1.0 - p_t) ** self.gamma + loss *= alpha_factor * modulating_factor + + if self.reduction == "mean": + return loss.mean() + elif self.reduction == "sum": + return loss.sum() + else: # 'none' + return loss + + +class ConfusionMatrix: + # Updated version of https://github.com/kaanakan/object_detection_confusion_matrix + def __init__(self, nc, conf=0.25, iou_thres=0.45): + self.matrix = np.zeros((nc + 1, nc + 1)) + self.nc = nc # number of classes + self.conf = conf + self.iou_thres = iou_thres + + def process_batch(self, detections, labels): + """ + Return intersection-over-union (Jaccard index) of boxes. + Both sets of boxes are expected to be in (x1, y1, x2, y2) format. + Arguments: + detections (Array[N, 6]), x1, y1, x2, y2, conf, class + labels (Array[M, 5]), class, x1, y1, x2, y2 + Returns: + None, updates confusion matrix accordingly + """ + if detections is None: + gt_classes = labels.int() + for gc in gt_classes: + self.matrix[self.nc, gc] += 1 # background FN + return + + detections = detections[detections[:, 4] > self.conf] + gt_classes = labels[:, 0].int() + detection_classes = detections[:, 5].int() + iou = box_iou(labels[:, 1:], detections[:, :4]) + + x = torch.where(iou > self.iou_thres) + if x[0].shape[0]: + matches = ( + torch.cat((torch.stack(x, 1), iou[x[0], x[1]][:, None]), 1) + .cpu() + .numpy() + ) + if x[0].shape[0] > 1: + matches = matches[matches[:, 2].argsort()[::-1]] + matches = matches[np.unique(matches[:, 1], return_index=True)[1]] + matches = matches[matches[:, 2].argsort()[::-1]] + matches = matches[np.unique(matches[:, 0], return_index=True)[1]] + else: + matches = np.zeros((0, 3)) + + n = matches.shape[0] > 0 + m0, m1, _ = matches.transpose().astype(int) + for i, gc in enumerate(gt_classes): + j = m0 == i + if n and sum(j) == 1: + self.matrix[detection_classes[m1[j]], gc] += 1 # correct + else: + self.matrix[self.nc, gc] += 1 # true background + + if n: + for i, dc in enumerate(detection_classes): + if not any(m1 == i): + self.matrix[dc, self.nc] += 1 # predicted background + + def matrix(self): + return self.matrix + + def tp_fp(self): + tp = self.matrix.diagonal() # true positives + fp = self.matrix.sum(1) - tp # false positives + # fn = self.matrix.sum(0) - tp # false negatives (missed detections) + return tp[:-1], fp[:-1] # remove background class + + # @TryExcept("WARNING ⚠️ ConfusionMatrix plot failure") + def plot(self, normalize=True, save_dir="", names=()): + import seaborn as sn + + array = self.matrix / ( + (self.matrix.sum(0).reshape(1, -1) + 1e-9) if normalize else 1 + ) # normalize columns + array[array < 0.005] = np.nan # don't annotate (would appear as 0.00) + + fig, ax = plt.subplots(1, 1, figsize=(12, 9), tight_layout=True) + nc, nn = self.nc, len(names) # number of classes, names + sn.set(font_scale=1.0 if nc < 50 else 0.8) # for label size + labels = (0 < nn < 99) and (nn == nc) # apply names to ticklabels + ticklabels = (names + ["background"]) if labels else "auto" + with warnings.catch_warnings(): + warnings.simplefilter( + "ignore" + ) # suppress empty matrix RuntimeWarning: All-NaN slice encountered + sn.heatmap( + array, + ax=ax, + annot=nc < 30, + annot_kws={"size": 8}, + cmap="Blues", + fmt=".2f", + square=True, + vmin=0.0, + xticklabels=ticklabels, + yticklabels=ticklabels, + ).set_facecolor((1, 1, 1)) + ax.set_xlabel("True") + ax.set_ylabel("Predicted") + ax.set_title("Confusion Matrix") + fig.savefig(Path(save_dir) / "confusion_matrix.png", dpi=250) + plt.close(fig) + + def print(self): + for i in range(self.nc + 1): + print(" ".join(map(str, self.matrix[i]))) + + +def smooth(y, f=0.05): + # Box filter of fraction f + nf = round(len(y) * f * 2) // 2 + 1 # number of filter elements (must be odd) + p = np.ones(nf // 2) # ones padding + yp = np.concatenate((p * y[0], y, p * y[-1]), 0) # y padded + return np.convolve(yp, np.ones(nf) / nf, mode="valid") # y-smoothed + + +def plot_pr_curve(px, py, ap, save_dir=Path("pr_curve.png"), names=()): + # Precision-recall curve + fig, ax = plt.subplots(1, 1, figsize=(9, 6), tight_layout=True) + py = np.stack(py, axis=1) + + if 0 < len(names) < 21: # display per-class legend if < 21 classes + for i, y in enumerate(py.T): + ax.plot( + px, y, linewidth=1, label=f"{names[i]} {ap[i, 0]:.3f}" + ) # plot(recall, precision) + else: + ax.plot(px, py, linewidth=1, color="grey") # plot(recall, precision) + + ax.plot( + px, + py.mean(1), + linewidth=3, + color="blue", + label="all classes %.3f mAP@0.5" % ap[:, 0].mean(), + ) + ax.set_xlabel("Recall") + ax.set_ylabel("Precision") + ax.set_xlim(0, 1) + ax.set_ylim(0, 1) + ax.legend(bbox_to_anchor=(1.04, 1), loc="upper left") + ax.set_title("Precision-Recall Curve") + fig.savefig(save_dir, dpi=250) + plt.close(fig) + + +def plot_mc_curve( + px, + py, + save_dir=Path("mc_curve.png"), + names=(), + xlabel="Confidence", + ylabel="Metric", +): + # Metric-confidence curve + fig, ax = plt.subplots(1, 1, figsize=(9, 6), tight_layout=True) + + if 0 < len(names) < 21: # display per-class legend if < 21 classes + for i, y in enumerate(py): + ax.plot(px, y, linewidth=1, label=f"{names[i]}") # plot(confidence, metric) + else: + ax.plot(px, py.T, linewidth=1, color="grey") # plot(confidence, metric) + + y = smooth(py.mean(0), 0.05) + ax.plot( + px, + y, + linewidth=3, + color="blue", + label=f"all classes {y.max():.2f} at {px[y.argmax()]:.3f}", + ) + ax.set_xlabel(xlabel) + ax.set_ylabel(ylabel) + ax.set_xlim(0, 1) + ax.set_ylim(0, 1) + ax.legend(bbox_to_anchor=(1.04, 1), loc="upper left") + ax.set_title(f"{ylabel}-Confidence Curve") + fig.savefig(save_dir, dpi=250) + plt.close(fig) + + +def compute_ap(recall, precision): + """Compute the average precision, given the recall and precision curves + # Arguments + recall: The recall curve (list) + precision: The precision curve (list) + # Returns + Average precision, precision curve, recall curve + """ + + # Append sentinel values to beginning and end + mrec = np.concatenate(([0.0], recall, [1.0])) + mpre = np.concatenate(([1.0], precision, [0.0])) + + # Compute the precision envelope + mpre = np.flip(np.maximum.accumulate(np.flip(mpre))) + + # Integrate area under curve + method = "interp" # methods: 'continuous', 'interp' + if method == "interp": + x = np.linspace(0, 1, 101) # 101-point interp (COCO) + ap = np.trapz(np.interp(x, mrec, mpre), x) # integrate + else: # 'continuous' + i = np.where(mrec[1:] != mrec[:-1])[0] # points where x-axis (recall) changes + ap = np.sum((mrec[i + 1] - mrec[i]) * mpre[i + 1]) # area under curve + + return ap, mpre, mrec + + +def ap_per_class( + tp, + conf, + pred_cls, + target_cls, + plot=False, + save_dir=Path(), + names=(), + eps=1e-16, + prefix="", +): + """Compute the average precision, given the recall and precision curves. + Source: https://github.com/rafaelpadilla/Object-Detection-Metrics. + # Arguments + tp: True positives (nparray, nx1 or nx10). + conf: Objectness value from 0-1 (nparray). + pred_cls: Predicted object classes (nparray). + target_cls: True object classes (nparray). + plot: Plot precision-recall curve at mAP@0.5 + save_dir: Plot save directory + # Returns + The average precision as computed in py-faster-rcnn. + """ + + # Sort by objectness + i = np.argsort(-conf) + tp, conf, pred_cls = tp[i], conf[i], pred_cls[i] + + # Find unique classes + unique_classes, nt = np.unique(target_cls, return_counts=True) + nc = unique_classes.shape[0] # number of classes, number of detections + + # Create Precision-Recall curve and compute AP for each class + px, py = np.linspace(0, 1, 1000), [] # for plotting + ap, p, r = np.zeros((nc, tp.shape[1])), np.zeros((nc, 1000)), np.zeros((nc, 1000)) + for ci, c in enumerate(unique_classes): + i = pred_cls == c + n_l = nt[ci] # number of labels + n_p = i.sum() # number of predictions + if n_p == 0 or n_l == 0: + continue + + # Accumulate FPs and TPs + fpc = (1 - tp[i]).cumsum(0) + tpc = tp[i].cumsum(0) + + # Recall + recall = tpc / (n_l + eps) # recall curve + r[ci] = np.interp( + -px, -conf[i], recall[:, 0], left=0 + ) # negative x, xp because xp decreases + + # Precision + precision = tpc / (tpc + fpc) # precision curve + p[ci] = np.interp(-px, -conf[i], precision[:, 0], left=1) # p at pr_score + + # AP from recall-precision curve + for j in range(tp.shape[1]): + ap[ci, j], mpre, mrec = compute_ap(recall[:, j], precision[:, j]) + if plot and j == 0: + py.append(np.interp(px, mrec, mpre)) # precision at mAP@0.5 + + # from IPython import embed; embed() + # Compute F1 (harmonic mean of precision and recall) + f1 = 2 * p * r / (p + r + eps) + names = [ + v for k, v in names.items() if k in unique_classes + ] # list: only classes that have data + names = dict(enumerate(names)) # to dict + if plot: + plot_pr_curve(px, py, ap, save_dir / f"{prefix}PR_curve.png", names) + plot_mc_curve(px, f1, save_dir / f"{prefix}F1_curve.png", names, ylabel="F1") + plot_mc_curve( + px, p, save_dir / f"{prefix}P_curve.png", names, ylabel="Precision" + ) + plot_mc_curve(px, r, save_dir / f"{prefix}R_curve.png", names, ylabel="Recall") + + i = smooth(f1.mean(0), 0.1).argmax() # max F1 index + p, r, f1 = p[:, i], r[:, i], f1[:, i] + tp = (r * nt).round() # true positives + fp = (tp / (p + eps) - tp).round() # false positives + return tp, fp, p, r, f1, ap, unique_classes.astype(int) + + +class Metric: + def __init__(self) -> None: + self.p = [] # (nc, ) + self.r = [] # (nc, ) + self.f1 = [] # (nc, ) + self.all_ap = [] # (nc, 10) + self.ap_class_index = [] # (nc, ) + self.nc = 0 + + @property + def ap50(self): + """AP@0.5 of all classes. + Return: + (nc, ) or []. + """ + return self.all_ap[:, 0] if len(self.all_ap) else [] + + @property + def ap(self): + """AP@0.5:0.95 + Return: + (nc, ) or []. + """ + return self.all_ap.mean(1) if len(self.all_ap) else [] + + @property + def mp(self): + """mean precision of all classes. + Return: + float. + """ + return self.p.mean() if len(self.p) else 0.0 + + @property + def mr(self): + """mean recall of all classes. + Return: + float. + """ + return self.r.mean() if len(self.r) else 0.0 + + @property + def map50(self): + """Mean AP@0.5 of all classes. + Return: + float. + """ + return self.all_ap[:, 0].mean() if len(self.all_ap) else 0.0 + + @property + def map75(self): + """Mean AP@0.75 of all classes. + Return: + float. + """ + return self.all_ap[:, 5].mean() if len(self.all_ap) else 0.0 + + @property + def map(self): + """Mean AP@0.5:0.95 of all classes. + Return: + float. + """ + return self.all_ap.mean() if len(self.all_ap) else 0.0 + + def mean_results(self): + """Mean of results, return mp, mr, map50, map""" + return [self.mp, self.mr, self.map50, self.map] + + def class_result(self, i): + """class-aware result, return p[i], r[i], ap50[i], ap[i]""" + return self.p[i], self.r[i], self.ap50[i], self.ap[i] + + @property + def maps(self): + """mAP of each class""" + maps = np.zeros(self.nc) + self.map + for i, c in enumerate(self.ap_class_index): + maps[c] = self.ap[i] + return maps + + def fitness(self): + # Model fitness as a weighted combination of metrics + w = [0.0, 0.0, 0.1, 0.9] # weights for [P, R, mAP@0.5, mAP@0.5:0.95] + return (np.array(self.mean_results()) * w).sum() + + def update(self, results): + """ + Args: + results: tuple(p, r, ap, f1, ap_class) + """ + self.p, self.r, self.f1, self.all_ap, self.ap_class_index = results + + +class DetMetrics: + def __init__(self, save_dir=Path("."), plot=False, names=()) -> None: + self.save_dir = save_dir + self.plot = plot + self.names = names + self.box = Metric() + self.speed = { + "preprocess": 0.0, + "inference": 0.0, + "loss": 0.0, + "postprocess": 0.0, + } + self.probs = {} + self.tp, self.fp = [], [] + + def process(self, tp, conf, pred_cls, target_cls): + + if len(conf) > 0: + for cls_id in range(len(self.names)): + conf_with_cls = conf[np.where(pred_cls == cls_id)] + if len(conf_with_cls) > 0: + highest_prob = conf_with_cls.max() + self.probs[self.names[cls_id]] = [highest_prob] + + results = ap_per_class( + tp, + conf, + pred_cls, + target_cls, + plot=self.plot, + save_dir=self.save_dir, + names=self.names, + ) + self.tp, self.fp = results[:2] + + results = results[2:] + self.box.nc = len(self.names) + self.box.update(results) + + @property + def keys(self): + return [ + "metrics/precision(B)", + "metrics/recall(B)", + "metrics/mAP50(B)", + "metrics/mAP50-95(B)", + ] + + def mean_results(self): + return self.box.mean_results() + + def class_result(self, i): + return self.box.class_result(i) + + @property + def maps(self): + return self.box.maps + + @property + def fitness(self): + return self.box.fitness() + + @property + def ap_class_index(self): + return self.box.ap_class_index + + @property + def results_dict(self): + return dict(zip(self.keys + ["fitness"], self.mean_results() + [self.fitness])) + + def custom_result(self, instances_info =None, iou_match_dict: dict = None, prob_of_classes: dict = None): + """_summary_ + + Args: + instances_info (np.ndarray, optional): _description_. Defaults to None. + iou_list (list, optional): _description_. Defaults to None. + iou_match_dict (dict, optional): _description_. Defaults to None. + prob_of_classes (dict, optional): _description_. Defaults to None. + + Returns: + _type_: _description_ + """ + + instances_info = instances_info.tolist() if isinstance(instances_info, np.ndarray) else instances_info + total_instances = sum(instances_info) + total_instances = total_instances.item() if not isinstance(total_instances, int) else total_instances + + custom_res = {} + + for ci, c in self.names.items(): + iou_match = iou_match_dict[c] + average_iou = np.mean(iou_match).item() if len(iou_match) > 0 else 0 + _tp = self.tp[ci] if len(self.tp) == len(self.names) else 0 + _fp = self.fp[ci] if len(self.fp) == len(self.names) else 0 + _miss = instances_info[ci] - _tp + custom_res.update( + { + self.names[ci]: { + "actual": instances_info[ci], + "correct": int(_tp), + "missed_detection": int(_miss), + "false_detection": int(_fp), + "average_iou": round(average_iou, 4), + "average_dice": 0 + } + } + ) + + custom_res.update({ + "probability": prob_of_classes, + "average": { + "actual": int(total_instances // len(self.names)), + "correct": int(self.tp.sum() // len(self.names)) if len(self.tp) > 0 else 0, + "missed_detection": 0, + "false_detection": int(self.fp.sum() // len(self.names)) if len(self.fp) > 0 else 0, + "average_iou": round(np.mean([custom_res[cls_name]['average_iou'] for cls_name in self.names.values()]).item(), 4), + "average_dice": 0, + }, + "total": { + "actual": total_instances, + "correct": int(self.tp.sum()) if len(self.tp) > 0 else 0 , + "missed_detection": 0, + "false_detection": int(self.fp.sum()) if len(self.fp) > 0 else 0, + }, + }) + custom_res["total"]["missed_detection"] = ( + custom_res["total"]["actual"] - custom_res["total"]["correct"] + ) + custom_res["average"]["missed_detection"] = custom_res["total"][ + "missed_detection" + ] // len(self.names) + + + + return custom_res + + +class SegmentMetrics: + def __init__(self, save_dir=Path("."), plot=False, names=()) -> None: + self.save_dir = save_dir + self.plot = plot + self.names = names + self.box = Metric() + self.seg = Metric() + self.speed = { + "preprocess": 0.0, + "inference": 0.0, + "loss": 0.0, + "postprocess": 0.0, + } + self.tp = [] + self.fp = [] + self.probs = {} + + + def process(self, tp_m, tp_b, conf, pred_cls, target_cls): + + if len(conf) > 0: + for cls_id in range(len(self.names)): + conf_with_cls = conf[np.where(pred_cls == cls_id)] + if len(conf_with_cls) > 0: + highest_prob = conf_with_cls.max() + self.probs[self.names[cls_id]] = [highest_prob] + + + res_mask = ap_per_class( + tp_m, + conf, + pred_cls, + target_cls, + plot=self.plot, + save_dir=self.save_dir, + names=self.names, + prefix="Mask", + ) + + tp, fp, results_mask = res_mask[0], res_mask[1], res_mask[2:] + self.seg.nc = len(self.names) + self.seg.update(results_mask) + self.tp = tp + self.fp = fp + # print(self.tp, self.fp) + + results_box = ap_per_class( + tp_b, + conf, + pred_cls, + target_cls, + plot=self.plot, + save_dir=self.save_dir, + names=self.names, + prefix="Box", + )[2:] + self.box.nc = len(self.names) + self.box.update(results_box) + + @property + def keys(self): + return [ + "metrics/precision(B)", + "metrics/recall(B)", + "metrics/mAP50(B)", + "metrics/mAP50-95(B)", + "metrics/precision(M)", + "metrics/recall(M)", + "metrics/mAP50(M)", + "metrics/mAP50-95(M)", + ] + + def mean_results(self): + return self.box.mean_results() + self.seg.mean_results() + + def class_result(self, i): + return self.box.class_result(i) + self.seg.class_result(i) + + def custom_result(self, instances_info =None, iou_match_dict: dict = None, prob_of_classes: dict = None): + """_summary_ + + Args: + instances_info (np.ndarray, optional): _description_. Defaults to None. + iou_list (list, optional): _description_. Defaults to None. + iou_match_dict (dict, optional): _description_. Defaults to None. + prob_of_classes (dict, optional): _description_. Defaults to None. + + Returns: + _type_: _description_ + """ + + instances_info = instances_info.tolist() if isinstance(instances_info, np.ndarray) else instances_info + total_instances = sum(instances_info) + total_instances = total_instances.item() if not isinstance(total_instances, int) else total_instances + + custom_res = {} + + for ci, c in self.names.items(): + iou_match = iou_match_dict[c] + average_iou = np.mean(iou_match).item() if len(iou_match) > 0 else 0 + _tp = self.tp[ci] if len(self.tp) == len(self.names) else 0 + _fp = self.fp[ci] if len(self.fp) == len(self.names) else 0 + _miss = instances_info[ci] - _tp + custom_res.update( + { + self.names[ci]: { + "actual": instances_info[ci], + "correct": int(_tp), + "missed_detection": int(_miss), + "false_detection": int(_fp), + "average_iou": round(average_iou, 4), + "average_dice": 0 + } + } + ) + + custom_res.update({ + "probability": prob_of_classes, + "average": { + "actual": int(total_instances // len(self.names)), + "correct": int(self.tp.sum() // len(self.names)) if len(self.tp) > 0 else 0, + "missed_detection": 0, + "false_detection": int(self.fp.sum() // len(self.names)) if len(self.fp) > 0 else 0, + "average_iou": round(np.mean([custom_res[cls_name]['average_iou'] for cls_name in self.names.values()]).item(), 4), + "average_dice": 0, + }, + "total": { + "actual": total_instances, + "correct": int(self.tp.sum()) if len(self.tp) > 0 else 0 , + "missed_detection": 0, + "false_detection": int(self.fp.sum()) if len(self.fp) > 0 else 0, + }, + }) + custom_res["total"]["missed_detection"] = ( + custom_res["total"]["actual"] - custom_res["total"]["correct"] + ) + custom_res["average"]["missed_detection"] = custom_res["total"][ + "missed_detection" + ] // len(self.names) + + + return custom_res + + @property + def maps(self): + return self.box.maps + self.seg.maps + + @property + def fitness(self): + return self.seg.fitness() + self.box.fitness() + + @property + def ap_class_index(self): + # boxes and masks have the same ap_class_index + return self.box.ap_class_index + + @property + def results_dict(self): + return dict(zip(self.keys + ["fitness"], self.mean_results() + [self.fitness])) + + +class ClassifyMetrics: + def __init__(self) -> None: + self.top1 = 0 + self.top5 = 0 + + self.speed = { + "preprocess": 0.0, + "inference": 0.0, + "loss": 0.0, + "postprocess": 0.0, + } + + + def process(self, targets, pred): + # target classes and predicted classes + pred, targets = torch.cat(pred), torch.cat(targets) + correct = (targets[:, None] == pred).float() + acc = torch.stack( + (correct[:, 0], correct.max(1).values), dim=1 + ) # (top1, top5) accuracy + self.top1, self.top5 = acc.mean(0).tolist() + + def custom_result(self ,targets, pred): + # from IPython import embed; embed() + metric_per_class = {} + pred, targets = torch.cat(pred), torch.cat(targets) + pred = pred.cpu().numpy()[:, 0] + targets = targets.cpu().numpy() + conf_mat = confusion_matrix(targets, pred) + + """{ + "actual": + "correct": + "recall": + "precision": + } + """ + k = conf_mat.shape[0] + for cls_id in range(k): + tp = conf_mat[cls_id, cls_id] + fp = np.sum(conf_mat[cls_id, :]) - tp + fn = np.sum(conf_mat[:, cls_id]) - tp + tn = np.sum(conf_mat) - tp - fp - fn + + res_per_class = { + "actual": tp + fp, + "correct": tp, + "miss_detection": 0, + "false_detection": fp, + "recall": 0 if tp + fn == 0 else tp / (tp+fn), + "precision": tp / (tp + fp) + } + + + metric_per_class[cls_id] = res_per_class + + return metric_per_class + + + @property + def fitness(self): + return self.top5 + + @property + def results_dict(self): + return dict(zip(self.keys + ["fitness"], [self.top1, self.top5, self.fitness])) + + @property + def keys(self): + return ["metrics/accuracy_top1", "metrics/accuracy_top5"] + + +if __name__ == "__main__": + det_metric = DetMetrics() + diff --git a/cope2n-ai-fi/modules/sdsvkie/eval_with_api.py b/cope2n-ai-fi/modules/sdsvkie/eval_with_api.py new file mode 100755 index 0000000..fe4f050 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/eval_with_api.py @@ -0,0 +1,275 @@ +import json +import logging +from pathlib import Path +from typing import Any, Dict, List, Optional, Union + +import requests +import tqdm +from sdsvkie.utils.eval_kie import eval_kie +from sdsvkie.utils.io_file import read_json, write_json + +logging.basicConfig( + level=logging.INFO, + # format="" + +) +logger = logging.getLogger() + + +HEADERS = { + 'accept': 'application/json', + 'Authorization': 'Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJleHAiOjE2OTA2ODk4ODcsInVzZXJuYW1lIjoiYWRtaW4ifQ.Oybpc9tBsN35vCn3jzekkABDQKJT6yO1aBBJ4rMNln0' +} + +URL = "http://107.120.133.27:8082/predict/image" + + +def run( + data_dir: str, + url: str, + gt_path: str, + field_pred_file: str, + samples: Union[int, None] = None, + +): + + files = get_files(data_dir, recursive=False, limit=samples) + preds = predict(url, files) + + ## process for table + # table_eval_result = {} + # table_preds = get_table_preds(preds) + # table_eval_result = + + # process for seller, buyer, ... + field_eval_result = {} + # field_preds = get_field_preds_from_api(api_preds=preds) + field_preds = get_field_preds_from_file(pred_file=field_pred_file) + classes = get_classes(preds=field_preds) + if len(classes) == 0: + raise Exception("Can not get the classes list") + field_eval_result = eval( + gt=gt_path, + pred=field_preds, + classes=classes, + classes_ignore=['other', 'table'] + ) + print(field_eval_result) + ## combine result + combine_result = {} + # combine_result = combine_result(table_res=table_eval_result, field_res=field_eval_result) + + + print_result( + data_path=data_dir, + num_samples=len(list(field_preds.keys())), + target_level=0.05, + result=1.0, # edit here + ) + return combine_result + + + +def print_result( + data_path: str, + num_samples:int, + target_level: float, + result: float, + metric: str = "NLD", + avg_time: float = 1.6363 + ): + + print(f"Path of validation dataset: {data_path}\n" + + f"Number of validation dataset: {num_samples}\n" + + f"Evaluation metric: {metric}\n" + + f"Target level: {target_level}\n" + + f"Archieved level: {result}\n" + + f"Average time: {avg_time}\n" + + f"Verification result: {'PASS' if result > target_level else 'FAILED'}" + ) + + +def get_field_preds_from_api(api_preds: str) -> dict: + field_preds = get_fields_preds(api_preds) + field_preds = combine_to_single_file(field_preds) + return field_preds + +def get_field_preds_from_file(pred_file: str) -> dict: + """ + Get predictions from json file + """ + field_preds = read_json(pred_file) + return field_preds + + + +def get_fields_preds(preds: List[Dict]): + preds = [ + {item['file_path']: format_output_api(item['response_dict'])} + for item in preds + ] + return preds + +def combine_result(table_res: Dict, field_res: Dict): + return {} + +def _str2dict(text: str) -> Dict: + try: + data = json.loads(text) + except Exception as err: + logger.error(f"{err} - data: {text}") + data = {} + return data + + +def predict_one_file(url: str, file: Union[str, Path]) -> Dict: + """ + Output format: + { + file_path: path of file + response_dict: + } + """ + if isinstance(file, str): + file = Path(file) + + payload = {} + filename = file.name + files = [ + ( + 'file', + ( + filename, + open(str(file), 'rb'), + 'application/pdf' + ) + ) + ] + # logger.info(f"Files: {file}") + response = requests.request( + "POST", url, headers=HEADERS, data=payload, files=files) + + response_dict = _str2dict(response.text) + + return { + "file_path": str(file), + "pred_data": response_dict + } + + +def predict(url: str, files: List[Union[str, Path]]) -> List[Dict]: + """ + List of {'file_path', 'response_dict'} + """ + + preds = [] + for idx, file in tqdm.tqdm(enumerate(files)): + try: + pred = predict_one_file(url, file) + preds.append(pred) + except: + logger.info(f"Error at file: {file}") + return preds + + +def get_files(data_dir: str, recursive: bool = False, limit: Union[int, None] = None) -> List[Union[Path, str]]: + if recursive: + files = Path(data_dir).rglob("*") + else: + files = Path(data_dir).glob("*") + + if limit: + files = list(files)[:limit] + return files + + +def _stem_filename(filename: str) -> str: + """ + Stem a file path: x/y.txt -> y + """ + return Path(filename).stem + + +def format_output_api(output_api: Dict, skip_fields=['table']) -> Dict: + if "pages" not in output_api: + return {} + pages = output_api['pages'] + + result = {} + for page in pages: + fields = page['fields'] + for field_item in fields: + field_label, field_value = field_item['label'], field_item['value'] + if field_label in result or field_label in skip_fields: + continue + result[field_label] = field_value + return result + + +def combine_to_single_file(preds: List[Dict]) -> None: + if len(preds) == 0: + return {} + combined_data = { + _stem_filename(item["filename"]): item["pred_data"] + for item in preds + } + return combined_data + + +def eval( + gt: Union[str, Dict], + pred: Union[str, Dict], + classes: List[str], + classes_ignore: List[str] = [] +) -> Dict: + eval_res = eval_kie( + gt_e2e_path=gt, + pred_e2e_path=pred, + kie_labels=classes, + skip_labels=classes_ignore + ) + return eval_res + + +def get_classes(preds: Dict) -> List[str]: + classes = [] + for k, v in preds.items(): + if v: + classes = list(v.keys()) + break + return classes + + +def test(): + import requests + + url = "http://107.120.133.27:8082/predict/image" + + payload = {} + files = [ + ('file', ('(1 of 19)_HOADON_1C23TYY_50.pdf', open( + '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/PV2/final/all_in/(1 of 19)_HOADON_1C23TYY_50.pdf', 'rb'), 'application/pdf')) + ] + headers = { + 'accept': 'application/json', + 'Authorization': 'Bearer eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJleHAiOjE2OTA2ODk4ODcsInVzZXJuYW1lIjoiYWRtaW4ifQ.Oybpc9tBsN35vCn3jzekkABDQKJT6yO1aBBJ4rMNln0' + } + + response = requests.request( + "POST", url, headers=headers, data=payload, files=files) + + print(response.text) + # print(json.loa ds(response.text)) + + +if __name__ == "__main__": + limit = 5 + run( + data_dir="/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/PV2/final/all_in", + url=URL, + gt_path="/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/PV2/final/all_in.json", + field_pred_file="/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/invoice_all_in_final_e2e_21072023_5.json", + samples=limit + ) + + # test() diff --git a/cope2n-ai-fi/modules/sdsvkie/index.html b/cope2n-ai-fi/modules/sdsvkie/index.html new file mode 100755 index 0000000..af4f8eb --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/index.html @@ -0,0 +1,15 @@ +Google



 

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Google c cc thứ tiếng: English Franais 繁體中文

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\ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/notebooks/data.ipynb b/cope2n-ai-fi/modules/sdsvkie/notebooks/data.ipynb new file mode 100755 index 0000000..863b51b --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/notebooks/data.ipynb @@ -0,0 +1,2817 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from PIL import Image, ImageDraw, ImageFont\n", + "import os \n", + "import random\n", + "import cv2\n", + "import numpy as np \n", + "from pathlib import Path" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "\n", + "def visualize_kie(\n", + " img,\n", + " boxes, \n", + " pred_labels, \n", + " skip_classes=['other'], \n", + " image_name=\"out_kie.jpg\", \n", + " outdir=\"workdirs/visualize\"\n", + " ):\n", + " \"\"\"Visualize kie output \n", + "\n", + " Args:\n", + " image (PIL.Image): _description_\n", + " boxes (list[xyxy]): list of xyxy boxes\n", + " kie_preds (list[str]): _description_\n", + " skip_classes (list[str], optional): list of skip labels. Defaults to ['other'].\n", + " image_path (str, optional): _description_. Defaults to None.\n", + " outdir (_type_, optional): _description_. Defaults to None.\n", + " \"\"\"\n", + " if not os.path.exists(outdir):\n", + " os.makedirs(outdir, exist_ok=True)\n", + "\n", + " image = img.copy()\n", + " if isinstance(image, np.ndarray):\n", + " image = Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))\n", + " \n", + " set_labels = sorted(list(set(pred_labels)))\n", + " colors = [\n", + " (\n", + " random.randint(0, 255),\n", + " random.randint(0, 255),\n", + " random.randint(0, 255),\n", + " ) for _ in range(len(set_labels))\n", + " ]\n", + "\n", + " text_checkin = [0] * len(set_labels)\n", + "\n", + " draw = ImageDraw.Draw(image)\n", + " font = ImageFont.load_default()\n", + " for i, pred_label in enumerate(pred_labels):\n", + " if pred_label in skip_classes:\n", + " continue\n", + " pred_label_idx = set_labels.index(pred_label)\n", + " box = boxes[i]\n", + " color = colors[pred_label_idx]\n", + " draw.rectangle(box,fill=None, outline=color)\n", + "\n", + " # skip visualize text label for other boxes \n", + " if text_checkin[set_labels.index(pred_label)] == 0:\n", + " draw.text((int(box[0])+10, int(box[1])-10),fill=color, text=pred_label, font = font)\n", + " text_checkin[pred_label_idx] = 1\n", + " image.save(os.path.join(outdir, image_name))\n", + "\n", + "def visualize_ocr(\n", + " img,\n", + " boxes, \n", + " texts,\n", + " image_name=\"out_ocr.jpg\", \n", + " outdir=\"workdirs/visualize\"\n", + " ):\n", + " \"\"\"Visualize kie output \n", + "\n", + " Args:\n", + " image (PIL.Image): _description_\n", + " boxes (list[xyxy]): list of xyxy boxes\n", + " kie_preds (list[str]): _description_\n", + " skip_classes (list[str], optional): list of skip labels. Defaults to ['other'].\n", + " image_path (str, optional): _description_. Defaults to None.\n", + " outdir (_type_, optional): _description_. Defaults to None.\n", + " \"\"\"\n", + " if not os.path.exists(outdir):\n", + " os.makedirs(outdir, exist_ok=True)\n", + "\n", + " image = img.copy()\n", + " if isinstance(image, np.ndarray):\n", + " image = Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB))\n", + " color = (\n", + " random.randint(0, 255),\n", + " random.randint(0, 255),\n", + " random.randint(0, 255),\n", + " )\n", + "\n", + " \n", + "\n", + " draw = ImageDraw.Draw(image)\n", + " font = ImageFont.load_default()\n", + " for i, text in enumerate(texts):\n", + " box = boxes[i]\n", + " draw.rectangle(box,fill=None, outline=color) \n", + " # draw.text((int(box[0])+10, int(box[1])-10),fill=color, text=text, font = font)\n", + " image.save(os.path.join(outdir, image_name))\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "import glob\n", + "def read_txt(txt):\n", + " with open(txt, 'r', encoding='utf8') as f:\n", + " data = [line.strip() for line in f]\n", + " return data \n", + "\n", + "def get_data_from_txt_dir(txt_dir):\n", + " txt_paths = glob.glob(txt_dir + \"/*.txt\")\n", + " data = {}\n", + " for txt_path in txt_paths:\n", + " txt_name = os.path.basename(txt_path)\n", + " \n", + " \n", + " txt_data = read_txt(txt_path)\n", + " format_data = []\n", + " for line in txt_data:\n", + " items = line.split(\"\\t\")\n", + " assert len(items) == 6, \"error get len = {} - {} at {}\".format(len(items), items, txt_path)\n", + " box = [int(float(x)) for x in items[:4]]\n", + " text = items[4]\n", + " kie_label = items[5]\n", + " format_data.append(\n", + " {\n", + " 'box': box,\n", + " 'text': text, \n", + " 'label': kie_label\n", + " }\n", + " )\n", + " data[txt_name] = format_data\n", + "\n", + " return data" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "import glob \n", + "import os \n", + "import cv2\n", + "\n", + "img_dir = \"/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/invoice_viettinbank_poc\"\n", + "txt_dir = \"/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/invoice_viettinbank_poc\"\n", + "vis_dir = \"/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/notebooks/visualize/invoice_viettinbank_poc\"\n" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "56\n" + ] + } + ], + "source": [ + "\n", + "from pathlib import Path\n", + "img_paths = [p for p in glob.glob(f\"{img_dir}/*\") if \".txt\" not in p]\n", + "print(len(img_paths))\n", + "all_data = get_data_from_txt_dir(txt_dir)\n", + "\n", + "\n", + "for img_path in img_paths:\n", + " img = cv2.imread(img_path)\n", + " if img is None:\n", + " print(\"Image is none: \", img_path)\n", + " txt_file = Path(img_path).with_suffix(\".txt\").name\n", + " img_data = all_data[str(Path(img_path).with_suffix(\".txt\").name)]\n", + " # print(img_data)\n", + " boxes = [item['box'] for item in img_data]\n", + " texts = [item['text'] for item in img_data]\n", + " labels = [item['label'] for item in img_data]\n", + " \n", + " \n", + " visualize_kie(\n", + " img,\n", + " boxes, \n", + " labels, \n", + " skip_classes=['Others', 'other'], \n", + " image_name=os.path.basename(img_path), \n", + " outdir=vis_dir\n", + " )\n", + " # break" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [], + "source": [ + "def _check_iou(box1, box2, threshold=0.9):\n", + " \"\"\"_summary_\n", + "\n", + " Args:\n", + " box1 (_type_): word box\n", + " box2 (_type_): line box \n", + " threshold (float, optional): _description_. Defaults to 0.9.\n", + "\n", + " Returns:\n", + " _type_: _description_\n", + " \"\"\"\n", + " area1 = (box1[2] - box1[0]) * (box1[3] - box1[1])\n", + " area2 = (box2[2] - box2[0]) * (box2[3] - box2[1])\n", + " xmin_intersect = max(box1[0], box2[0])\n", + " ymin_intersect = max(box1[1], box2[1])\n", + " xmax_intersect = min(box1[2], box2[2])\n", + " ymax_intersect = min(box1[3], box2[3])\n", + "\n", + "\n", + " if xmax_intersect < xmin_intersect or ymax_intersect < ymin_intersect:\n", + " area_intersect = 0\n", + " else:\n", + " area_intersect = (xmax_intersect - xmin_intersect) * (\n", + " ymax_intersect - ymin_intersect\n", + " )\n", + " # union = area1 + area2 - area_intersect\n", + " iou = area_intersect / area1\n", + " return iou " + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1.0" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "_check_iou(box1=(465, 901, 664, 940), box2=(465, 901, 735, 940))" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "ename": "", + "evalue": "", + "output_type": "error", + "traceback": [ + "\u001b[1;31mRunning cells with 'py38_hoanglv' requires the ipykernel package.\n", + "\u001b[1;31mRun the following command to install 'ipykernel' into the Python environment. \n", + "\u001b[1;31mCommand: 'conda install -n py38_hoanglv ipykernel --update-deps --force-reinstall'" + ] + } + ], + "source": [ + "from sdsvkie.utils.io_file import read_json\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "pred_data = read_json(\"/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/exp_5/test_mcocr_not_label_ep21.json\")" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['minimart anan', '', 'vincommerce', 'nha sach gdtc cam pha', 'cua hang nam oanh', 'pho mo', 'saigon coop coop food hn the kpark', 'sctc co tho 104 tran phu cam pha', 'the coffee house', 'payoo', 'sieu thi bach hoa tong hop', 'sctc co thu 104 tran phu cam pha', 'thuc coffee', 'i vincommerce', 'f vincommerce', 'phuc anh minimart', 'vietcombank', 'guitar cafe', 'sieu thi minh loan', 'nha hang aozora sushi', 'thanh xuan', 'legend welcome to trung nguyen legend', 'coffee milano coffee vietnam', 'tiem da thanh xuan', 'gia re moi ngay', 'tiem da', 'oanh cua hang nam', 'phuc anh minimart noi ha lam', 'payoo uimmart', 'phuc coffee tea phuc long', 'anan minimart', 'c h a m', 'minimart', 'saigon coop coop food hn van khe', 'hniqlo vincom', 'ma co so opmart thue xa lo ha noi', 'ch thoi trang adidas', 'mart coopmart xa lo ha noi', 'vm hni cc nang huong', 'pharmacity', 'solanin l cong 1 phan', 'kai tea v kai tea', 'minimx', 'lamason10k', 'tien do thanh xuan', 'gia lam', 'sctc co thu 104 tran phu so cam pha', 'sieu thi my pham thong he shop', 'bidv', 'cafe cj building', 'go cool mart', 'saigon coop food hn', 'coopmart hau giang', 'feel coffee', 'coop saigon kpark food hn the', 'nha hang ut giang nguyen chanh', 'lahatafe just good coffee', 'satra group satrafoods nguyen van qua 2', 'tien no thanh xuan', '0 trung tam thuong mai aeon ha dong', 'vm thang long', 'cong ty co phan bot phap van cau gia', 'bieu thi bach hoa tong hop', 'nghcanh', 'big c long bien', 'books n coffee', 'coopmart', 'coop hoc quoc', 'vitimex quang ninh vincom cam pha', 'co opmart nguyen dinh chiel', 'cuitar cafe', 'vinmart', 'bieu thi thu cung pet yeu', 'pha nha sach gdtc cam pha', 'sieu thi minh loan phan', 'ly', 'flomesweethome ban hang', 'big c an phu', 'tiem tra', 'nha sachgdte cam pha', 'coopmart nguyen dinh chieu', 'biku thi bach hoa tong hoa', 'cp c o 0 p co opmart nguyen dinh chieu', 'nha nai 0110 am pha do 21d', 'ngoc com ga bao', 'jet mart', 'sushi nha hang aozora', 'bidv ', 'coffee milano coffee vietnam ', 'milano coffee milano coffee vietnam 4', 'coop smile', 'coor p mari', 'i thuc coffee', 'farnilymart', 'tran phu cam sctc co thu 104 pha', 'milano coffee milano coffee vietnam de', 'mart coopmart hau giang', 'satra group satrafoods 2b duong binh loi', 'ga dong quan', 'minimart anal', 'cty ld tnhh kfc viet nam', 'minimart phuc anh ha', 'velutino cong ty cp dau tu velutino viet nam', 'bun ho hu nn o xuan', 'biep thi bach hoa tono hoi', 'nha thuoc benh vien da khoa thanh pho vinh', 'phu noi', 'cua hang nam oanh tp ha', 'uniqlo vincom pham ngoc thach', 'vcb loi', 'saigon coop coop food hn the k park', 'hau giang', 'saigon coop food hn the kpark coop', 'welcome to trung nguyen legend', 'big c di an cty tnhh eb binh duong', 'milano coffee milang coffee vietnam ', 'bach hoa xanh', 'familymart', 'nha son gdty cam pha', 'dim sum corner trung hoa', 'minimart phuc anh ha noi lam', 'saigon coop pa coop food hn the kpark', 'cua hang tu chon anh giang', 'oma b a k e 4 e', 'hai ly', 'thghu tuan', 'covb food hn the', 'packer brinition 12341', 'viet tttm cho sui', 'tttm van hosieu thi seika mart', 'cho sui phu thi gia lam', 'circle k vietnam', 'cty cp sach tbth quang ninh', 'vinh', 'parts ga teaus 19', 'lahatafe', 'charles', 'coop food hn the', 'the coffee house thuy', 'saigon coop coop food hi the kpark', 'mooserroo vietham the moose roo smokehouse', 'tien da thanh xuan', 'saigo coop food', 'coopsmic', 'thu thanh xuan', 'phuong oc hai phong', 'kai tea kai tea', 'talala', 'ittm', 'vincom skylake', 'vision vincommerce', 'marumart']\n" + ] + } + ], + "source": [ + "store_names = [normalize(item['Store_name_value']) for k, item in pred_data.items()]\n", + "# store_names = list(set(store_names))\n", + "from collections import Counter\n", + "my_counter = Counter(store_names)\n", + "list_tuples = my_counter.most_common()\n", + "stores = [x[0] for x in list_tuples]\n", + "print(stores)" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[('minimart anan', 318),\n", + " ('', 296),\n", + " ('vincommerce', 177),\n", + " ('nha sach gdtc cam pha', 101),\n", + " ('cua hang nam oanh', 64),\n", + " ('pho mo', 41),\n", + " ('saigon coop coop food hn the kpark', 33),\n", + " ('sctc co tho 104 tran phu cam pha', 23),\n", + " ('the coffee house', 23),\n", + " ('payoo', 20),\n", + " ('sieu thi bach hoa tong hop', 18),\n", + " ('sctc co thu 104 tran phu cam pha', 16),\n", + " ('thuc coffee', 13),\n", + " ('i vincommerce', 10),\n", + " ('f vincommerce', 9),\n", + " ('phuc anh minimart', 9),\n", + " ('vietcombank', 9),\n", + " ('guitar cafe', 8),\n", + " ('sieu thi minh loan', 5),\n", + " ('nha hang aozora sushi', 5),\n", + " ('thanh xuan', 3),\n", + " ('legend welcome to trung nguyen legend', 3),\n", + " ('coffee milano coffee vietnam', 2),\n", + " ('tiem da thanh xuan', 2),\n", + " ('gia re moi ngay', 2),\n", + " ('tiem da', 2),\n", + " ('oanh cua hang nam', 2),\n", + " ('phuc anh minimart noi ha lam', 2),\n", + " ('payoo uimmart', 2),\n", + " ('phuc coffee tea phuc long', 2),\n", + " ('anan minimart', 2),\n", + " ('c h a m', 2),\n", + " ('minimart', 2),\n", + " ('saigon coop coop food hn van khe', 2),\n", + " ('hniqlo vincom', 1),\n", + " ('ma co so opmart thue xa lo ha noi', 1),\n", + " ('ch thoi trang adidas', 1),\n", + " ('mart coopmart xa lo ha noi', 1),\n", + " ('vm hni cc nang huong', 1),\n", + " ('pharmacity', 1),\n", + " ('solanin l cong 1 phan', 1),\n", + " ('kai tea v kai tea', 1),\n", + " ('minimx', 1),\n", + " ('lamason10k', 1),\n", + " ('tien do thanh xuan', 1),\n", + " ('gia lam', 1),\n", + " ('sctc co thu 104 tran phu so cam pha', 1),\n", + " ('sieu thi my pham thong he shop', 1),\n", + " ('bidv', 1),\n", + " ('cafe cj building', 1),\n", + " ('go cool mart', 1),\n", + " ('saigon coop food hn', 1),\n", + " ('coopmart hau giang', 1),\n", + " ('feel coffee', 1),\n", + " ('coop saigon kpark food hn the', 1),\n", + " ('nha hang ut giang nguyen chanh', 1),\n", + " ('lahatafe just good coffee', 1),\n", + " ('satra group satrafoods nguyen van qua 2', 1),\n", + " ('tien no thanh xuan', 1),\n", + " ('0 trung tam thuong mai aeon ha dong', 1),\n", + " ('vm thang long', 1),\n", + " ('cong ty co phan bot phap van cau gia', 1),\n", + " ('bieu thi bach hoa tong hop', 1),\n", + " ('nghcanh', 1),\n", + " ('big c long bien', 1),\n", + " ('books n coffee', 1),\n", + " ('coopmart', 1),\n", + " ('coop hoc quoc', 1),\n", + " ('vitimex quang ninh vincom cam pha', 1),\n", + " ('co opmart nguyen dinh chiel', 1),\n", + " ('cuitar cafe', 1),\n", + " ('vinmart', 1),\n", + " ('bieu thi thu cung pet yeu', 1),\n", + " ('pha nha sach gdtc cam pha', 1),\n", + " ('sieu thi minh loan phan', 1),\n", + " ('ly', 1),\n", + " ('flomesweethome ban hang', 1),\n", + " ('big c an phu', 1),\n", + " ('tiem tra', 1),\n", + " ('nha sachgdte cam pha', 1),\n", + " ('coopmart nguyen dinh chieu', 1),\n", + " ('biku thi bach hoa tong hoa', 1),\n", + " ('cp c o 0 p co opmart nguyen dinh chieu', 1),\n", + " ('nha nai 0110 am pha do 21d', 1),\n", + " ('ngoc com ga bao', 1),\n", + " ('jet mart', 1),\n", + " ('sushi nha hang aozora', 1),\n", + " ('bidv ', 1),\n", + " ('coffee milano coffee vietnam ', 1),\n", + " ('milano coffee milano coffee vietnam 4', 1),\n", + " ('coop smile', 1),\n", + " ('coor p mari', 1),\n", + " ('i thuc coffee', 1),\n", + " ('farnilymart', 1),\n", + " ('tran phu cam sctc co thu 104 pha', 1),\n", + " ('milano coffee milano coffee vietnam de', 1),\n", + " ('mart coopmart hau giang', 1),\n", + " ('satra group satrafoods 2b duong binh loi', 1),\n", + " ('ga dong quan', 1),\n", + " ('minimart anal', 1),\n", + " ('cty ld tnhh kfc viet nam', 1),\n", + " ('minimart phuc anh ha', 1),\n", + " ('velutino cong ty cp dau tu velutino viet nam', 1),\n", + " ('bun ho hu nn o xuan', 1),\n", + " ('biep thi bach hoa tono hoi', 1),\n", + " ('nha thuoc benh vien da khoa thanh pho vinh', 1),\n", + " ('phu noi', 1),\n", + " ('cua hang nam oanh tp ha', 1),\n", + " ('uniqlo vincom pham ngoc thach', 1),\n", + " ('vcb loi', 1),\n", + " ('saigon coop coop food hn the k park', 1),\n", + " ('hau giang', 1),\n", + " ('saigon coop food hn the kpark coop', 1),\n", + " ('welcome to trung nguyen legend', 1),\n", + " ('big c di an cty tnhh eb binh duong', 1),\n", + " ('milano coffee milang coffee vietnam ', 1),\n", + " ('bach hoa xanh', 1),\n", + " ('familymart', 1),\n", + " ('nha son gdty cam pha', 1),\n", + " ('dim sum corner trung hoa', 1),\n", + " ('minimart phuc anh ha noi lam', 1),\n", + " ('saigon coop pa coop food hn the kpark', 1),\n", + " ('cua hang tu chon anh giang', 1),\n", + " ('oma b a k e 4 e', 1),\n", + " ('hai ly', 1),\n", + " ('thghu tuan', 1),\n", + " ('covb food hn the', 1),\n", + " ('packer brinition 12341', 1),\n", + " ('viet tttm cho sui', 1),\n", + " ('tttm van hosieu thi seika mart', 1),\n", + " ('cho sui phu thi gia lam', 1),\n", + " ('circle k vietnam', 1),\n", + " ('cty cp sach tbth quang ninh', 1),\n", + " ('vinh', 1),\n", + " ('parts ga teaus 19', 1),\n", + " ('lahatafe', 1),\n", + " ('charles', 1),\n", + " ('coop food hn the', 1),\n", + " ('the coffee house thuy', 1),\n", + " ('saigon coop coop food hi the kpark', 1),\n", + " ('mooserroo vietham the moose roo smokehouse', 1),\n", + " ('tien da thanh xuan', 1),\n", + " ('saigo coop food', 1),\n", + " ('coopsmic', 1),\n", + " ('thu thanh xuan', 1),\n", + " ('phuong oc hai phong', 1),\n", + " ('kai tea kai tea', 1),\n", + " ('talala', 1),\n", + " ('ittm', 1),\n", + " ('vincom skylake', 1),\n", + " ('vision vincommerce', 1),\n", + " ('marumart', 1)]" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "my_counter.most_common()" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "152" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(stores)" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": {}, + "outputs": [], + "source": [ + "img_dir = \"/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/exp_5/test_mcocr_not_label_ep21\"\n", + "\n", + "store_names = [\n", + " 'minimart anan',\n", + " 'vincommerce', \n", + " 'nha sach gdtc cam pha',\n", + " 'cua hang nam oanh', \n", + " 'pho mo', \n", + " 'saigon coop coop food hn the kpark', \n", + " 'sctc co tho 104 tran phu cam pha', \n", + " 'the coffee house', \n", + " 'payoo', \n", + " 'sieu thi bach hoa tong hop', \n", + " 'sctc co thu 104 tran phu cam pha', \n", + " 'thuc coffee', \n", + " 'vincommerce', \n", + " 'phuc anh minimart', \n", + " 'vietcombank', \n", + " 'guitar cafe', \n", + " 'sieu thi minh loan'\n", + " ]" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "other/have_title/HNIQLO_Vincom\n", + "vincommerce\n", + "vincommerce\n", + "minimart_anan\n", + "other/non_title\n", + "minimart_anan\n", + "the_coffee_house\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "minimart_anan\n", + "minimart_anan\n", + "minimart_anan\n", + "vincommerce\n", + "vincommerce\n", + "vincommerce\n", + "other/non_title\n", + "vincommerce\n", + "minimart_anan\n", + "cua_hang_nam_oanh\n", + "cua_hang_nam_oanh\n", + "nha_sach_gdtc_cam_pha\n", + "other/non_title\n", + "minimart_anan\n", + "other/non_title\n", + "nha_sach_gdtc_cam_pha\n", + "other/non_title\n", + "minimart_anan\n", + "vincommerce\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "other/non_title\n", + "minimart_anan\n", + "vincommerce\n", + "minimart_anan\n", + "other/have_title/Ma_Co_SO_opMart_thue:_XÃ_LO_HA_NOI\n", + "the_coffee_house\n", + "vincommerce\n", + "minimart_anan\n", + "minimart_anan\n", + "cua_hang_nam_oanh\n", + "vincommerce\n", + "cua_hang_nam_oanh\n", + "other/have_title/CH_THỜI_TRANG_ADIDAS\n", + "the_coffee_house\n", + "other/non_title\n", + "other/non_title\n", + "minimart_anan\n", + "payoo\n", + "vincommerce\n", + "minimart_anan\n", + "other/have_title/mart_Co.opMart_XÃ_LO_HA_NOI\n", + "vincommerce\n", + "other/non_title\n", + "the_coffee_house\n", + "sieu_thi_bach_hoa_tong_hop\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "sieu_thi_bach_hoa_tong_hop\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "the_coffee_house\n", + "other/have_title/COFFEE_Milano_Coffee_Vietnam\n", + "minimart_anan\n", + "sieu_thi_bach_hoa_tong_hop\n", + "minimart_anan\n", + "nha_sach_gdtc_cam_pha\n", + "nha_sach_gdtc_cam_pha\n", + "other/non_title\n", + "minimart_anan\n", + "cua_hang_nam_oanh\n", + "minimart_anan\n", + "other/non_title\n", + "minimart_anan\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "vincommerce\n", + "nha_sach_gdtc_cam_pha\n", + "cua_hang_nam_oanh\n", + "other/non_title\n", + "other/non_title\n", + "vincommerce\n", + "other/non_title\n", + "other/have_title/VM+_HNI_CC_Nàng_Hương\n", + "pho_mo\n", + "other/non_title\n", + "other/non_title\n", + "other/non_title\n", + "other/non_title\n", + "vincommerce\n", + "minimart_anan\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "other/non_title\n", + "minimart_anan\n", + "cua_hang_nam_oanh\n", + "other/have_title/Tiêm_đã_Thanh_Xuân\n", + "other/have_title/GIÁ_RẺ_MOI_NGÀY\n", + "minimart_anan\n", + "minimart_anan\n", + "vincommerce\n", + "minimart_anan\n", + "other/have_title/Nhà_Hàng_Aozora_Sushi\n", + "vincommerce\n", + "other/non_title\n", + "guitar_cafe\n", + "other/non_title\n", + "other/have_title/Pharmacity\n", + "nha_sach_gdtc_cam_pha\n", + "vincommerce\n", + "other/non_title\n", + "vincommerce\n", + "minimart_anan\n", + "vincommerce\n", + "other/have_title/Solanin_l_Công_1)_Phân\n", + "nha_sach_gdtc_cam_pha\n", + "pho_mo\n", + "minimart_anan\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "vincommerce\n", + "vincommerce\n", + "minimart_anan\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "other/non_title\n", + "other/non_title\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "minimart_anan\n", + "minimart_anan\n", + "other/non_title\n", + "nha_sach_gdtc_cam_pha\n", + "other/non_title\n", + "minimart_anan\n", + "phuc_anh_minimart\n", + "other/non_title\n", + "cua_hang_nam_oanh\n", + "other/non_title\n", + "minimart_anan\n", + "minimart_anan\n", + "the_coffee_house\n", + "other/have_title/Tiêm_đã\n", + "pho_mo\n", + "sieu_thi_bach_hoa_tong_hop\n", + "minimart_anan\n", + "payoo\n", + "minimart_anan\n", + "other/non_title\n", + "other/non_title\n", + "minimart_anan\n", + "minimart_anan\n", + "pho_mo\n", + "vincommerce\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "other/have_title/Nhà_Hàng_Aozora_Sushi\n", + "nha_sach_gdtc_cam_pha\n", + "other/have_title/KAI_TEA_V_KAI_TEA\n", + "vincommerce\n", + "minimart_anan\n", + "other/non_title\n", + "other/non_title\n", + "other/have_title/MINIMX\n", + "pho_mo\n", + "other/have_title/Thanh_Xuân\n", + "minimart_anan\n", + "vincommerce\n", + "vincommerce\n", + "vincommerce\n", + "minimart_anan\n", + "cua_hang_nam_oanh\n", + "other/have_title/LAMASON10K\n", + "other/have_title/Tiền_đo_Thanh_Xuân\n", + "other/non_title\n", + "cua_hang_nam_oanh\n", + "vincommerce\n", + "cua_hang_nam_oanh\n", + "minimart_anan\n", + "other/non_title\n", + "other/non_title\n", + "other/non_title\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "other/non_title\n", + "sieu_thi_bach_hoa_tong_hop\n", + "pho_mo\n", + "cua_hang_nam_oanh\n", + "vincommerce\n", + "other/have_title/Gia_Lam\n", + "vincommerce\n", + "minimart_anan\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "other/non_title\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "vincommerce\n", + "other/non_title\n", + "nha_sach_gdtc_cam_pha\n", + "other/non_title\n", + "vincommerce\n", + "other/non_title\n", + "other/non_title\n", + "minimart_anan\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "other/non_title\n", + "nha_sach_gdtc_cam_pha\n", + "sieu_thi_bach_hoa_tong_hop\n", + "the_coffee_house\n", + "nha_sach_gdtc_cam_pha\n", + "other/non_title\n", + "minimart_anan\n", + "minimart_anan\n", + "vincommerce\n", + "other/have_title/BIDV&\n", + "minimart_anan\n", + "the_coffee_house\n", + "other/non_title\n", + "minimart_anan\n", + "the_coffee_house\n", + "vietcombank\n", + "other/non_title\n", + "cua_hang_nam_oanh\n", + "vincommerce\n", + "vincommerce\n", + "minimart_anan\n", + "other/have_title/Cafe_CJ_Building\n", + "other/non_title\n", + "other/non_title\n", + "minimart_anan\n", + "payoo\n", + "minimart_anan\n", + "other/non_title\n", + "other/non_title\n", + "minimart_anan\n", + "cua_hang_nam_oanh\n", + "minimart_anan\n", + "minimart_anan\n", + "minimart_anan\n", + "other/non_title\n", + "pho_mo\n", + "vincommerce\n", + "cua_hang_nam_oanh\n", + "other/have_title/GO_CO.OL_mart\n", + "the_coffee_house\n", + "vincommerce\n", + "pho_mo\n", + "vincommerce\n", + "minimart_anan\n", + "pho_mo\n", + "other/non_title\n", + "the_coffee_house\n", + "other/non_title\n", + "other/non_title\n", + "minimart_anan\n", + "the_coffee_house\n", + "minimart_anan\n", + "phuc_anh_minimart\n", + "other/non_title\n", + "other/non_title\n", + "minimart_anan\n", + "other/non_title\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "minimart_anan\n", + "other/non_title\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "other/non_title\n", + "other/have_title/Co.opMart_HAU_GIANG\n", + "other/non_title\n", + "phuc_anh_minimart\n", + "the_coffee_house\n", + "minimart_anan\n", + "payoo\n", + "sieu_thi_bach_hoa_tong_hop\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "nha_sach_gdtc_cam_pha\n", + "pho_mo\n", + "vincommerce\n", + "thuc_coffee\n", + "pho_mo\n", + "other/non_title\n", + "other/non_title\n", + "nha_sach_gdtc_cam_pha\n", + "phuc_anh_minimart\n", + "vincommerce\n", + "other/have_title/Payoo_UIMMART\n", + "vincommerce\n", + "other/non_title\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "minimart_anan\n", + "sieu_thi_bach_hoa_tong_hop\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "minimart_anan\n", + "minimart_anan\n", + "other/non_title\n", + "other/have_title/Nhà_Hàng_Út_Giang_Nguyễn_Chánh\n", + "vincommerce\n", + "other/non_title\n", + "nha_sach_gdtc_cam_pha\n", + "payoo\n", + "minimart_anan\n", + "vincommerce\n", + "other/non_title\n", + "vincommerce\n", + "vincommerce\n", + "vincommerce\n", + "vincommerce\n", + "minimart_anan\n", + "pho_mo\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "cua_hang_nam_oanh\n", + "minimart_anan\n", + "cua_hang_nam_oanh\n", + "other/non_title\n", + "vincommerce\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "minimart_anan\n", + "other/have_title/PHUC_Coffee_Tea_PHUC_LONG\n", + "the_coffee_house\n", + "vincommerce\n", + "minimart_anan\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "vincommerce\n", + "other/non_title\n", + "phuc_anh_minimart\n", + "vincommerce\n", + "minimart_anan\n", + "minimart_anan\n", + "minimart_anan\n", + "minimart_anan\n", + "other/non_title\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "pho_mo\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "minimart_anan\n", + "minimart_anan\n", + "vincommerce\n", + "other/non_title\n", + "other/have_title/Tiêm_đã\n", + "minimart_anan\n", + "other/have_title/LahaTafe_JUST_GOOD_COFFEE\n", + "nha_sach_gdtc_cam_pha\n", + "vietcombank\n", + "minimart_anan\n", + "vincommerce\n", + "nha_sach_gdtc_cam_pha\n", + "other/non_title\n", + "minimart_anan\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "other/non_title\n", + "other/have_title/Legend_Welcome_to_Trung_Nguyen_Legend\n", + "other/non_title\n", + "other/have_title/C_H_A_M\n", + "other/have_title/Satra_Group_Satrafoods_Nguyễn_Văn_Quá_2\n", + "cua_hang_nam_oanh\n", + "vincommerce\n", + "other/non_title\n", + "other/non_title\n", + "other/non_title\n", + "vietcombank\n", + "payoo\n", + "pho_mo\n", + "vietcombank\n", + "nha_sach_gdtc_cam_pha\n", + "other/have_title/Tiền_No_Thanh_Xuân\n", + "other/have_title/0_TRUNG_TÂM_THƯƠNG_MẠI_AEON_-_HÀ_ĐÔNG\n", + "other/non_title\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "cua_hang_nam_oanh\n", + "vincommerce\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "other/have_title/PHUC_Coffee_Tea_PHUC_LONG\n", + "minimart_anan\n", + "minimart_anan\n", + "vincommerce\n", + "other/have_title/VM_Thăng_Long\n", + "other/non_title\n", + "minimart_anan\n", + "minimart_anan\n", + "minimart_anan\n", + "nha_sach_gdtc_cam_pha\n", + "vincommerce\n", + "cua_hang_nam_oanh\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "other/have_title/CÔNG_TY_cổ_PHẦN_BOT_PHÁP_VÂN_-_CẦU_GIA\n", + "sieu_thi_bach_hoa_tong_hop\n", + "other/non_title\n", + "vincommerce\n", + "other/non_title\n", + "the_coffee_house\n", + "nha_sach_gdtc_cam_pha\n", + "other/non_title\n", + "minimart_anan\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "other/non_title\n", + "vincommerce\n", + "other/non_title\n", + "minimart_anan\n", + "other/non_title\n", + "vincommerce\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "cua_hang_nam_oanh\n", + "cua_hang_nam_oanh\n", + "minimart_anan\n", + "minimart_anan\n", + "pho_mo\n", + "vincommerce\n", + "other/non_title\n", + "nha_sach_gdtc_cam_pha\n", + "vincommerce\n", + "vincommerce\n", + "the_coffee_house\n", + "vincommerce\n", + "minimart_anan\n", + "minimart_anan\n", + "minimart_anan\n", + "minimart_anan\n", + "other/non_title\n", + "vincommerce\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "pho_mo\n", + "sieu_thi_bach_hoa_tong_hop\n", + "minimart_anan\n", + "minimart_anan\n", + "other/non_title\n", + "other/non_title\n", + "minimart_anan\n", + "other/non_title\n", + "minimart_anan\n", + "other/non_title\n", + "vincommerce\n", + "other/non_title\n", + "other/non_title\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "minimart_anan\n", + "cua_hang_nam_oanh\n", + "minimart_anan\n", + "other/non_title\n", + "other/non_title\n", + "minimart_anan\n", + "minimart_anan\n", + "nha_sach_gdtc_cam_pha\n", + "other/have_title/Nhà_Hàng_Aozora_Sushi\n", + "minimart_anan\n", + "the_coffee_house\n", + "vincommerce\n", + "nha_sach_gdtc_cam_pha\n", + "other/non_title\n", + "minimart_anan\n", + "other/non_title\n", + "cua_hang_nam_oanh\n", + "other/have_title/Ng.H.Cảnh\n", + "other/non_title\n", + "minimart_anan\n", + "other/non_title\n", + "vincommerce\n", + "vincommerce\n", + "vincommerce\n", + "cua_hang_nam_oanh\n", + "minimart_anan\n", + "other/have_title/BIG_C_LONG_BIEN\n", + "cua_hang_nam_oanh\n", + "minimart_anan\n", + "other/non_title\n", + "minimart_anan\n", + "other/have_title/BOOKS_n_COFFEE\n", + "vincommerce\n", + "other/non_title\n", + "other/non_title\n", + "vincommerce\n", + "cua_hang_nam_oanh\n", + "pho_mo\n", + "minimart_anan\n", + "other/non_title\n", + "other/non_title\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "pho_mo\n", + "other/have_title/Co.opMart\n", + "vincommerce\n", + "vincommerce\n", + "other/have_title/co.op_HOC_QUOC\n", + "nha_sach_gdtc_cam_pha\n", + "the_coffee_house\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "minimart_anan\n", + "vincommerce\n", + "minimart_anan\n", + "other/have_title/Vitimex_Quảng_Ninh_VinCom_Cẩm_Phà\n", + "other/have_title/Co_.opMart_NGUYỄN_DINH_CHIEL\n", + "other/non_title\n", + "nha_sach_gdtc_cam_pha\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "guitar_cafe\n", + "minimart_anan\n", + "minimart_anan\n", + "other/non_title\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "minimart_anan\n", + "other/non_title\n", + "other/non_title\n", + "other/have_title/VinMart\n", + "guitar_cafe\n", + "vincommerce\n", + "other/non_title\n", + "other/non_title\n", + "vincommerce\n", + "the_coffee_house\n", + "other/non_title\n", + "vincommerce\n", + "vincommerce\n", + "other/have_title/Biêu_thị_thủ_cung_PET_YÊU\n", + "other/non_title\n", + "minimart_anan\n", + "other/non_title\n", + "nha_sach_gdtc_cam_pha\n", + "other/non_title\n", + "minimart_anan\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "nha_sach_gdtc_cam_pha\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "minimart_anan\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "minimart_anan\n", + "other/non_title\n", + "vincommerce\n", + "other/non_title\n", + "cua_hang_nam_oanh\n", + "minimart_anan\n", + "cua_hang_nam_oanh\n", + "the_coffee_house\n", + "minimart_anan\n", + "payoo\n", + "minimart_anan\n", + "pho_mo\n", + "minimart_anan\n", + "sieu_thi_bach_hoa_tong_hop\n", + "vincommerce\n", + "vincommerce\n", + "cua_hang_nam_oanh\n", + "nha_sach_gdtc_cam_pha\n", + "other/non_title\n", + "the_coffee_house\n", + "minimart_anan\n", + "nha_sach_gdtc_cam_pha\n", + "other/non_title\n", + "minimart_anan\n", + "other/non_title\n", + "vincommerce\n", + "cua_hang_nam_oanh\n", + "other/non_title\n", + "other/have_title/Ly\n", + "vincommerce\n", + "other/have_title/FlomeSweetHome_-_Bán_hàng\n", + "other/have_title/BIG_C_AN_PHU\n", + "minimart_anan\n", + "other/non_title\n", + "nha_sach_gdtc_cam_pha\n", + "other/have_title/Tiêm_trả\n", + "nha_sach_gdtc_cam_pha\n", + "cua_hang_nam_oanh\n", + "minimart_anan\n", + "other/non_title\n", + "minimart_anan\n", + "sieu_thi_bach_hoa_tong_hop\n", + "vincommerce\n", + "other/non_title\n", + "nha_sach_gdtc_cam_pha\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "other/non_title\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "other/have_title/Tiếm_đã_Thanh_Xuân\n", + "other/have_title/Legend_Welcome_to_Trung_Nguyen_Legend\n", + "nha_sach_gdtc_cam_pha\n", + "other/non_title\n", + "other/non_title\n", + "vincommerce\n", + "other/non_title\n", + "minimart_anan\n", + "minimart_anan\n", + "minimart_anan\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "other/have_title/Legend_Welcome_to_Trung_Nguyen_Legend\n", + "nha_sach_gdtc_cam_pha\n", + "pho_mo\n", + "minimart_anan\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "vincommerce\n", + "cua_hang_nam_oanh\n", + "nha_sach_gdtc_cam_pha\n", + "other/have_title/GIÁ_RE_MỔI_NGÀY\n", + "minimart_anan\n", + "vincommerce\n", + "other/non_title\n", + "minimart_anan\n", + "minimart_anan\n", + "other/non_title\n", + "minimart_anan\n", + "minimart_anan\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "vincommerce\n", + "other/non_title\n", + "other/non_title\n", + "other/non_title\n", + "nha_sach_gdtc_cam_pha\n", + "payoo\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "minimart_anan\n", + "vincommerce\n", + "minimart_anan\n", + "other/non_title\n", + "vincommerce\n", + "minimart_anan\n", + "sieu_thi_bach_hoa_tong_hop\n", + "vincommerce\n", + "minimart_anan\n", + "minimart_anan\n", + "pho_mo\n", + "minimart_anan\n", + "nha_sach_gdtc_cam_pha\n", + "vincommerce\n", + "vietcombank\n", + "nha_sach_gdtc_cam_pha\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "minimart_anan\n", + "minimart_anan\n", + "other/have_title/Co.opMart_NGUYỄN_DINH_CHIEU\n", + "minimart_anan\n", + "vincommerce\n", + "minimart_anan\n", + "the_coffee_house\n", + "minimart_anan\n", + "sieu_thi_bach_hoa_tong_hop\n", + "other/non_title\n", + "minimart_anan\n", + "nha_sach_gdtc_cam_pha\n", + "nha_sach_gdtc_cam_pha\n", + "pho_mo\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "other/have_title/CP_C_O_0_P_Co_opMart_NGUYỄN_DINH_CHIEU\n", + "other/have_title/NHÃ_NAI_-_01).10_._AM_PHA_DO_21D\n", + "other/non_title\n", + "other/have_title/NGỌC_CƠM_GÀ_BẢO\n", + "vincommerce\n", + "minimart_anan\n", + "other/non_title\n", + "other/non_title\n", + "other/non_title\n", + "other/have_title/JET_MART\n", + "other/non_title\n", + "payoo\n", + "pho_mo\n", + "other/non_title\n", + "minimart_anan\n", + "vincommerce\n", + "minimart_anan\n", + "vincommerce\n", + "vincommerce\n", + "other/non_title\n", + "the_coffee_house\n", + "nha_sach_gdtc_cam_pha\n", + "pho_mo\n", + "nha_sach_gdtc_cam_pha\n", + "other/non_title\n", + "other/have_title/Sushi_Nhà_Hàng_Aozora\n", + "vincommerce\n", + "cua_hang_nam_oanh\n", + "other/non_title\n", + "vincommerce\n", + "minimart_anan\n", + "sieu_thi_bach_hoa_tong_hop\n", + "other/non_title\n", + "minimart_anan\n", + "other/non_title\n", + "vincommerce\n", + "other/non_title\n", + "other/non_title\n", + "minimart_anan\n", + "other/have_title/BIDV_,\n", + "cua_hang_nam_oanh\n", + "minimart_anan\n", + "minimart_anan\n", + "minimart_anan\n", + "other/have_title/COFFEE_Milano_Coffee_Vietnam_####\n", + "minimart_anan\n", + "vincommerce\n", + "vincommerce\n", + "minimart_anan\n", + "other/non_title\n", + "payoo\n", + "vincommerce\n", + "nha_sach_gdtc_cam_pha\n", + "other/non_title\n", + "minimart_anan\n", + "vincommerce\n", + "minimart_anan\n", + "cua_hang_nam_oanh\n", + "other/non_title\n", + "phuc_anh_minimart\n", + "other/non_title\n", + "other/have_title/MILANO_COFFEE_Milano_Coffee_Vietnam_4\n", + "other/have_title/co.op_smile\n", + "other/have_title/CO.Or_P_mari\n", + "minimart_anan\n", + "other/non_title\n", + "minimart_anan\n", + "other/non_title\n", + "vincommerce\n", + "minimart_anan\n", + "other/non_title\n", + "minimart_anan\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "nha_sach_gdtc_cam_pha\n", + "other/non_title\n", + "other/non_title\n", + "minimart_anan\n", + "cua_hang_nam_oanh\n", + "vincommerce\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "vincommerce\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "minimart_anan\n", + "other/non_title\n", + "vincommerce\n", + "minimart_anan\n", + "payoo\n", + "minimart_anan\n", + "nha_sach_gdtc_cam_pha\n", + "other/non_title\n", + "the_coffee_house\n", + "vincommerce\n", + "sieu_thi_bach_hoa_tong_hop\n", + "other/have_title/FarnilyMart\n", + "other/have_title/TRẦN_PHÚ_-_CẨM_SCTC_CÔ_THỦ_104_PHẢ\n", + "phuc_anh_minimart\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "other/non_title\n", + "other/have_title/MILANO_COFFEE_Milano_Coffee_Vietnam_đẻ\n", + "other/have_title/mart_Co.opMart_HAU_GIANG\n", + "minimart_anan\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "minimart_anan\n", + "nha_sach_gdtc_cam_pha\n", + "vincommerce\n", + "nha_sach_gdtc_cam_pha\n", + "vincommerce\n", + "other/non_title\n", + "minimart_anan\n", + "vincommerce\n", + "vincommerce\n", + "vincommerce\n", + "vincommerce\n", + "vincommerce\n", + "nha_sach_gdtc_cam_pha\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "other/non_title\n", + "minimart_anan\n", + "other/non_title\n", + "vincommerce\n", + "vincommerce\n", + "vincommerce\n", + "other/have_title/Satra_Group_Satrafoods_2B_Đường_Bình_Lợi\n", + "other/non_title\n", + "other/have_title/Ga_Dong_Quan\n", + "cua_hang_nam_oanh\n", + "vincommerce\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "vincommerce\n", + "vincommerce\n", + "other/non_title\n", + "other/non_title\n", + "minimart_anan\n", + "vincommerce\n", + "sieu_thi_bach_hoa_tong_hop\n", + "other/non_title\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "minimart_anan\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "minimart_anan\n", + "other/non_title\n", + "other/non_title\n", + "minimart_anan\n", + "other/non_title\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "minimart_anan\n", + "vincommerce\n", + "other/non_title\n", + "minimart_anan\n", + "sieu_thi_bach_hoa_tong_hop\n", + "other/have_title/Cty_LD_TNHH_KFC_Viet_Nam\n", + "vincommerce\n", + "cua_hang_nam_oanh\n", + "minimart_anan\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "pho_mo\n", + "other/non_title\n", + "minimart_anan\n", + "vincommerce\n", + "pho_mo\n", + "cua_hang_nam_oanh\n", + "minimart_anan\n", + "minimart_anan\n", + "other/have_title/VELUTINO_CÔNG_TY_CP_ĐẦU_TƯ_VELUTINO_VIỆT_NAM\n", + "minimart_anan\n", + "vincommerce\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "nha_sach_gdtc_cam_pha\n", + "vincommerce\n", + "minimart_anan\n", + "the_coffee_house\n", + "vincommerce\n", + "other/non_title\n", + "other/non_title\n", + "other/have_title/Bún_HÒ_Hu_NN_O_Xuân\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "vincommerce\n", + "other/non_title\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "nha_sach_gdtc_cam_pha\n", + "the_coffee_house\n", + "other/non_title\n", + "vietcombank\n", + "pho_mo\n", + "sieu_thi_bach_hoa_tong_hop\n", + "minimart_anan\n", + "nha_sach_gdtc_cam_pha\n", + "vincommerce\n", + "cua_hang_nam_oanh\n", + "other/non_title\n", + "other/have_title/NHÀ_THUỐC_BỆNH_VIỆN_ĐA_KHOA_THÀNH_PHỐ_VINH\n", + "minimart_anan\n", + "phuc_anh_minimart\n", + "minimart_anan\n", + "minimart_anan\n", + "cua_hang_nam_oanh\n", + "other/non_title\n", + "guitar_cafe\n", + "minimart_anan\n", + "minimart_anan\n", + "minimart_anan\n", + "pho_mo\n", + "vietcombank\n", + "vincommerce\n", + "vincommerce\n", + "other/non_title\n", + "other/have_title/Thanh_Xuân\n", + "pho_mo\n", + "sieu_thi_bach_hoa_tong_hop\n", + "minimart_anan\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "minimart_anan\n", + "cua_hang_nam_oanh\n", + "other/non_title\n", + "minimart_anan\n", + "minimart_anan\n", + "other/non_title\n", + "guitar_cafe\n", + "pho_mo\n", + "other/non_title\n", + "other/non_title\n", + "minimart_anan\n", + "minimart_anan\n", + "other/non_title\n", + "cua_hang_nam_oanh\n", + "minimart_anan\n", + "cua_hang_nam_oanh\n", + "nha_sach_gdtc_cam_pha\n", + "other/have_title/UNIQLO_Vincom_Phạm_Ngọc_Thạch\n", + "minimart_anan\n", + "other/non_title\n", + "minimart_anan\n", + "minimart_anan\n", + "minimart_anan\n", + "minimart_anan\n", + "other/have_title/VCB_-_Lợi\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "other/non_title\n", + "vincommerce\n", + "pho_mo\n", + "pho_mo\n", + "sieu_thi_bach_hoa_tong_hop\n", + "other/have_title/HAU_GIANG\n", + "other/non_title\n", + "other/non_title\n", + "other/non_title\n", + "minimart_anan\n", + "vincommerce\n", + "minimart_anan\n", + "minimart_anan\n", + "cua_hang_nam_oanh\n", + "other/non_title\n", + "minimart_anan\n", + "other/non_title\n", + "minimart_anan\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "cua_hang_nam_oanh\n", + "vincommerce\n", + "vincommerce\n", + "cua_hang_nam_oanh\n", + "other/non_title\n", + "other/non_title\n", + "other/have_title/Welcome_to_Trung_Nguyen_Legend\n", + "other/non_title\n", + "vincommerce\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "other/non_title\n", + "other/non_title\n", + "other/non_title\n", + "sieu_thi_bach_hoa_tong_hop\n", + "other/non_title\n", + "other/non_title\n", + "vincommerce\n", + "other/have_title/BIG_C_DI_AN_CTY_TNHH_EB_BINH_DUONG\n", + "minimart_anan\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "other/non_title\n", + "other/non_title\n", + "other/non_title\n", + "minimart_anan\n", + "other/non_title\n", + "nha_sach_gdtc_cam_pha\n", + "other/non_title\n", + "minimart_anan\n", + "minimart_anan\n", + "other/have_title/MILANO_COFFEE_Milang_Coffee_Vietnam_####\n", + "other/non_title\n", + "cua_hang_nam_oanh\n", + "nha_sach_gdtc_cam_pha\n", + "other/have_title/BÁCH_HÓA_XANH\n", + "vincommerce\n", + "vincommerce\n", + "other/non_title\n", + "guitar_cafe\n", + "other/non_title\n", + "minimart_anan\n", + "minimart_anan\n", + "other/non_title\n", + "nha_sach_gdtc_cam_pha\n", + "payoo\n", + "other/have_title/FamilyMart\n", + "nha_sach_gdtc_cam_pha\n", + "other/have_title/Payoo_UIMMART\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "other/non_title\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "the_coffee_house\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "minimart_anan\n", + "minimart_anan\n", + "other/non_title\n", + "vincommerce\n", + "minimart_anan\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "other/non_title\n", + "sieu_thi_bach_hoa_tong_hop\n", + "payoo\n", + "nha_sach_gdtc_cam_pha\n", + "vincommerce\n", + "other/non_title\n", + "other/non_title\n", + "other/have_title/DIM_SUM_CORNER_TRUNG_HÒA\n", + "vincommerce\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "other/non_title\n", + "other/non_title\n", + "minimart_anan\n", + "pho_mo\n", + "minimart_anan\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "cua_hang_nam_oanh\n", + "minimart_anan\n", + "other/non_title\n", + "vincommerce\n", + "cua_hang_nam_oanh\n", + "pho_mo\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "other/non_title\n", + "minimart_anan\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "minimart_anan\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "vincommerce\n", + "other/non_title\n", + "the_coffee_house\n", + "minimart_anan\n", + "minimart_anan\n", + "vincommerce\n", + "minimart_anan\n", + "vincommerce\n", + "cua_hang_nam_oanh\n", + "pho_mo\n", + "vietcombank\n", + "minimart_anan\n", + "other/have_title/oma_B_a_k_e_4_é\n", + "vincommerce\n", + "minimart_anan\n", + "minimart_anan\n", + "other/have_title/Hải_Ly\n", + "minimart_anan\n", + "minimart_anan\n", + "vincommerce\n", + "minimart_anan\n", + "the_coffee_house\n", + "minimart_anan\n", + "other/non_title\n", + "minimart_anan\n", + "vincommerce\n", + "vincommerce\n", + "nha_sach_gdtc_cam_pha\n", + "vincommerce\n", + "vincommerce\n", + "minimart_anan\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "nha_sach_gdtc_cam_pha\n", + "vincommerce\n", + "vincommerce\n", + "vincommerce\n", + "cua_hang_nam_oanh\n", + "other/have_title/THGHU_TUẤN\n", + "other/non_title\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "minimart_anan\n", + "other/non_title\n", + "other/have_title/Covb_Food_HN_The\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "other/non_title\n", + "nha_sach_gdtc_cam_pha\n", + "vincommerce\n", + "vincommerce\n", + "payoo\n", + "minimart_anan\n", + "minimart_anan\n", + "minimart_anan\n", + "other/non_title\n", + "other/non_title\n", + "minimart_anan\n", + "vincommerce\n", + "other/non_title\n", + "other/have_title/PACKER_BRINITION_12341\n", + "minimart_anan\n", + "vincommerce\n", + "minimart_anan\n", + "phuc_anh_minimart\n", + "minimart_anan\n", + "minimart_anan\n", + "minimart_anan\n", + "minimart_anan\n", + "other/have_title/Nhà_Hàng_Aozora_Sushi\n", + "vincommerce\n", + "minimart_anan\n", + "minimart_anan\n", + "minimart_anan\n", + "other/have_title/Việt_TTTM_Cho_Sui\n", + "minimart_anan\n", + "other/non_title\n", + "payoo\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "minimart_anan\n", + "payoo\n", + "other/have_title/TTTM_VAN_HO-SIEU_THI_SEIKA_MART\n", + "other/have_title/Chợ_Sủi_Phú_Thị_Gia_Lâm\n", + "guitar_cafe\n", + "other/non_title\n", + "the_coffee_house\n", + "sieu_thi_bach_hoa_tong_hop\n", + "other/non_title\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "vincommerce\n", + "other/non_title\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "nha_sach_gdtc_cam_pha\n", + "vincommerce\n", + "vincommerce\n", + "minimart_anan\n", + "nha_sach_gdtc_cam_pha\n", + "other/non_title\n", + "vincommerce\n", + "nha_sach_gdtc_cam_pha\n", + "nha_sach_gdtc_cam_pha\n", + "nha_sach_gdtc_cam_pha\n", + "vincommerce\n", + "other/non_title\n", + "minimart_anan\n", + "minimart_anan\n", + "other/non_title\n", + "pho_mo\n", + "other/non_title\n", + "other/have_title/CIRCLE_K_VIETNAM\n", + "minimart_anan\n", + "other/non_title\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "other/non_title\n", + "cua_hang_nam_oanh\n", + "other/have_title/CTY_CP_SÁCH_&_TBTH_QUẢNG_NINH\n", + "other/non_title\n", + "vincommerce\n", + "other/have_title/VINH\n", + "other/have_title/PARTS_GA_TEAUS_1.9\n", + "minimart_anan\n", + "vincommerce\n", + "minimart_anan\n", + "other/have_title/LahaTafe\n", + "vincommerce\n", + "vincommerce\n", + "other/have_title/charles\n", + "other/non_title\n", + "other/non_title\n", + "vincommerce\n", + "other/have_title/Nhà_Hàng_Aozora_Sushi\n", + "other/non_title\n", + "other/non_title\n", + "vincommerce\n", + "cua_hang_nam_oanh\n", + "other/non_title\n", + "other/non_title\n", + "vincommerce\n", + "other/non_title\n", + "sieu_thi_bach_hoa_tong_hop\n", + "other/non_title\n", + "minimart_anan\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "minimart_anan\n", + "other/non_title\n", + "other/non_title\n", + "other/non_title\n", + "minimart_anan\n", + "other/non_title\n", + "nha_sach_gdtc_cam_pha\n", + "other/non_title\n", + "minimart_anan\n", + "other/non_title\n", + "minimart_anan\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "other/non_title\n", + "cua_hang_nam_oanh\n", + "minimart_anan\n", + "other/have_title/C_H_A_M\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "pho_mo\n", + "other/non_title\n", + "cua_hang_nam_oanh\n", + "minimart_anan\n", + "the_coffee_house\n", + "minimart_anan\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "other/non_title\n", + "the_coffee_house\n", + "vincommerce\n", + "vincommerce\n", + "sieu_thi_bach_hoa_tong_hop\n", + "the_coffee_house\n", + "other/have_title/Thanh_Xuân\n", + "minimart_anan\n", + "vincommerce\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "other/non_title\n", + "other/non_title\n", + "vincommerce\n", + "nha_sach_gdtc_cam_pha\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "vincommerce\n", + "cua_hang_nam_oanh\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "other/have_title/MOOSERROO_VIETHAM_THE_MOOSE_&_ROO_SMOKEHOUSE\n", + "other/non_title\n", + "minimart_anan\n", + "vincommerce\n", + "other/non_title\n", + "other/non_title\n", + "the_coffee_house\n", + "other/non_title\n", + "other/have_title/Tiền_đã_Thanh_Xuân\n", + "pho_mo\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "pho_mo\n", + "payoo\n", + "phuc_anh_minimart\n", + "payoo\n", + "vincommerce\n", + "minimart_anan\n", + "other/non_title\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "cua_hang_nam_oanh\n", + "minimart_anan\n", + "other/non_title\n", + "minimart_anan\n", + "guitar_cafe\n", + "minimart_anan\n", + "sieu_thi_bach_hoa_tong_hop\n", + "other/non_title\n", + "sieu_thi_bach_hoa_tong_hop\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "vincommerce\n", + "other/non_title\n", + "minimart_anan\n", + "minimart_anan\n", + "other/non_title\n", + "cua_hang_nam_oanh\n", + "cua_hang_nam_oanh\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "other/non_title\n", + "other/non_title\n", + "minimart_anan\n", + "minimart_anan\n", + "payoo\n", + "other/non_title\n", + "vincommerce\n", + "nha_sach_gdtc_cam_pha\n", + "cua_hang_nam_oanh\n", + "minimart_anan\n", + "other/non_title\n", + "vincommerce\n", + "minimart_anan\n", + "other/non_title\n", + "other/non_title\n", + "cua_hang_nam_oanh\n", + "other/have_title/coopsmic\n", + "nha_sach_gdtc_cam_pha\n", + "cua_hang_nam_oanh\n", + "minimart_anan\n", + "minimart_anan\n", + "other/non_title\n", + "other/non_title\n", + "other/non_title\n", + "cua_hang_nam_oanh\n", + "vincommerce\n", + "minimart_anan\n", + "nha_sach_gdtc_cam_pha\n", + "other/non_title\n", + "other/non_title\n", + "other/have_title/thủ_Thanh_Xuân\n", + "vietcombank\n", + "vincommerce\n", + "other/non_title\n", + "minimart_anan\n", + "phuc_anh_minimart\n", + "minimart_anan\n", + "minimart_anan\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "minimart_anan\n", + "other/have_title/Phương_Ốc_Hải_Phòng\n", + "minimart_anan\n", + "minimart_anan\n", + "the_coffee_house\n", + "other/have_title/KAI_TEA_KAI_TEA\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "other/non_title\n", + "other/non_title\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "minimart_anan\n", + "minimart_anan\n", + "other/non_title\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "vincommerce\n", + "vincommerce\n", + "other/non_title\n", + "minimart_anan\n", + "nha_sach_gdtc_cam_pha\n", + "minimart_anan\n", + "minimart_anan\n", + "sctc_co_tho_104_tran_phu__cam_pha\n", + "minimart_anan\n", + "nha_sach_gdtc_cam_pha\n", + "vincommerce\n", + "other/non_title\n", + "nha_sach_gdtc_cam_pha\n", + "nha_sach_gdtc_cam_pha\n", + "the_coffee_house\n", + "saigon_coop_coop_food_hn_the_kpark\n", + "minimart_anan\n", + "other/non_title\n", + "minimart_anan\n", + "pho_mo\n", + "minimart_anan\n", + "pho_mo\n", + "cua_hang_nam_oanh\n", + "other/non_title\n", + "vincommerce\n", + "other/non_title\n", + "vincommerce\n", + "other/have_title/TALALA\n", + "the_coffee_house\n", + "other/have_title/ITTM\n", + "other/non_title\n", + "other/non_title\n", + "other/non_title\n", + "guitar_cafe\n", + "nha_sach_gdtc_cam_pha\n", + "other/have_title/VINCOM_SKYLAKE\n", + "vincommerce\n", + "other/non_title\n", + "minimart_anan\n", + "nha_sach_gdtc_cam_pha\n", + "other/non_title\n", + "vincommerce\n", + "other/have_title/COFFEE_Milano_Coffee_Vietnam\n", + "other/non_title\n", + "the_coffee_house\n", + "vincommerce\n", + "other/non_title\n", + "other/non_title\n", + "vincommerce\n", + "other/non_title\n", + "minimart_anan\n", + "minimart_anan\n", + "other/have_title/MARUMART\n", + "other/non_title\n", + "cua_hang_nam_oanh\n", + "minimart_anan\n", + "other/non_title\n", + "cua_hang_nam_oanh\n", + "minimart_anan\n", + "other/non_title\n", + "other/non_title\n", + "minimart_anan\n", + "pho_mo\n", + "vincommerce\n", + "other/non_title\n", + "minimart_anan\n", + "payoo\n" + ] + } + ], + "source": [ + "import Levenshtein\n", + "from pathlib import Path\n", + "import shutil\n", + "import re \n", + "from unidecode import unidecode\n", + "\n", + "def normalize(text):\n", + " text = text.lower()\n", + " text = unidecode(text)\n", + " text = re.sub(r'[^a-zA-Z0-9\\s]+', '', text)\n", + " return text \n", + " \n", + "\n", + "\n", + "def is_match(src, str_new, thr=0.7):\n", + " src = normalize(src)\n", + " str_new = normalize(str_new)\n", + " distance = Levenshtein.ratio(src, str_new)\n", + " if distance > thr:\n", + " return True \n", + " else:\n", + " return False\n", + "\n", + "def get_store_name(gt_store, store_list):\n", + " for store in store_list:\n", + " if is_match(store, gt_store, thr=0.6):\n", + " return store.lower()\n", + " \n", + " if len(gt_store) == 0:\n", + " return \"other/non_title\"\n", + " else:\n", + " return \"other/have_title/{}\".format(gt_store)\n", + " \n", + "\n", + "\n", + "\n", + "out_dir = \"/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/exp_5/test_mcocr_not_label_ep21_by_store_name\"\n", + "out_dir = Path(out_dir)\n", + "for img_name, item in pred_data.items():\n", + " store_name = item['Store_name_value']\n", + " store_category = get_store_name(store_name, store_list=store_names)\n", + " store_category = store_category.replace(\" \", \"_\")\n", + " print(store_category)\n", + " out_dir_by_store = out_dir / store_category\n", + " if not out_dir_by_store.exists():\n", + " out_dir_by_store.mkdir(parents=True, exist_ok=True)\n", + "\n", + " img_full_name = Path(img_name).with_suffix(\".jpg\")\n", + " img_full_path = Path(img_dir) / img_full_name\n", + " if not img_full_path.exists():\n", + " print(str(img_full_path))\n", + " continue\n", + " else:\n", + " shutil.copy(str(img_full_path), out_dir_by_store)\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": {}, + "outputs": [], + "source": [ + "import glob\n", + "import os \n", + "import shutil\n", + "non_title_dir = \"/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/exp_5/test_mcocr_not_label_ep21_by_store_name/other/non_title\"\n", + "src_dir = \"/mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/MC-OCR/raw/Images_aligned/train_splitted/not_labeling\"\n", + "\n", + "out_dir = \"/mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/MC-OCR/raw/Images_aligned/train_splitted/no_detect_seller\"\n", + "\n", + "non_seller_img_paths = glob.glob(non_title_dir + \"/*.jpg\")\n", + "if not os.path.exists(out_dir):\n", + " os.makedirs(out_dir, exist_ok=True)\n", + "for img_path in non_seller_img_paths:\n", + " shutil.copy(os.path.join(src_dir, os.path.basename(img_path)), out_dir)\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [ + { + "ename": "", + "evalue": "", + "output_type": "error", + "traceback": [ + "\u001b[1;31mFailed to start the Kernel 'py38_hoanglv (Python 3.8.16)'. \n", + "\u001b[1;31mView Jupyter log for further details. Cannot find module './351.node.js'\n", + "\u001b[1;31mRequire stack:\n", + "\u001b[1;31m- /home/sds/.vscode-server/extensions/ms-toolsai.jupyter-2023.3.1201040234/out/extension.node.js\n", + "\u001b[1;31m- /home/sds/.vscode-server/bin/252e5463d60e63238250799aef7375787f68b4ee/out/vs/loader.js\n", + "\u001b[1;31m- /home/sds/.vscode-server/bin/252e5463d60e63238250799aef7375787f68b4ee/out/bootstrap-amd.js\n", + "\u001b[1;31m- /home/sds/.vscode-server/bin/252e5463d60e63238250799aef7375787f68b4ee/out/bootstrap-fork.js" + ] + } + ], + "source": [ + "import json \n", + "with open(\"/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/pred_vat_multi_page.json\", 'r', encoding='utf8') as f:\n", + " data = json.load(f)\n", + " \n", + "data" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import shutil\n", + "import glob \n", + "from pathlib import Path" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "pdf_paths = glob.glob(\"/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/*.jpg\")\n", + "len(pdf_paths)\n", + "out_dir = \"/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/intermediate/multi_pages/SL_HCM_batch_2_first_last_page_2\"\n", + "if not Path(out_dir).exists():\n", + " Path(out_dir).mkdir(parents=True, exist_ok=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03684662_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03684662_2.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03684662_3.jpg', 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'/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03834825_9.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03834840_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03834834_2.jpg']\n" + ] + } + ], + "source": [ + "pdf_paths = sorted(pdf_paths)\n", + "print(pdf_paths[:10])\n", + "valid_pdf_paths = []\n", + "past_pdf_key = None\n", + "past_pdf_path = None\n", + "for pdf_path in pdf_paths:\n", + " pdf_key = str(Path(pdf_path).stem).split(\"_\")[0]\n", + " pdf_page = int(str(Path(pdf_path).stem).split(\"_\")[-1])\n", + " if past_pdf_key is None:\n", + " past_pdf_key = pdf_key\n", + " past_pdf_path = pdf_path\n", + " \n", + " if pdf_page == 1:\n", + " valid_pdf_paths.append(pdf_path)\n", + " \n", + " if past_pdf_key != pdf_key:\n", + " valid_pdf_paths.append(past_pdf_path)\n", + " \n", + " print(past_pdf_key, pdf_key)\n", + " past_pdf_path = pdf_path\n", + " past_pdf_key = pdf_key\n", + "print(valid_pdf_paths)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'EAS03808205': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03808205_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03808205_2.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03808205_3.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03808205_4.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03808205_5.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03808205_6.jpg', 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'/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03802424_2.jpg'], 'EAS03684846': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03684846_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03684846_2.jpg'], 'EAS03834840': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03834840_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03834840_2.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03834840_3.jpg'], 'EAS03743355': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03743355_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03743355_2.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03743355_3.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03743355_4.jpg'], 'EAS03685924': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03685924_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03685924_2.jpg'], 'EAS03805967': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03805967_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03805967_2.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03805967_3.jpg'], 'EAS03684855': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03684855_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03684855_2.jpg'], 'EAS03797812': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03797812_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03797812_2.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03797812_3.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03797812_4.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03797812_5.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03797812_6.jpg'], 'EAS03813592': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03813592_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03813592_2.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03813592_3.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03813592_4.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03813592_5.jpg'], 'EAS03809701': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03809701_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03809701_2.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03809701_3.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03809701_4.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03809701_5.jpg'], 'EAS03684671': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03684671_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03684671_2.jpg'], 'EAS03819335': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03819335_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03819335_2.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03819335_3.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03819335_4.jpg'], 'EAS03816179': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03816179_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03816179_2.jpg'], 'EAS03805606': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03805606_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03805606_2.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03805606_3.jpg'], 'EAS03684871': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03684871_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03684871_2.jpg'], 'EAS03819349': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03819349_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03819349_2.jpg'], 'EAS03750789': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03750789_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03750789_2.jpg'], 'EAS03743498': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03743498_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03743498_2.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03743498_3.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03743498_4.jpg'], 'EAS03834798': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03834798_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03834798_2.jpg'], 'EAS03819330': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03819330_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03819330_2.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03819330_3.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03819330_4.jpg'], 'EAS03799021': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03799021_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03799021_2.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03799021_3.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03799021_4.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03799021_5.jpg'], 'EAS03813595': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03813595_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03813595_2.jpg'], 'EAS03808299': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03808299_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03808299_2.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03808299_3.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03808299_4.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03808299_5.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03808299_6.jpg'], 'EAS03820888': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03820888_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03820888_2.jpg'], 'EAS03784255': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03784255_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03784255_2.jpg'], 'EAS03828421': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03828421_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03828421_2.jpg'], 'EAS03833384': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03833384_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03833384_2.jpg'], 'EAS03834139': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03834139_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03834139_2.jpg'], 'EAS03820901': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03820901_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03820901_2.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03820901_3.jpg'], 'EAS03815264': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03815264_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03815264_2.jpg'], 'EAS03684856': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03684856_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03684856_2.jpg'], 'EAS03813646': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03813646_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03813646_2.jpg'], 'EAS03819215': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03819215_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03819215_2.jpg'], 'EAS03816196': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03816196_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03816196_2.jpg'], 'EAS03834800': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03834800_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03834800_2.jpg'], 'EAS03819364': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03819364_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03819364_2.jpg'], 'EAS03809656': ['/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03809656_1.jpg', '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2/EAS03809656_2.jpg']}\n" + ] + } + ], + "source": [ + "data_dict = {}\n", + "for pdf_path in pdf_paths:\n", + " pdf_key = str(Path(pdf_path).stem).split(\"_\")[0]\n", + " if pdf_key not in data_dict:\n", + " data_dict[pdf_key] = [pdf_path]\n", + " else:\n", + " data_dict[pdf_key].append(pdf_path)\n", + "\n", + "for pdf_key in data_dict.keys():\n", + " data_dict[pdf_key] = sorted(data_dict[pdf_key], key=lambda pdf_path: int(Path(pdf_path).stem.split(\"_\")[-1]))\n", + "\n", + "print(data_dict)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "for k, pdf_list in data_dict.items():\n", + " first_page, last_page = pdf_list[0], pdf_list[-1]\n", + " shutil.copy(first_page, out_dir)\n", + " shutil.copy(last_page, out_dir)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "for pdf_path in valid_pdf_paths:\n", + " shutil.copy(pdf_path, out_dir)" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "py38_hoanglv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.16" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/cope2n-ai-fi/modules/sdsvkie/notebooks/data.py b/cope2n-ai-fi/modules/sdsvkie/notebooks/data.py new file mode 100755 index 0000000..4fb9f03 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/notebooks/data.py @@ -0,0 +1,84 @@ +# from sdsvkie.utils.io_file import read_json +import json +import Levenshtein +from pathlib import Path +import shutil +import re +from unidecode import unidecode + +# from sdsvkie.utils.io_file import read_json + + +def normalize(text): + text = text.lower() + text = unidecode(text) + text = re.sub(r'[^a-zA-Z0-9\s]+', '', text) + return text + + + +def is_match(src, str_new, thr=0.7): + src = normalize(src) + str_new = normalize(str_new) + distance = Levenshtein.ratio(src, str_new) + if distance > thr: + return True + else: + return False + +def get_store_name(gt_store, store_list): + for store in store_list: + if is_match(store, gt_store, thr=0.6): + return store.lower() + + if len(gt_store) == 0: + return "other_non_title" + else: + return "other_have_title_{}".format(gt_store) + + +def read_json(json_path): + with open(json_path, "r", encoding="utf8") as f: + data = json.load(f) + return data + + + + +json_path = "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/test_ss_receipt.json" +pred_data = read_json(json_path) + +store_names = [normalize(item['Store_name_value']) for k, item in pred_data.items()] +# store_names = list(set(store_names)) +from collections import Counter +my_counter = Counter(store_names) +list_tuples = my_counter.most_common() +print(list_tuples) +stores = [x[0] for x in list_tuples] +print(stores) + + +store_names = stores[1:] + +img_dir = "/mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/SS_Receipt/Images_splitted/All" +out_dir = "/mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/SS_Receipt/Done" +out_dir = Path(out_dir) +for img_name, item in pred_data.items(): + store_name = item['Store_name_value'] + store_category = get_store_name(store_name, store_list=store_names) + store_category = store_category.replace(" ", "_") + print(store_category) + out_dir_by_store = out_dir / store_category + if not out_dir_by_store.exists(): + out_dir_by_store.mkdir(parents=True, exist_ok=True) + + img_full_name = Path(img_name).with_suffix(".jpg") + img_full_path = Path(img_dir) / img_full_name + + txt_full_path = img_full_path.with_suffix(".txt") + if not img_full_path.exists(): + print(str(img_full_path)) + continue + else: + shutil.copy(str(img_full_path), out_dir_by_store) + shutil.copy(str(txt_full_path), out_dir_by_store) \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/notebooks/page0.jpg b/cope2n-ai-fi/modules/sdsvkie/notebooks/page0.jpg new file mode 100755 index 0000000..c4b7a0d Binary files /dev/null and b/cope2n-ai-fi/modules/sdsvkie/notebooks/page0.jpg differ diff --git a/cope2n-ai-fi/modules/sdsvkie/notebooks/pdf2image.ipynb b/cope2n-ai-fi/modules/sdsvkie/notebooks/pdf2image.ipynb new file mode 100755 index 0000000..0a17864 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/notebooks/pdf2image.ipynb @@ -0,0 +1,197 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import fitz\n", + "from io import BytesIO" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "1\n" + ] + } + ], + "source": [ + "pdf_path = \"/mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/raw/batch_1/PDF/eReceipt/(Sol tech Grp)_202303_Receipt_Transfort #1.pdf\"\n", + "with open(pdf_path, 'rb') as f:\n", + " pdf_bytes = f.read()\n", + "doc = fitz.open(stream=pdf_bytes, filetype='pdf')\n", + "print(doc.page_count)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "isinstance(pdf_bytes, bytes)" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np \n", + "import os \n", + "\n", + "def pdf_to_image(pdf, dpi=300, is_get_first_page=False, max_page=1000):\n", + " \"\"\"_summary_\n", + "\n", + " Args:\n", + " pdf (_type_): _description_\n", + " dpi (int, optional): _description_. Defaults to 300.\n", + " is_get_first_page (bool, optional): _description_. Defaults to False.\n", + " max_page (int, optional): _description_. Defaults to 1000.\n", + "\n", + " Raises:\n", + " NotImplementedError: _description_\n", + "\n", + " Returns:\n", + " _type_: _description_\n", + " \"\"\"\n", + " if isinstance(pdf, str):\n", + " if not os.path.exists(pdf):\n", + " print(f\"Not found pdf path at {pdf}\")\n", + " return []\n", + " doc = fitz.open(pdf) # open document\n", + " elif isinstance(pdf, bytes):\n", + " doc = fitz.open(stream=pdf, filetype='pdf')\n", + " else:\n", + " raise NotImplementedError(f\"Not yet implement for {type(pdf)} type !!!\")\n", + " \n", + " zoom = dpi // 72\n", + " magnify = fitz.Matrix(zoom, zoom) \n", + " imgs = []\n", + " for idx, page in enumerate(doc):\n", + " pix = page.get_pixmap(matrix=magnify) # render page to an image\n", + " \n", + " im = np.frombuffer(pix.samples, dtype=np.uint8).reshape(pix.h, pix.w, pix.n)\n", + " im = np.ascontiguousarray(im[..., [2, 1, 0]]) # rgb to bgr\n", + " imgs.append(im)\n", + " if is_get_first_page or idx >= max_page:\n", + " break\n", + " return imgs" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "ename": "FileNotFoundError", + "evalue": "no such file: '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/raw/batch_1/PDF/eReceipt/(Sol tech Grp)_202303_Rec eipt_Transfort #1.pdf'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mFileNotFoundError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[18], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m imgs \u001b[39m=\u001b[39m pdf_to_image(pdf\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39m/mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/raw/batch_1/PDF/eReceipt/(Sol tech Grp)_202303_Rec eipt_Transfort #1.pdf\u001b[39;49m\u001b[39m\"\u001b[39;49m)\n\u001b[1;32m 2\u001b[0m \u001b[39mprint\u001b[39m(\u001b[39mlen\u001b[39m(imgs))\n", + "Cell \u001b[0;32mIn[13], line 5\u001b[0m, in \u001b[0;36mpdf_to_image\u001b[0;34m(pdf, dpi, is_get_first_page)\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mpdf_to_image\u001b[39m(pdf, dpi\u001b[39m=\u001b[39m\u001b[39m300\u001b[39m, is_get_first_page\u001b[39m=\u001b[39m\u001b[39mFalse\u001b[39;00m):\n\u001b[1;32m 4\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39misinstance\u001b[39m(pdf, \u001b[39mstr\u001b[39m):\n\u001b[0;32m----> 5\u001b[0m doc \u001b[39m=\u001b[39m fitz\u001b[39m.\u001b[39;49mopen(pdf) \u001b[39m# open document\u001b[39;00m\n\u001b[1;32m 6\u001b[0m \u001b[39melif\u001b[39;00m \u001b[39misinstance\u001b[39m(pdf, \u001b[39mbytes\u001b[39m):\n\u001b[1;32m 7\u001b[0m doc \u001b[39m=\u001b[39m fitz\u001b[39m.\u001b[39mopen(stream\u001b[39m=\u001b[39mpdf, filetype\u001b[39m=\u001b[39m\u001b[39m'\u001b[39m\u001b[39mpdf\u001b[39m\u001b[39m'\u001b[39m)\n", + "File \u001b[0;32m~/miniconda3/envs/py38_hoanglv/lib/python3.8/site-packages/fitz/fitz.py:3867\u001b[0m, in \u001b[0;36mDocument.__init__\u001b[0;34m(self, filename, stream, filetype, rect, width, height, fontsize)\u001b[0m\n\u001b[1;32m 3865\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m os\u001b[39m.\u001b[39mpath\u001b[39m.\u001b[39mexists(filename):\n\u001b[1;32m 3866\u001b[0m msg \u001b[39m=\u001b[39m \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mno such file: \u001b[39m\u001b[39m'\u001b[39m\u001b[39m{\u001b[39;00mfilename\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[0;32m-> 3867\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mFileNotFoundError\u001b[39;00m(msg)\n\u001b[1;32m 3868\u001b[0m \u001b[39melif\u001b[39;00m \u001b[39mnot\u001b[39;00m os\u001b[39m.\u001b[39mpath\u001b[39m.\u001b[39misfile(filename):\n\u001b[1;32m 3869\u001b[0m msg \u001b[39m=\u001b[39m \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m'\u001b[39m\u001b[39m{\u001b[39;00mfilename\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m\u001b[39m is no file\u001b[39m\u001b[39m\"\u001b[39m\n", + "\u001b[0;31mFileNotFoundError\u001b[0m: no such file: '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/raw/batch_1/PDF/eReceipt/(Sol tech Grp)_202303_Rec eipt_Transfort #1.pdf'" + ] + } + ], + "source": [ + "imgs = pdf_to_image(pdf=\"/mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/raw/batch_1/PDF/eReceipt/(Sol tech Grp)_202303_Rec eipt_Transfort #1.pdf\")\n", + "print(len(imgs))" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt \n", + "plt.imshow(imgs[0])\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "# import module\n", + "from pdf2image import convert_from_path\n", + " \n", + " \n", + "# Store Pdf with convert_from_path function\n", + "images = convert_from_path('/mnt/hdd2T/AICR/Projects/2023/Invoices_SL_HCM/EAS03581488.pdf', dpi=300)\n", + " \n", + "for i in range(len(images)):\n", + " \n", + " # Save pages as images in the pdf\n", + " images[i].save('page'+ str(i) +'.jpg', 'JPEG')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "py38_hoanglv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.16" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/cope2n-ai-fi/modules/sdsvkie/notebooks/scp.sh b/cope2n-ai-fi/modules/sdsvkie/notebooks/scp.sh new file mode 100755 index 0000000..d9d239b --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/notebooks/scp.sh @@ -0,0 +1 @@ +rsync -r --exclude='workdirs/' --exclude='notebooks/' --exclude='weights/' --exclude='wandb/' --exclude='microsoft/' /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie user@107.120.133.42:/mnt/data/kie diff --git a/cope2n-ai-fi/modules/sdsvkie/notebooks/sdsvap_invoice.ipynb b/cope2n-ai-fi/modules/sdsvkie/notebooks/sdsvap_invoice.ipynb new file mode 100755 index 0000000..57814e6 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/notebooks/sdsvap_invoice.ipynb @@ -0,0 +1,194 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import os \n", + "import glob \n", + "from tqdm import tqdm \n", + "import cv2 \n", + "import shutil\n", + "from pathlib import Path" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "DATA_DIR = \"/mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/raw/IMGS\"\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "def copy_only_first_page(data_dir, out_dir, skip_types=['Receipt_taxi','Receipt_food_Cam', 'Receipt_food_Scan']):\n", + " paths = sorted(glob.glob(data_dir + \"/*/*\"))\n", + " print(\"Total paths: \", len(paths))\n", + " out_dir = Path(out_dir)\n", + " for path in paths:\n", + " type_doc = Path(path).parent.name\n", + " out_dir_full = out_dir / type_doc\n", + " if not out_dir_full.exists():\n", + " out_dir_full.mkdir(parents=True)\n", + " if type_doc in skip_types:\n", + " shutil.copy(path, str(out_dir_full))\n", + " else:\n", + " if \"_1.jpg\" in path:\n", + " shutil.copy(path, out_dir_full)\n", + " prefix_name = \"_\".join(path.split(\"_\")[:-1]) + \"_1.jpg\"\n", + " print(prefix_name)\n", + " if Path(prefix_name).exists():\n", + " continue\n", + " else:\n", + " shutil.copy(path, out_dir_full)" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "classes = [\n", + " # id invoice\n", + " 'No_key', # số hóa đơn\n", + " 'No_value', \n", + " 'Form_key', # mẫu số hóa đơn\n", + " 'Form_value', \n", + " 'Serial_key', # số kí hiệu hoá đơn\n", + " 'Serial_value', \n", + " 'Date_value', \n", + "\n", + " # seller info\n", + " 'Seller_company_name_key', \n", + " 'Seller_company_name_value', \n", + " 'Seller_tax_code_key', \n", + " 'Seller_tax_code_value', \n", + " 'Seller_address_value',\n", + " 'Seller_address_key', \n", + " 'Seller_tel_key',\n", + " 'Seller_tel_value', \n", + " \n", + " # buyer info\n", + " 'Buyer_personal_name_key',\n", + " 'Buyer_personal_name_value', \n", + " 'Buyer_company_name_key', \n", + " 'Buyer_company_name_value', \n", + " 'Buyer_tax_code_key', \n", + " 'Buyer_tax_code_value', \n", + " 'Buyer_address_key', \n", + " 'Buyer_address_value', \n", + " 'Buyer_address_key',\n", + " 'Buyer_address_value',\n", + "\n", + " # money info\n", + " 'Tax_amount_key', \n", + " 'Tax_amount_value', \n", + " 'Total_key', \n", + " 'Total_value', \n", + " 'Total_in_words_key', \n", + " 'Total_in_words_value',\n", + " \n", + " 'Other', \n", + "]" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "classes = [x.lower() for x in classes]" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['no_key',\n", + " 'no_value',\n", + " 'form_key',\n", + " 'form_value',\n", + " 'serial_key',\n", + " 'serial_value',\n", + " 'date_value',\n", + " 'seller_company_name_key',\n", + " 'seller_company_name_value',\n", + " 'seller_tax_code_key',\n", + " 'seller_tax_code_value',\n", + " 'seller_address_value',\n", + " 'seller_address_key',\n", + " 'seller_tel_key',\n", + " 'seller_tel_value',\n", + " 'buyer_personal_name_key',\n", + " 'buyer_personal_name_value',\n", + " 'buyer_company_name_key',\n", + " 'buyer_company_name_value',\n", + " 'buyer_tax_code_key',\n", + " 'buyer_tax_code_value',\n", + " 'buyer_address_key',\n", + " 'buyer_address_value',\n", + " 'buyer_address_key',\n", + " 'buyer_address_value',\n", + " 'tax_amount_key',\n", + " 'tax_amount_value',\n", + " 'total_key',\n", + " 'total_value',\n", + " 'total_in_words_key',\n", + " 'total_in_words_value',\n", + " 'other']" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "classes" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "py38_hoanglv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.16" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/cope2n-ai-fi/modules/sdsvkie/notebooks/wildreceipt_data.ipynb b/cope2n-ai-fi/modules/sdsvkie/notebooks/wildreceipt_data.ipynb new file mode 100755 index 0000000..0289d25 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/notebooks/wildreceipt_data.ipynb @@ -0,0 +1,2129 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "import os \n", + "import json\n", + "import numpy as np\n", + "from pathlib import Path\n", + "import shutil\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "def write_txt(txt, data, mode=\"w\"):\n", + " with open(txt, mode, encoding=\"utf8\") as f:\n", + " for line in data:\n", + " f.write(line + \"\\n\")\n", + "\n", + "\n", + "def read_txt(txt):\n", + " with open(txt, \"r\", encoding=\"utf8\") as f:\n", + " data = [line.strip() for line in f]\n", + " return data\n", + "\n", + "\n", + "def poly2bbox(poly):\n", + " poly = np.array(poly).astype(np.uint32).reshape(-1, 2)\n", + " xmin, ymin = np.min(poly, axis=0)\n", + " xmax, ymax = np.max(poly, axis=0)\n", + " bbox = [xmin, ymin, xmax, ymax]\n", + " return bbox\n", + "\n", + "\n", + " \n", + "def create_kie_wildreceipt(root_dir, txt_file, classes, out_dir):\n", + " if not out_dir.exists():\n", + " out_dir.mkdir(parents=True)\n", + " visited = {}\n", + " data = read_txt(txt_file)\n", + " for item in data:\n", + " \n", + " item = json.loads(item)\n", + " print(item)\n", + " file_name = Path(item['file_name'])\n", + " annos = item['annotations']\n", + " txt_out_data = []\n", + " for anno in annos:\n", + " box = anno['box']\n", + " box = poly2bbox(box)\n", + " text = anno['text']\n", + " text = text.replace(\"\\t\", \" \")\n", + " label = classes[anno['label']]\n", + " out = \"\\t\".join([str(x) for x in box])\n", + " out = \"\\t\".join([out, text, label])\n", + " txt_out_data.append(out)\n", + "\n", + " txt_name = Path(file_name).with_suffix(\".txt\").name\n", + " if txt_name not in visited:\n", + " visited[txt_name] = 1\n", + " else:\n", + " visited[txt_name] += 1\n", + " out_txt_path = out_dir / txt_name\n", + "\n", + " write_txt(out_txt_path, txt_out_data)\n", + " img_out_path = out_dir / file_name.name \n", + " shutil.copy(root_dir / file_name, img_out_path)\n", + "\n", + "def create_kie_wildreceipt_dataset(root_dir, train_txt, test_txt, class_file, out_dir):\n", + " root_dir = Path(root_dir)\n", + " out_dir = Path(out_dir)\n", + " if not out_dir.exists():\n", + " out_dir.mkdir(parents=True)\n", + "\n", + "\n", + " classes = read_txt(class_file)\n", + " classes = {\n", + " int(item.split(\" \")[0]): item.split(\" \")[1] for item in classes\n", + " }\n", + " print(classes) \n", + " \n", + " create_kie_wildreceipt(root_dir, train_txt, classes, out_dir / \"train\")\n", + " create_kie_wildreceipt(root_dir, test_txt, classes, out_dir / \"test\")\n", + " # print(data[0])" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{0: 'Ignore', 1: 'Store_name_value', 2: 'Store_name_key', 3: 'Store_addr_value', 4: 'Store_addr_key', 5: 'Tel_value', 6: 'Tel_key', 7: 'Date_value', 8: 'Date_key', 9: 'Time_value', 10: 'Time_key', 11: 'Prod_item_value', 12: 'Prod_item_key', 13: 'Prod_quantity_value', 14: 'Prod_quantity_key', 15: 'Prod_price_value', 16: 'Prod_price_key', 17: 'Subtotal_value', 18: 'Subtotal_key', 19: 'Tax_value', 20: 'Tax_key', 21: 'Tips_value', 22: 'Tips_key', 23: 'Total_value', 24: 'Total_key', 25: 'Others'}\n", + "{'file_name': 'image_files/Image_16/11/d5de7f2a20751e50b84c747c17a24cd98bed3554.jpeg', 'height': 1200, 'width': 1600, 'annotations': [{'box': [550.0, 190.0, 937.0, 190.0, 937.0, 104.0, 550.0, 104.0], 'text': 'SAFEWAY', 'label': 1}, {'box': [1048.0, 211.0, 1074.0, 211.0, 1074.0, 196.0, 1048.0, 196.0], 'text': 'TM', 'label': 25}, {'box': [535.0, 239.0, 833.0, 239.0, 833.0, 200.0, 535.0, 200.0], 'text': 'ATOREMGRTOMMILAZZO', 'label': 25}, {'box': [907.0, 256.0, 1081.0, 256.0, 1081.0, 223.0, 907.0, 223.0], 'text': '703-777-5833', 'label': 5}, {'box': [576.0, 282.0, 1016.0, 282.0, 1016.0, 230.0, 576.0, 230.0], 'text': 'THANKYOUFORSHOPPINGWITHUS!', 'label': 25}, {'box': [724.0, 387.0, 840.0, 387.0, 840.0, 355.0, 724.0, 355.0], 'text': 'GROCERY', 'label': 25}, {'box': [474.0, 433.0, 733.0, 433.0, 733.0, 394.0, 474.0, 394.0], 'text': 'BCCHOCCUPCAKES', 'label': 11}, {'box': [470.0, 466.0, 764.0, 466.0, 764.0, 421.0, 470.0, 421.0], 'text': 'ACNSPRYFRTSHAPE', 'label': 11}, {'box': [466.0, 483.0, 595.0, 483.0, 595.0, 448.0, 466.0, 448.0], 'text': 'Regprice', 'label': 25}, {'box': [463.0, 517.0, 658.0, 517.0, 658.0, 478.0, 463.0, 478.0], 'text': 'Cardsavings', 'label': 25}, {'box': [459.0, 538.0, 574.0, 538.0, 574.0, 507.0, 459.0, 507.0], 'text': 'MfrCpn', 'label': 25}, {'box': [455.0, 578.0, 686.0, 578.0, 686.0, 536.0, 455.0, 536.0], 'text': 'MultipliedCpn', 'label': 25}, {'box': [453.0, 611.0, 750.0, 611.0, 750.0, 565.0, 453.0, 565.0], 'text': 'DULCEDELECHECHE', 'label': 11}, {'box': [449.0, 625.0, 581.0, 625.0, 581.0, 593.0, 449.0, 593.0], 'text': 'Regprice', 'label': 25}, {'box': [446.0, 662.0, 644.0, 662.0, 644.0, 623.0, 446.0, 623.0], 'text': 'CardSavings', 'label': 25}, {'box': [443.0, 683.0, 558.0, 683.0, 558.0, 650.0, 443.0, 650.0], 'text': 'MfrCpn', 'label': 25}, {'box': [441.0, 723.0, 673.0, 723.0, 673.0, 682.0, 441.0, 682.0], 'text': 'MuitipliedCpn', 'label': 25}, {'box': [437.0, 758.0, 737.0, 758.0, 737.0, 708.0, 437.0, 708.0], 'text': 'MULTIGRAINCHEERIO', 'label': 11}, {'box': [433.0, 774.0, 566.0, 774.0, 566.0, 739.0, 433.0, 739.0], 'text': 'RegPrice', 'label': 25}, {'box': [430.0, 808.0, 632.0, 808.0, 632.0, 769.0, 430.0, 769.0], 'text': 'CardSavings', 'label': 25}, {'box': [426.0, 830.0, 544.0, 830.0, 544.0, 800.0, 426.0, 800.0], 'text': 'MfrCpn', 'label': 25}, {'box': [424.0, 872.0, 660.0, 872.0, 660.0, 831.0, 424.0, 831.0], 'text': 'MuitieliedCpn', 'label': 25}, {'box': [419.0, 907.0, 708.0, 907.0, 708.0, 860.0, 419.0, 860.0], 'text': 'PROGRESSOR&HSTK', 'label': 11}, {'box': [414.0, 922.0, 550.0, 922.0, 550.0, 890.0, 414.0, 890.0], 'text': 'RegPrice', 'label': 25}, {'box': [413.0, 962.0, 615.0, 962.0, 615.0, 923.0, 413.0, 923.0], 'text': 'CardSavings', 'label': 25}, {'box': [613.0, 1049.0, 836.0, 1049.0, 836.0, 1001.0, 613.0, 1001.0], 'text': 'REFRIG/FROZEN', 'label': 25}, {'box': [1005.0, 465.0, 1070.0, 465.0, 1070.0, 437.0, 1005.0, 437.0], 'text': '3.99', 'label': 15}, {'box': [1023.0, 491.0, 1067.0, 491.0, 1067.0, 469.0, 1023.0, 469.0], 'text': '.49', 'label': 15}, {'box': [848.0, 509.0, 913.0, 509.0, 913.0, 481.0, 848.0, 481.0], 'text': '3.79', 'label': 25}, {'box': [847.0, 538.0, 927.0, 538.0, 927.0, 512.0, 847.0, 512.0], 'text': '1.80-', 'label': 25}, {'box': [863.0, 566.0, 925.0, 566.0, 925.0, 543.0, 863.0, 543.0], 'text': '.75-', 'label': 25}, {'box': [862.0, 596.0, 923.0, 596.0, 923.0, 572.0, 862.0, 572.0], 'text': '.75-', 'label': 25}, {'box': [993.0, 641.0, 1060.0, 641.0, 1060.0, 610.0, 993.0, 610.0], 'text': '1.99', 'label': 15}, {'box': [836.0, 655.0, 901.0, 655.0, 901.0, 629.0, 836.0, 629.0], 'text': '4.19', 'label': 25}, {'box': [835.0, 683.0, 916.0, 683.0, 916.0, 658.0, 835.0, 658.0], 'text': '1.20-', 'label': 25}, {'box': [853.0, 713.0, 914.0, 713.0, 914.0, 688.0, 853.0, 688.0], 'text': '.50-', 'label': 25}, {'box': [851.0, 743.0, 912.0, 743.0, 912.0, 719.0, 851.0, 719.0], 'text': '.50-', 'label': 25}, {'box': [985.0, 791.0, 1050.0, 791.0, 1050.0, 760.0, 985.0, 760.0], 'text': '1.50', 'label': 15}, {'box': [825.0, 804.0, 891.0, 804.0, 891.0, 775.0, 825.0, 775.0], 'text': '3.99', 'label': 25}, {'box': [826.0, 832.0, 906.0, 832.0, 906.0, 805.0, 826.0, 805.0], 'text': '1.49-', 'label': 25}, {'box': [840.0, 865.0, 903.0, 865.0, 903.0, 838.0, 840.0, 838.0], 'text': '.50-', 'label': 25}, {'box': [839.0, 895.0, 901.0, 895.0, 901.0, 869.0, 839.0, 869.0], 'text': '.50-', 'label': 25}, {'box': [972.0, 946.0, 1041.0, 946.0, 1041.0, 913.0, 972.0, 913.0], 'text': '2.00', 'label': 15}, {'box': [812.0, 957.0, 878.0, 957.0, 878.0, 928.0, 812.0, 928.0], 'text': '2.69', 'label': 25}, {'box': [831.0, 989.0, 894.0, 989.0, 894.0, 963.0, 831.0, 963.0], 'text': '.69-', 'label': 25}, {'box': [402.0, 1069.0, 483.0, 1069.0, 483.0, 1044.0, 402.0, 1044.0], 'text': '1OIY', 'label': 14}, {'box': [395.0, 1127.0, 703.0, 1127.0, 703.0, 1072.0, 395.0, 1072.0], 'text': 'PLSBRYBSCTSANDWI', 'label': 11}, {'box': [395.0, 1159.0, 702.0, 1159.0, 702.0, 1105.0, 395.0, 1105.0], 'text': 'TOTINOSPZASTOFFE', 'label': 11}, {'box': [390.0, 1173.0, 526.0, 1173.0, 526.0, 1136.0, 390.0, 1136.0], 'text': 'RegPrice', 'label': 25}, {'box': [384.0, 1199.0, 589.0, 1199.0, 589.0, 1172.0, 384.0, 1172.0], 'text': '', 'label': 0}, {'box': [790.0, 1198.0, 861.0, 1198.0, 861.0, 1177.0, 790.0, 1177.0], 'text': '', 'label': 0}, {'box': [958.0, 1171.0, 1029.0, 1171.0, 1029.0, 1132.0, 958.0, 1132.0], 'text': '3.50', 'label': 15}, {'box': [956.0, 1198.0, 1029.0, 1198.0, 1029.0, 1163.0, 956.0, 1163.0], 'text': '3.49', 'label': 15}, {'box': [1091.0, 466.0, 1103.0, 466.0, 1103.0, 439.0, 1091.0, 439.0], 'text': 'B', 'label': 25}, {'box': [1088.0, 494.0, 1102.0, 494.0, 1102.0, 469.0, 1088.0, 469.0], 'text': 'B', 'label': 25}, {'box': [1078.0, 642.0, 1092.0, 642.0, 1092.0, 615.0, 1078.0, 615.0], 'text': 'B', 'label': 25}, {'box': [1070.0, 792.0, 1087.0, 792.0, 1087.0, 765.0, 1070.0, 765.0], 'text': 'B', 'label': 25}, {'box': [1062.0, 948.0, 1077.0, 948.0, 1077.0, 919.0, 1062.0, 919.0], 'text': 'B', 'label': 25}, {'box': [1045.0, 1168.0, 1063.0, 1168.0, 1063.0, 1143.0, 1045.0, 1143.0], 'text': 'B', 'label': 25}, {'box': [1044.0, 1198.0, 1060.0, 1198.0, 1060.0, 1176.0, 1044.0, 1176.0], 'text': 'B', 'label': 25}]}\n", + "{'file_name': 'image_files/Image_36/15/f4bb5ce76d2bc39f560fade5d3bc8aee9edaee6a.jpeg', 'height': 1777, 'width': 1000, 'annotations': [{'box': [273.0, 22.0, 737.0, 22.0, 737.0, 1.0, 273.0, 1.0], 'text': '', 'label': 0}, {'box': [222.0, 69.0, 761.0, 69.0, 761.0, 18.0, 222.0, 18.0], 'text': 'Rulesandregulationsapply.Seecontestrulesfordetails.', 'label': 25}, {'box': [369.0, 105.0, 549.0, 105.0, 549.0, 62.0, 369.0, 62.0], 'text': 'Walmart', 'label': 1}, {'box': [449.0, 117.0, 545.0, 117.0, 545.0, 97.0, 449.0, 97.0], 'text': 'supercentre', 'label': 25}, {'box': [360.0, 197.0, 552.0, 197.0, 552.0, 156.0, 360.0, 156.0], 'text': 'SUPERCENTER', 'label': 25}, {'box': [326.0, 224.0, 604.0, 224.0, 604.0, 184.0, 326.0, 184.0], 'text': 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'WithpurchaseofanyRainXorUltimateExpress', 'label': 25}, {'box': [86.0, 999.0, 645.0, 999.0, 645.0, 959.0, 86.0, 959.0], 'text': 'washreceive1$offyournextvisitwithin', 'label': 25}]}\n", + "{'file_name': 'image_files/Image_66/4/5b6f6c44f766c762362c03c7c7d71f7f47bfa015.jpeg', 'height': 450, 'width': 337, 'annotations': [{'box': [120.0, 43.0, 236.0, 43.0, 236.0, 32.0, 120.0, 32.0], 'text': 'OLDCASTLEPUB', 'label': 1}, {'box': [104.0, 54.0, 253.0, 54.0, 253.0, 41.0, 104.0, 41.0], 'text': '160W54THSTREET', 'label': 3}, {'box': [84.0, 75.0, 217.0, 75.0, 217.0, 62.0, 84.0, 62.0], 'text': '0125TABLE5#Party1', 'label': 25}, {'box': [84.0, 85.0, 179.0, 85.0, 179.0, 73.0, 84.0, 73.0], 'text': 'MARIBELMSvrCk:13', 'label': 25}, {'box': [187.0, 86.0, 224.0, 86.0, 224.0, 74.0, 187.0, 74.0], 'text': '10/24/14', 'label': 7}, {'box': [83.0, 96.0, 183.0, 96.0, 183.0, 84.0, 83.0, 84.0], 'text': 'DININGROOM', 'label': 25}, {'box': [83.0, 114.0, 89.0, 114.0, 89.0, 105.0, 83.0, 105.0], 'text': '2', 'label': 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139.0], 'text': 'SIDECAESAR', 'label': 11}, {'box': [30.0, 168.0, 92.0, 168.0, 92.0, 156.0, 30.0, 156.0], 'text': 'JAMBALAYA', 'label': 11}, {'box': [30.0, 185.0, 119.0, 185.0, 119.0, 171.0, 30.0, 171.0], 'text': '8OZSTRIPLOIN', 'label': 11}, {'box': [29.0, 201.0, 85.0, 201.0, 85.0, 188.0, 29.0, 188.0], 'text': 'ADDMUSH', 'label': 11}, {'box': [29.0, 218.0, 112.0, 218.0, 112.0, 204.0, 29.0, 204.0], 'text': 'FOUNTAINPOP', 'label': 11}, {'box': [255.0, 138.0, 287.0, 138.0, 287.0, 126.0, 255.0, 126.0], 'text': '16.00', 'label': 15}, {'box': [261.0, 153.0, 287.0, 153.0, 287.0, 141.0, 261.0, 141.0], 'text': '4.99', 'label': 15}, {'box': [255.0, 170.0, 288.0, 170.0, 288.0, 158.0, 255.0, 158.0], 'text': '16.00', 'label': 15}, {'box': [254.0, 187.0, 287.0, 187.0, 287.0, 175.0, 254.0, 175.0], 'text': '39.90', 'label': 15}, {'box': [262.0, 203.0, 288.0, 203.0, 288.0, 190.0, 262.0, 190.0], 'text': '1.98', 'label': 15}, {'box': [261.0, 219.0, 288.0, 219.0, 288.0, 207.0, 261.0, 207.0], 'text': 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507.0, 462.0, 507.0, 443.0, 415.0, 443.0], 'text': '16.07.2012', 'label': 7}, {'box': [468.0, 506.0, 510.0, 506.0, 510.0, 486.0, 468.0, 486.0], 'text': '3,10', 'label': 15}, {'box': [470.0, 551.0, 512.0, 551.0, 512.0, 531.0, 470.0, 531.0], 'text': '7,90', 'label': 15}, {'box': [473.0, 598.0, 514.0, 598.0, 514.0, 575.0, 473.0, 575.0], 'text': '1,90', 'label': 15}, {'box': [475.0, 645.0, 516.0, 645.0, 516.0, 622.0, 475.0, 622.0], 'text': '2,50', 'label': 15}, {'box': [448.0, 690.0, 527.0, 690.0, 527.0, 668.0, 448.0, 668.0], 'text': '15,40€', 'label': 23}, {'box': [394.0, 714.0, 470.0, 714.0, 470.0, 694.0, 394.0, 694.0], 'text': '12,94€', 'label': 17}, {'box': [399.0, 738.0, 471.0, 738.0, 471.0, 716.0, 399.0, 716.0], 'text': '2,46€', 'label': 19}, {'box': [536.0, 711.0, 546.0, 711.0, 546.0, 693.0, 536.0, 693.0], 'text': 'A', 'label': 25}, {'box': [536.0, 733.0, 548.0, 733.0, 548.0, 718.0, 536.0, 718.0], 'text': 'A', 'label': 25}, {'box': [377.0, 763.0, 528.0, 763.0, 528.0, 740.0, 377.0, 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406.0, 211.0, 339.0, 211.0], 'text': '50000.00', 'label': 15}, {'box': [340.0, 249.0, 406.0, 249.0, 406.0, 231.0, 340.0, 231.0], 'text': '40000.00', 'label': 15}, {'box': [355.0, 269.0, 408.0, 269.0, 408.0, 252.0, 355.0, 252.0], 'text': '810.00', 'label': 15}, {'box': [351.0, 291.0, 409.0, 291.0, 409.0, 273.0, 351.0, 273.0], 'text': '1050.00', 'label': 15}, {'box': [352.0, 312.0, 411.0, 312.0, 411.0, 294.0, 352.0, 294.0], 'text': '1080.00', 'label': 15}, {'box': [368.0, 334.0, 413.0, 334.0, 413.0, 315.0, 368.0, 315.0], 'text': '40.00', 'label': 15}, {'box': [368.0, 356.0, 413.0, 356.0, 413.0, 337.0, 368.0, 337.0], 'text': '20.00', 'label': 15}, {'box': [369.0, 378.0, 413.0, 378.0, 413.0, 359.0, 369.0, 359.0], 'text': '20.00', 'label': 15}, {'box': [369.0, 401.0, 414.0, 401.0, 414.0, 381.0, 369.0, 381.0], 'text': '20.00', 'label': 15}, {'box': [371.0, 424.0, 415.0, 424.0, 415.0, 404.0, 371.0, 404.0], 'text': '12.00', 'label': 15}, {'box': [373.0, 448.0, 416.0, 448.0, 416.0, 427.0, 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2434.0, 488.0, 2434.0], 'text': 'Wevalueyouropinion!', 'label': 25}, {'box': [417.0, 2578.0, 1376.0, 2578.0, 1376.0, 2502.0, 417.0, 2502.0], 'text': 'Bethenext$1,000Winner!', 'label': 25}, {'box': [521.0, 2648.0, 1260.0, 2648.0, 1260.0, 2572.0, 521.0, 2572.0], 'text': '3winnerspermonth.', 'label': 25}, {'box': [185.0, 2725.0, 1603.0, 2725.0, 1603.0, 2634.0, 185.0, 2634.0], 'text': \"Completeasurveyabouttoday'svisit:\", 'label': 25}, {'box': [152.0, 2791.0, 437.0, 2791.0, 437.0, 2723.0, 152.0, 2723.0], 'text': 'Call', 'label': 25}, {'box': [531.0, 2785.0, 1578.0, 2785.0, 1578.0, 2701.0, 531.0, 2701.0], 'text': '1.866.214.5750', 'label': 25}, {'box': [188.0, 2863.0, 1580.0, 2863.0, 1580.0, 2785.0, 188.0, 2785.0], 'text': 'Orvisitwww.dollargeneralsurvey.com', 'label': 25}, {'box': [414.0, 3119.0, 1364.0, 3119.0, 1364.0, 3048.0, 414.0, 3048.0], 'text': 'Paracompletarunestudio', 'label': 25}, {'box': [273.0, 3173.0, 1548.0, 3173.0, 1548.0, 3107.0, 273.0, 3107.0], 'text': 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155.0, 62.0], 'text': '09:54PM', 'label': 9}, {'box': [12.0, 66.0, 152.0, 66.0, 152.0, 50.0, 12.0, 50.0], 'text': 'BILLNo:1352RetailInvoice', 'label': 25}, {'box': [12.0, 76.0, 103.0, 76.0, 103.0, 63.0, 12.0, 63.0], 'text': 'TableNo:11/GF', 'label': 25}, {'box': [10.0, 85.0, 67.0, 85.0, 67.0, 73.0, 10.0, 73.0], 'text': 'Cover:1', 'label': 25}, {'box': [11.0, 99.0, 79.0, 99.0, 79.0, 85.0, 11.0, 85.0], 'text': 'USER:ADMIN', 'label': 25}, {'box': [11.0, 123.0, 68.0, 123.0, 68.0, 110.0, 11.0, 110.0], 'text': 'Description', 'label': 12}, {'box': [104.0, 125.0, 122.0, 125.0, 122.0, 110.0, 104.0, 110.0], 'text': 'Qty', 'label': 14}, {'box': [122.0, 124.0, 146.0, 124.0, 146.0, 111.0, 122.0, 111.0], 'text': 'Rate', 'label': 25}, {'box': [159.0, 123.0, 191.0, 123.0, 191.0, 111.0, 159.0, 111.0], 'text': 'Amount', 'label': 16}, {'box': [9.0, 148.0, 68.0, 148.0, 68.0, 134.0, 9.0, 134.0], 'text': 'SoftDrinks', 'label': 11}, {'box': [11.0, 160.0, 62.0, 160.0, 62.0, 147.0, 11.0, 147.0], 'text': 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131.0, 137.0], 'text': '24.00', 'label': 25}, {'box': [176.0, 146.0, 203.0, 146.0, 203.0, 137.0, 176.0, 137.0], 'text': '48.00', 'label': 15}, {'box': [131.0, 159.0, 157.0, 159.0, 157.0, 148.0, 131.0, 148.0], 'text': '93.00', 'label': 25}, {'box': [175.0, 159.0, 202.0, 159.0, 202.0, 148.0, 175.0, 148.0], 'text': '93.00', 'label': 15}, {'box': [130.0, 171.0, 157.0, 171.0, 157.0, 161.0, 130.0, 161.0], 'text': '76.00', 'label': 25}, {'box': [176.0, 171.0, 202.0, 171.0, 202.0, 160.0, 176.0, 160.0], 'text': '76.00', 'label': 15}, {'box': [126.0, 183.0, 157.0, 183.0, 157.0, 173.0, 126.0, 173.0], 'text': '115.00', 'label': 25}, {'box': [171.0, 183.0, 203.0, 183.0, 203.0, 173.0, 171.0, 173.0], 'text': '230.00', 'label': 15}, {'box': [126.0, 196.0, 157.0, 196.0, 157.0, 185.0, 126.0, 185.0], 'text': '118.00', 'label': 25}, {'box': [171.0, 195.0, 203.0, 195.0, 203.0, 185.0, 171.0, 185.0], 'text': '118.00', 'label': 15}, {'box': [126.0, 208.0, 157.0, 208.0, 157.0, 198.0, 126.0, 198.0], 'text': 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1177.0, 648.0, 1129.0, 455.0, 1129.0], 'text': '6.SA-TAY', 'label': 11}, {'box': [498.0, 1243.0, 765.0, 1243.0, 765.0, 1188.0, 498.0, 1188.0], 'text': 'SLICEDCHIX', 'label': 11}, {'box': [396.0, 1281.0, 418.0, 1281.0, 418.0, 1241.0, 396.0, 1241.0], 'text': '1', 'label': 13}, {'box': [391.0, 1339.0, 415.0, 1339.0, 415.0, 1300.0, 391.0, 1300.0], 'text': '1', 'label': 13}, {'box': [443.0, 1300.0, 757.0, 1300.0, 757.0, 1243.0, 443.0, 1243.0], 'text': '40.THAISALAD', 'label': 11}, {'box': [444.0, 1357.0, 727.0, 1357.0, 727.0, 1303.0, 444.0, 1303.0], 'text': '102.PADTHAI', 'label': 11}, {'box': [1172.0, 1034.0, 1267.0, 1034.0, 1267.0, 991.0, 1172.0, 991.0], 'text': '7.95', 'label': 15}, {'box': [1148.0, 1092.0, 1265.0, 1092.0, 1265.0, 1049.0, 1148.0, 1049.0], 'text': '11.95', 'label': 15}, {'box': [1145.0, 1150.0, 1262.0, 1150.0, 1262.0, 1107.0, 1145.0, 1107.0], 'text': '12.95', 'label': 15}, {'box': [1163.0, 1208.0, 1259.0, 1208.0, 1259.0, 1165.0, 1163.0, 1165.0], 'text': '9.95', 'label': 15}, {'box': [1157.0, 1327.0, 1253.0, 1327.0, 1253.0, 1280.0, 1157.0, 1280.0], 'text': '7.95', 'label': 15}, {'box': [1152.0, 1386.0, 1250.0, 1386.0, 1250.0, 1341.0, 1152.0, 1341.0], 'text': '8.95', 'label': 15}, {'box': [477.0, 1418.0, 746.0, 1418.0, 746.0, 1364.0, 477.0, 1364.0], 'text': 'SLICEDPORK', 'label': 11}, {'box': [373.0, 1458.0, 396.0, 1458.0, 396.0, 1417.0, 373.0, 1417.0], 'text': '1', 'label': 13}, {'box': [365.0, 1519.0, 390.0, 1519.0, 390.0, 1477.0, 365.0, 1477.0], 'text': '1', 'label': 13}, {'box': [420.0, 1469.0, 588.0, 1469.0, 588.0, 1419.0, 420.0, 1419.0], 'text': 'SPECIAL', 'label': 11}, {'box': [1149.0, 1509.0, 1246.0, 1509.0, 1246.0, 1462.0, 1149.0, 1462.0], 'text': '1.00', 'label': 15}, {'box': [1121.0, 1572.0, 1241.0, 1572.0, 1241.0, 1522.0, 1121.0, 1522.0], 'text': '10.95', 'label': 15}, {'box': [418.0, 1543.0, 811.0, 1543.0, 811.0, 1480.0, 418.0, 1480.0], 'text': '129.YELLOWCURRY', 'label': 11}, {'box': [450.0, 1601.0, 728.0, 1601.0, 728.0, 1545.0, 450.0, 1545.0], 'text': 'SLICEDCHIX', 'label': 11}, {'box': [345.0, 1642.0, 370.0, 1642.0, 370.0, 1599.0, 345.0, 1599.0], 'text': '1', 'label': 13}, {'box': [392.0, 1666.0, 745.0, 1666.0, 745.0, 1603.0, 392.0, 1603.0], 'text': 'SOFTSHELLCRAB', 'label': 11}, {'box': [1136.0, 1696.0, 1238.0, 1696.0, 1238.0, 1647.0, 1136.0, 1647.0], 'text': '0.00', 'label': 15}, {'box': [432.0, 1731.0, 790.0, 1731.0, 790.0, 1667.0, 432.0, 1667.0], 'text': 'DRUNKENNOODLE', 'label': 11}, {'box': [1111.0, 1760.0, 1236.0, 1760.0, 1236.0, 1709.0, 1111.0, 1709.0], 'text': '18.95', 'label': 15}, {'box': [327.0, 1766.0, 348.0, 1766.0, 348.0, 1720.0, 327.0, 1720.0], 'text': '1', 'label': 13}, {'box': [370.0, 1780.0, 548.0, 1780.0, 548.0, 1725.0, 370.0, 1725.0], 'text': 'SPECIAL', 'label': 11}, {'box': [1100.0, 1827.0, 1232.0, 1827.0, 1232.0, 1772.0, 1100.0, 1772.0], 'text': '58.00', 'label': 15}, {'box': [362.0, 1861.0, 805.0, 1861.0, 805.0, 1788.0, 362.0, 1788.0], 'text': 'JOKIGENREDLABLE', 'label': 11}, {'box': [401.0, 1921.0, 719.0, 1921.0, 719.0, 1856.0, 401.0, 1856.0], 'text': 'SPECIALPREP', 'label': 11}, {'box': [278.0, 2032.0, 299.0, 2032.0, 299.0, 1983.0, 278.0, 1983.0], 'text': '1', 'label': 13}, {'box': [336.0, 1973.0, 472.0, 1973.0, 472.0, 1919.0, 336.0, 1919.0], 'text': 'MANGO', 'label': 11}, {'box': [327.0, 2051.0, 569.0, 2051.0, 569.0, 1985.0, 327.0, 1985.0], 'text': 'CNUTICRM', 'label': 11}, {'box': [1120.0, 2029.0, 1227.0, 2029.0, 1227.0, 1973.0, 1120.0, 1973.0], 'text': '7.95', 'label': 15}, {'box': [1115.0, 2101.0, 1223.0, 2101.0, 1223.0, 2042.0, 1115.0, 2042.0], 'text': '3.00', 'label': 15}, {'box': [1057.0, 2244.0, 1219.0, 2244.0, 1219.0, 2183.0, 1057.0, 2183.0], 'text': '159.55', 'label': 17}, {'box': [1082.0, 2319.0, 1215.0, 2319.0, 1215.0, 2258.0, 1082.0, 2258.0], 'text': '12.92', 'label': 19}, {'box': [883.0, 2392.0, 1208.0, 2392.0, 1208.0, 2318.0, 883.0, 2318.0], 'text': '172.47', 'label': 23}, {'box': [303.0, 2191.0, 518.0, 2191.0, 518.0, 2125.0, 303.0, 2125.0], 'text': 'SUBTOTAL', 'label': 18}, {'box': [297.0, 2250.0, 376.0, 2250.0, 376.0, 2196.0, 297.0, 2196.0], 'text': 'TAX', 'label': 20}, {'box': [183.0, 2320.0, 366.0, 2320.0, 366.0, 2256.0, 183.0, 2256.0], 'text': '10:40PM', 'label': 9}, {'box': [398.0, 2345.0, 644.0, 2345.0, 644.0, 2277.0, 398.0, 2277.0], 'text': 'TOTALDUE', 'label': 24}, {'box': [378.0, 2528.0, 999.0, 2528.0, 999.0, 2418.0, 378.0, 2418.0], 'text': 'THANKYOUFORVISITING', 'label': 25}]}\n", + "{'file_name': 'image_files/Image_19/12/487d17e3a29f795f2d183315aeb759390d96c84c.jpeg', 'height': 657, 'width': 408, 'annotations': [{'box': [22.0, 33.0, 121.0, 33.0, 121.0, 18.0, 22.0, 18.0], 'text': 'SushiYasuda', 'label': 1}, {'box': [23.0, 55.0, 184.0, 55.0, 184.0, 37.0, 23.0, 37.0], 'text': '204East43rdstreet', 'label': 3}, {'box': [22.0, 74.0, 169.0, 74.0, 169.0, 57.0, 22.0, 57.0], 'text': 'NewYorkNY10017', 'label': 3}, {'box': [23.0, 95.0, 135.0, 95.0, 135.0, 76.0, 23.0, 76.0], 'text': '(212)972-1001', 'label': 5}, {'box': [21.0, 135.0, 89.0, 135.0, 89.0, 117.0, 21.0, 117.0], 'text': '06/05/13', 'label': 7}, {'box': [112.0, 134.0, 170.0, 134.0, 170.0, 118.0, 112.0, 118.0], 'text': '1:19PM', 'label': 9}, {'box': [21.0, 154.0, 184.0, 154.0, 184.0, 137.0, 21.0, 137.0], 'text': 'Check3528', 'label': 25}, {'box': [22.0, 174.0, 187.0, 174.0, 187.0, 157.0, 22.0, 157.0], 'text': 'Waiter1MGCust2', 'label': 25}, {'box': [151.0, 194.0, 281.0, 194.0, 281.0, 177.0, 151.0, 177.0], 'text': 'Table7A', 'label': 25}, {'box': [25.0, 273.0, 30.0, 273.0, 30.0, 258.0, 25.0, 258.0], 'text': '1', 'label': 13}, {'box': [24.0, 293.0, 29.0, 293.0, 29.0, 278.0, 24.0, 278.0], 'text': '1', 'label': 13}, {'box': [23.0, 312.0, 29.0, 312.0, 29.0, 297.0, 23.0, 297.0], 'text': '1', 'label': 13}, {'box': [39.0, 273.0, 97.0, 273.0, 97.0, 256.0, 39.0, 256.0], 'text': 'Edamame', 'label': 11}, {'box': [37.0, 293.0, 72.0, 293.0, 72.0, 277.0, 37.0, 277.0], 'text': 'Kimo', 'label': 11}, {'box': [37.0, 313.0, 167.0, 313.0, 167.0, 296.0, 37.0, 296.0], 'text': 'AlaCarteSushi', 'label': 11}, {'box': [175.0, 354.0, 241.0, 354.0, 241.0, 335.0, 175.0, 335.0], 'text': 'Taxable:', 'label': 18}, {'box': [295.0, 274.0, 331.0, 274.0, 331.0, 257.0, 295.0, 257.0], 'text': '9.00', 'label': 15}, {'box': [290.0, 295.0, 331.0, 295.0, 331.0, 277.0, 290.0, 277.0], 'text': '10.50', 'label': 15}, {'box': [279.0, 315.0, 330.0, 315.0, 330.0, 298.0, 279.0, 298.0], 'text': '243.00', 'label': 15}, {'box': [279.0, 355.0, 331.0, 355.0, 331.0, 337.0, 279.0, 337.0], 'text': '262.50', 'label': 17}, {'box': [157.0, 396.0, 239.0, 396.0, 239.0, 376.0, 157.0, 376.0], 'text': 'Sub-total:', 'label': 18}, {'box': [157.0, 416.0, 240.0, 416.0, 240.0, 398.0, 157.0, 398.0], 'text': 'SalesTax:', 'label': 20}, {'box': [280.0, 395.0, 331.0, 395.0, 331.0, 378.0, 280.0, 378.0], 'text': '262.50', 'label': 17}, {'box': [288.0, 416.0, 332.0, 416.0, 332.0, 399.0, 288.0, 399.0], 'text': '23.30', 'label': 19}, {'box': [66.0, 457.0, 227.0, 457.0, 227.0, 437.0, 66.0, 437.0], 'text': 'TotalDue:', 'label': 24}, {'box': [248.0, 459.0, 348.0, 459.0, 348.0, 439.0, 248.0, 439.0], 'text': '285.80', 'label': 23}, {'box': [72.0, 524.0, 324.0, 524.0, 324.0, 500.0, 72.0, 500.0], 'text': 'FollowingthecustominJapan,', 'label': 25}, {'box': [55.0, 545.0, 326.0, 545.0, 326.0, 522.0, 55.0, 522.0], 'text': 'SushiYasuda’sservicestaffare', 'label': 25}, {'box': [48.0, 568.0, 333.0, 568.0, 333.0, 542.0, 48.0, 542.0], 'text': 'fullycompensatedbytheirsalary.', 'label': 25}, {'box': [39.0, 589.0, 359.0, 589.0, 359.0, 563.0, 39.0, 563.0], 'text': 'Thereforegratuitiesarenotaccepted.', 'label': 25}, {'box': [154.0, 629.0, 239.0, 629.0, 239.0, 608.0, 154.0, 608.0], 'text': 'Thankyou.', 'label': 25}, {'box': [210.0, 655.0, 398.0, 655.0, 398.0, 634.0, 210.0, 634.0], 'text': '', 'label': 0}]}\n", + "{'file_name': 'image_files/Image_78/7/25266f92935f86e84824233bc81b53495ba044a6.jpeg', 'height': 657, 'width': 408, 'annotations': [{'box': [23.0, 33.0, 120.0, 33.0, 120.0, 18.0, 23.0, 18.0], 'text': 'SushiYasuda', 'label': 1}, {'box': [24.0, 53.0, 183.0, 53.0, 183.0, 36.0, 24.0, 36.0], 'text': '204East43rdStreet', 'label': 3}, {'box': [24.0, 73.0, 167.0, 73.0, 167.0, 56.0, 24.0, 56.0], 'text': 'NewYorkNY10017', 'label': 3}, {'box': [24.0, 94.0, 133.0, 94.0, 133.0, 78.0, 24.0, 78.0], 'text': '(212)972-1001', 'label': 5}, {'box': [23.0, 134.0, 87.0, 134.0, 87.0, 118.0, 23.0, 118.0], 'text': '06/05/13', 'label': 7}, {'box': [114.0, 134.0, 168.0, 134.0, 168.0, 118.0, 114.0, 118.0], 'text': '1:19PM', 'label': 9}, {'box': [23.0, 155.0, 182.0, 155.0, 182.0, 137.0, 23.0, 137.0], 'text': 'Check3528', 'label': 25}, {'box': [23.0, 173.0, 185.0, 173.0, 185.0, 157.0, 23.0, 157.0], 'text': 'Waiter1MGCust2', 'label': 25}, {'box': [153.0, 193.0, 280.0, 193.0, 280.0, 177.0, 153.0, 177.0], 'text': 'Table7A', 'label': 25}, {'box': [24.0, 272.0, 30.0, 272.0, 30.0, 257.0, 24.0, 257.0], 'text': '1', 'label': 13}, {'box': [23.0, 291.0, 30.0, 291.0, 30.0, 277.0, 23.0, 277.0], 'text': '1', 'label': 13}, {'box': [23.0, 312.0, 30.0, 312.0, 30.0, 297.0, 23.0, 297.0], 'text': '1', 'label': 13}, {'box': [40.0, 272.0, 95.0, 272.0, 95.0, 258.0, 40.0, 258.0], 'text': 'Edamame', 'label': 11}, {'box': [38.0, 292.0, 71.0, 292.0, 71.0, 278.0, 38.0, 278.0], 'text': 'Kimo', 'label': 11}, {'box': [38.0, 312.0, 165.0, 312.0, 165.0, 296.0, 38.0, 296.0], 'text': 'AlaCarteSushi', 'label': 11}, {'box': [296.0, 273.0, 329.0, 273.0, 329.0, 257.0, 296.0, 257.0], 'text': '9.00', 'label': 15}, {'box': [290.0, 292.0, 330.0, 292.0, 330.0, 278.0, 290.0, 278.0], 'text': '10.50', 'label': 15}, {'box': [281.0, 312.0, 329.0, 312.0, 329.0, 298.0, 281.0, 298.0], 'text': '243.00', 'label': 15}, {'box': [176.0, 353.0, 238.0, 353.0, 238.0, 337.0, 176.0, 337.0], 'text': 'Taxable:', 'label': 18}, {'box': [280.0, 353.0, 330.0, 353.0, 330.0, 339.0, 280.0, 339.0], 'text': '262.50', 'label': 17}, {'box': [158.0, 393.0, 238.0, 393.0, 238.0, 377.0, 158.0, 377.0], 'text': 'Sub-total:', 'label': 18}, {'box': [280.0, 395.0, 331.0, 395.0, 331.0, 379.0, 280.0, 379.0], 'text': '262.50', 'label': 17}, {'box': [158.0, 415.0, 238.0, 415.0, 238.0, 399.0, 158.0, 399.0], 'text': 'SalesTax:', 'label': 20}, {'box': [289.0, 416.0, 331.0, 416.0, 331.0, 400.0, 289.0, 400.0], 'text': '23.30', 'label': 19}, {'box': [68.0, 456.0, 226.0, 456.0, 226.0, 438.0, 68.0, 438.0], 'text': 'TotalDue:', 'label': 24}, {'box': [247.0, 457.0, 348.0, 457.0, 348.0, 441.0, 247.0, 441.0], 'text': '285.80', 'label': 23}, {'box': [73.0, 524.0, 323.0, 524.0, 323.0, 502.0, 73.0, 502.0], 'text': 'FollowingthecustominJapan,', 'label': 25}, {'box': [56.0, 543.0, 325.0, 543.0, 325.0, 523.0, 56.0, 523.0], 'text': \"SushiYasuda'sservicestaffare\", 'label': 25}, {'box': [48.0, 567.0, 333.0, 567.0, 333.0, 543.0, 48.0, 543.0], 'text': 'fullycompensatedbytheirsalary.', 'label': 25}, {'box': [39.0, 588.0, 358.0, 588.0, 358.0, 563.0, 39.0, 563.0], 'text': 'Thereforegratuitiesarenotaccepted.', 'label': 25}, {'box': [156.0, 629.0, 237.0, 629.0, 237.0, 609.0, 156.0, 609.0], 'text': 'Thankyou.', 'label': 25}, {'box': [211.0, 654.0, 396.0, 654.0, 396.0, 636.0, 211.0, 636.0], 'text': 'photo:thepricehike', 'label': 25}, {'box': [23.0, 643.0, 381.0, 643.0, 381.0, 461.0, 23.0, 461.0], 'text': '', 'label': 0}]}\n", + "{'file_name': 'image_files/Image_41/17/0ee0c7051d837a0c66ba7f4d5fe45d0dcb5e6d2e.jpeg', 'height': 700, 'width': 534, 'annotations': [{'box': [57.0, 37.0, 161.0, 37.0, 161.0, 19.0, 57.0, 19.0], 'text': 'SushiYasuda', 'label': 1}, {'box': [56.0, 59.0, 229.0, 59.0, 229.0, 40.0, 56.0, 40.0], 'text': '204East43rdStreet', 'label': 3}, {'box': [57.0, 79.0, 212.0, 79.0, 212.0, 62.0, 57.0, 62.0], 'text': 'NewYorkNY10017', 'label': 3}, {'box': [57.0, 102.0, 176.0, 102.0, 176.0, 81.0, 57.0, 81.0], 'text': '(212)972-1001', 'label': 5}, {'box': [56.0, 145.0, 128.0, 145.0, 128.0, 126.0, 56.0, 126.0], 'text': '06/05/13', 'label': 7}, {'box': [151.0, 145.0, 213.0, 145.0, 213.0, 125.0, 151.0, 125.0], 'text': '1:19PM', 'label': 9}, {'box': 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637.0, 1656.0, 364.0, 1656.0], 'text': 'GROCERY', 'label': 11}, {'box': [364.0, 1828.0, 640.0, 1828.0, 640.0, 1753.0, 364.0, 1753.0], 'text': 'GROCERY', 'label': 11}, {'box': [365.0, 1935.0, 640.0, 1935.0, 640.0, 1854.0, 365.0, 1854.0], 'text': 'GROCERY', 'label': 11}, {'box': [366.0, 2031.0, 636.0, 2031.0, 636.0, 1961.0, 366.0, 1961.0], 'text': 'GROCERY', 'label': 11}, {'box': [363.0, 2132.0, 641.0, 2132.0, 641.0, 2060.0, 363.0, 2060.0], 'text': 'GROCERY', 'label': 11}, {'box': [365.0, 2236.0, 562.0, 2236.0, 562.0, 2164.0, 365.0, 2164.0], 'text': 'TOTAL', 'label': 24}, {'box': [365.0, 2344.0, 803.0, 2344.0, 803.0, 2266.0, 365.0, 2266.0], 'text': 'CREDITCARD', 'label': 25}, {'box': [447.0, 2446.0, 1042.0, 2446.0, 1042.0, 2369.0, 447.0, 2369.0], 'text': '*ORDER#0240*', 'label': 25}, {'box': [123.0, 2568.0, 1403.0, 2568.0, 1403.0, 2469.0, 123.0, 2469.0], 'text': 'EMPLOYEE1NO.000140REG02', 'label': 25}, {'box': [1199.0, 1022.0, 1403.0, 1022.0, 1403.0, 952.0, 1199.0, 952.0], 'text': 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416.0, 204.0, 230.0, 204.0], 'text': '206-447-0507', 'label': 5}, {'box': [19.0, 271.0, 80.0, 271.0, 80.0, 242.0, 19.0, 242.0], 'text': 'DATE', 'label': 8}, {'box': [246.0, 277.0, 400.0, 277.0, 400.0, 241.0, 246.0, 241.0], 'text': '08/20/2012', 'label': 7}, {'box': [585.0, 265.0, 637.0, 265.0, 637.0, 235.0, 585.0, 235.0], 'text': 'MON', 'label': 25}, {'box': [17.0, 312.0, 633.0, 312.0, 633.0, 272.0, 17.0, 272.0], 'text': 'OPENCHECK#7', 'label': 25}, {'box': [198.0, 386.0, 432.0, 386.0, 432.0, 352.0, 198.0, 352.0], 'text': '**SEAT#01**', 'label': 25}, {'box': [106.0, 423.0, 212.0, 423.0, 212.0, 392.0, 106.0, 392.0], 'text': 'DIETT1', 'label': 11}, {'box': [103.0, 462.0, 257.0, 462.0, 257.0, 428.0, 103.0, 428.0], 'text': 'CLASSICT1', 'label': 11}, {'box': [105.0, 500.0, 227.0, 500.0, 227.0, 465.0, 105.0, 465.0], 'text': 'TAX1AMT', 'label': 20}, {'box': [105.0, 538.0, 257.0, 538.0, 257.0, 505.0, 105.0, 505.0], 'text': 'TOTAL', 'label': 24}, {'box': [557.0, 416.0, 642.0, 416.0, 642.0, 386.0, 557.0, 386.0], 'text': '$3.00', 'label': 15}, {'box': [558.0, 458.0, 643.0, 458.0, 643.0, 424.0, 558.0, 424.0], 'text': '$8.00', 'label': 15}, {'box': [558.0, 497.0, 645.0, 497.0, 645.0, 462.0, 558.0, 462.0], 'text': '$1.05', 'label': 19}, {'box': [445.0, 537.0, 641.0, 537.0, 641.0, 503.0, 445.0, 503.0], 'text': '$12.05', 'label': 23}, {'box': [225.0, 614.0, 400.0, 614.0, 400.0, 584.0, 225.0, 584.0], 'text': '***ALL***', 'label': 25}, {'box': [95.0, 655.0, 222.0, 655.0, 222.0, 625.0, 95.0, 625.0], 'text': 'SUBTOTAL', 'label': 18}, {'box': [95.0, 697.0, 220.0, 697.0, 220.0, 664.0, 95.0, 664.0], 'text': 'TAX1AMT', 'label': 20}, {'box': [95.0, 741.0, 249.0, 741.0, 249.0, 704.0, 95.0, 704.0], 'text': 'TOTAL', 'label': 24}, {'box': [548.0, 658.0, 651.0, 658.0, 651.0, 625.0, 548.0, 625.0], 'text': '$11.00', 'label': 17}, {'box': [564.0, 700.0, 651.0, 700.0, 651.0, 666.0, 564.0, 666.0], 'text': '$1.05', 'label': 19}, {'box': [448.0, 743.0, 649.0, 743.0, 649.0, 707.0, 448.0, 707.0], 'text': '$12.05', 'label': 23}, {'box': [482.0, 784.0, 554.0, 784.0, 554.0, 749.0, 482.0, 749.0], 'text': 'TIME', 'label': 10}, {'box': [570.0, 785.0, 653.0, 785.0, 653.0, 749.0, 570.0, 749.0], 'text': '12:28', 'label': 9}, {'box': [0.0, 782.0, 368.0, 782.0, 368.0, 743.0, 0.0, 743.0], 'text': 'NO.007373REG01KANDIE', 'label': 25}, {'box': [125.0, 824.0, 497.0, 824.0, 497.0, 787.0, 125.0, 787.0], 'text': 'THANKYOUFORVISITING.', 'label': 25}, {'box': [168.0, 862.0, 464.0, 862.0, 464.0, 827.0, 168.0, 827.0], 'text': 'PLEASECOMEAGAIN!', 'label': 25}]}\n", + "{'file_name': 'image_files/Image_56/2/e9c310f0b1fa229d84c91bfbf71917a02bcc4b2a.jpeg', 'height': 450, 'width': 337, 'annotations': [{'box': [60.0, 72.0, 191.0, 72.0, 191.0, 52.0, 60.0, 52.0], 'text': 'MIAMISCIENCE', 'label': 1}, {'box': [111.0, 80.0, 171.0, 80.0, 171.0, 66.0, 111.0, 66.0], 'text': 'MUSEUM', 'label': 1}, {'box': [92.0, 118.0, 196.0, 118.0, 196.0, 101.0, 92.0, 101.0], 'text': '', 'label': 0}, {'box': [107.0, 129.0, 186.0, 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'CASHTENDERED', 'label': 25}, {'box': [84.0, 279.0, 117.0, 279.0, 117.0, 267.0, 84.0, 267.0], 'text': 'CHANGE', 'label': 25}, {'box': [208.0, 235.0, 237.0, 235.0, 237.0, 224.0, 208.0, 224.0], 'text': '29.90', 'label': 23}, {'box': [214.0, 248.0, 237.0, 248.0, 237.0, 237.0, 214.0, 237.0], 'text': '0.00', 'label': 19}, {'box': [210.0, 262.0, 238.0, 262.0, 238.0, 251.0, 210.0, 251.0], 'text': '50.00', 'label': 25}, {'box': [209.0, 275.0, 238.0, 275.0, 238.0, 264.0, 209.0, 264.0], 'text': '20.10', 'label': 25}, {'box': [47.0, 337.0, 87.0, 337.0, 87.0, 324.0, 47.0, 324.0], 'text': '3:16PM', 'label': 9}, {'box': [101.0, 335.0, 158.0, 335.0, 158.0, 321.0, 101.0, 321.0], 'text': '07/24/2012', 'label': 7}, {'box': [173.0, 332.0, 265.0, 332.0, 265.0, 319.0, 173.0, 319.0], 'text': '002:157235309', 'label': 25}, {'box': [119.0, 363.0, 219.0, 363.0, 219.0, 348.0, 119.0, 348.0], 'text': 'NOTVALID', 'label': 25}, {'box': [98.0, 379.0, 243.0, 379.0, 243.0, 363.0, 98.0, 363.0], 'text': 'FORADMISSION', 'label': 25}, {'box': [97.0, 406.0, 257.0, 406.0, 257.0, 392.0, 97.0, 392.0], 'text': '', 'label': 0}]}\n", + "{'file_name': 'image_files/Image_12/10/7ce1623d6d1aebb79015e1d9b78edf235e611eb4.jpeg', 'height': 450, 'width': 275, 'annotations': [{'box': [89.0, 13.0, 179.0, 13.0, 179.0, 0.0, 89.0, 0.0], 'text': \"jack'sSeafood\", 'label': 1}, {'box': [70.0, 29.0, 192.0, 29.0, 192.0, 14.0, 70.0, 14.0], 'text': '4CStreet,SuiteB', 'label': 3}, {'box': [83.0, 45.0, 184.0, 45.0, 184.0, 30.0, 83.0, 30.0], 'text': 'Eureka,CA95501', 'label': 3}, {'box': [91.0, 61.0, 179.0, 61.0, 179.0, 46.0, 91.0, 46.0], 'text': '(707)273-5273', 'label': 5}, {'box': [9.0, 91.0, 48.0, 91.0, 48.0, 77.0, 9.0, 77.0], 'text': 'Server', 'label': 25}, {'box': [197.0, 88.0, 262.0, 88.0, 262.0, 70.0, 197.0, 70.0], 'text': 'Station:2', 'label': 25}, {'box': [10.0, 122.0, 100.0, 122.0, 100.0, 108.0, 10.0, 108.0], 'text': 'Order#:11054', 'label': 25}, {'box': [10.0, 138.0, 76.0, 138.0, 76.0, 123.0, 10.0, 123.0], 'text': 'Table:T36', 'label': 25}, {'box': [215.0, 119.0, 263.0, 119.0, 263.0, 104.0, 215.0, 104.0], 'text': 'DineIn', 'label': 25}, {'box': [203.0, 135.0, 264.0, 135.0, 264.0, 119.0, 203.0, 119.0], 'text': 'Guests:2', 'label': 25}, {'box': [12.0, 168.0, 16.0, 168.0, 16.0, 156.0, 12.0, 156.0], 'text': '1', 'label': 13}, {'box': [12.0, 183.0, 16.0, 183.0, 16.0, 172.0, 12.0, 172.0], 'text': '1', 'label': 13}, {'box': [11.0, 230.0, 18.0, 230.0, 18.0, 218.0, 11.0, 218.0], 'text': '1', 'label': 13}, {'box': [12.0, 261.0, 18.0, 261.0, 18.0, 248.0, 12.0, 248.0], 'text': '1', 'label': 13}, {'box': [11.0, 292.0, 18.0, 292.0, 18.0, 280.0, 11.0, 280.0], 'text': '1', 'label': 13}, {'box': [23.0, 169.0, 111.0, 169.0, 111.0, 155.0, 23.0, 155.0], 'text': 'APP-SEAREDAHI', 'label': 11}, {'box': [23.0, 184.0, 113.0, 184.0, 113.0, 170.0, 23.0, 170.0], 'text': 'FISHANDCHIPS', 'label': 11}, {'box': [23.0, 198.0, 150.0, 198.0, 150.0, 185.0, 23.0, 185.0], 'text': '**SPICYCOLESLAW**', 'label': 11}, {'box': [23.0, 215.0, 157.0, 215.0, 157.0, 200.0, 23.0, 200.0], 'text': '*CLAMCHOWDER*3.00EA', 'label': 11}, {'box': [24.0, 229.0, 89.0, 229.0, 89.0, 216.0, 24.0, 216.0], 'text': 'FISHTACOS', 'label': 11}, {'box': [24.0, 246.0, 120.0, 246.0, 120.0, 232.0, 24.0, 232.0], 'text': '**HALFHALF**', 'label': 25}, {'box': [24.0, 260.0, 77.0, 260.0, 77.0, 248.0, 24.0, 248.0], 'text': 'Tiramisu', 'label': 11}, {'box': [23.0, 276.0, 143.0, 276.0, 143.0, 260.0, 23.0, 260.0], 'text': 'VIPDiscount(8.00)', 'label': 25}, {'box': [24.0, 293.0, 95.0, 293.0, 95.0, 278.0, 24.0, 278.0], 'text': 'GreatWhite', 'label': 11}, {'box': [230.0, 165.0, 263.0, 165.0, 263.0, 151.0, 230.0, 151.0], 'text': '15.00', 'label': 15}, {'box': [231.0, 180.0, 265.0, 180.0, 265.0, 166.0, 231.0, 166.0], 'text': '18.00', 'label': 15}, {'box': [232.0, 227.0, 265.0, 227.0, 265.0, 213.0, 232.0, 213.0], 'text': '16.00', 'label': 15}, {'box': [237.0, 258.0, 265.0, 258.0, 265.0, 245.0, 237.0, 245.0], 'text': '0.00', 'label': 15}, {'box': [237.0, 290.0, 265.0, 290.0, 265.0, 277.0, 237.0, 277.0], 'text': '5.00', 'label': 15}, {'box': [232.0, 321.0, 267.0, 321.0, 267.0, 307.0, 232.0, 307.0], 'text': '54.00', 'label': 17}, {'box': [239.0, 337.0, 267.0, 337.0, 267.0, 322.0, 239.0, 322.0], 'text': '4.73', 'label': 19}, {'box': [226.0, 370.0, 268.0, 370.0, 268.0, 355.0, 226.0, 355.0], 'text': '$58.73', 'label': 23}, {'box': [11.0, 323.0, 73.0, 323.0, 73.0, 310.0, 11.0, 310.0], 'text': 'SUBTOTAL:', 'label': 18}, {'box': [11.0, 340.0, 36.0, 340.0, 36.0, 326.0, 11.0, 326.0], 'text': 'TAX:', 'label': 20}, {'box': [10.0, 373.0, 49.0, 373.0, 49.0, 358.0, 10.0, 358.0], 'text': 'TOTAL:', 'label': 24}, {'box': [81.0, 403.0, 197.0, 403.0, 197.0, 388.0, 81.0, 388.0], 'text': '>>Ticket#:27<<', 'label': 25}, {'box': [70.0, 422.0, 134.0, 422.0, 134.0, 405.0, 70.0, 405.0], 'text': '10/14/2016', 'label': 7}, {'box': [140.0, 419.0, 206.0, 419.0, 206.0, 404.0, 140.0, 404.0], 'text': '2:56:56PM', 'label': 9}, {'box': [107.0, 449.0, 171.0, 449.0, 171.0, 436.0, 107.0, 436.0], 'text': 'THANKYOU!', 'label': 25}]}\n" + ] + } + ], + "source": [ + "create_kie_wildreceipt_dataset(\n", + " \"/mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/wildreceipt\",\n", + " train_txt=\"/mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/wildreceipt/train.txt\",\n", + " test_txt=\"/mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/wildreceipt/test.txt\",\n", + " class_file=\"/mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/wildreceipt/class_list.txt\",\n", + " out_dir=\"/mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/processed\"\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [], + "source": [ + "def format_txt_data(txt_data):\n", + " out_data = []\n", + " for item in txt_data:\n", + " splitted_items = item.split(\"\\t\")\n", + " if len(splitted_items) == 6:\n", + " box, text, label = splitted_items[:4], splitted_items[4], splitted_items[5]\n", + " else:\n", + " box, text, label = splitted_items[:4], splitted_items[4], \"dummy_label\"\n", + " out_data.append(\n", + " {\n", + " 'box': [int(x) for x in box],\n", + " 'text': text,\n", + " 'label': label\n", + " }\n", + " )\n", + "\n", + " return out_data\n", + "\n", + "def is_in_field(box1, box2, thr=0.7):\n", + " \"\"\"\n", + " Calculates the IOU between two bounding boxes based only on their y-axis intersection.\n", + "\n", + " Parameters:\n", + " box1 (tuple): A tuple in the format (xmin, ymin, xmax, ymax) representing the first bounding box.\n", + " box2 (tuple): A tuple in the format (xmin, ymin, xmax, ymax) representing the second bounding box.\n", + "\n", + " Returns:\n", + " float: The IOU between the two bounding boxes based only on their y-axis intersection.\n", + " \"\"\"\n", + " # Calculate the y-axis intersection between the two boxes\n", + " y_intersection = min(box1[3], box2[3]) - max(box1[1], box2[1])\n", + "\n", + " # If there is no y-axis intersection, the IOU is 0\n", + " if y_intersection <= 0:\n", + " return 0.0\n", + "\n", + " # Calculate the area of the union between the two boxes based only on their y-axis intersection\n", + " y_union = max(box1[3], box2[3]) - min(box1[1], box2[1])\n", + "\n", + " # Calculate the IOU\n", + " iou_y = y_intersection / y_union\n", + "\n", + " # Calculate the intersection along the x-axis\n", + " intersection = max(0, min(box1[2], box2[2]) - max(box1[0], box2[0]))\n", + " \n", + " # Calculate the area of the smaller box\n", + " smaller_box_width = min(box1[2] - box1[0], box2[2] - box2[0])\n", + " smaller_box_area = smaller_box_width * 1.0 # 1.0 for height, can be any value\n", + " \n", + " # Calculate the IoU along the x-axis\n", + " iou_x = intersection / smaller_box_area\n", + " print(f\"iou_y = {iou_y}, iou_x = {iou_x}\")\n", + " if iou_y > thr and iou_x > 0.9:\n", + " return True \n", + " \n", + " return False\n", + "\n", + "\n", + "def check_iou(box1, box2, threshold=0.9):\n", + " area1 = (box1[2] - box1[0]) * (box1[3] - box1[1])\n", + " area2 = (box2[2] - box2[0]) * (box2[3] - box2[1])\n", + " xmin_intersect = max(box1[0], box2[0])\n", + " ymin_intersect = max(box1[1], box2[1])\n", + " xmax_intersect = min(box1[2], box2[2])\n", + " ymax_intersect = min(box1[3], box2[3])\n", + "\n", + "\n", + " if xmax_intersect < xmin_intersect or ymax_intersect < ymin_intersect:\n", + " area_intersect = 0\n", + " else:\n", + " area_intersect = (xmax_intersect - xmin_intersect) * (\n", + " ymax_intersect * ymin_intersect\n", + " )\n", + " # union = area1 + area2 - area_intersect\n", + " iou = area_intersect / area1\n", + " if iou > threshold:\n", + " return True\n", + " return False\n", + "\n", + "def update_label_for_word(word_item, wildreceipt_data, list_labels, threshold=0.75):\n", + " have_label = False\n", + " for wild_item in wildreceipt_data:\n", + " # if is_in_field(word_item['box'], wild_item['box'], thr=0.5):\n", + " # print(wild_item['label'])\n", + " if check_iou(word_item['box'], wild_item['box'], threshold=threshold):\n", + " if wild_item['label'] in list_labels:\n", + " word_item['label'] = wild_item['label']\n", + " have_label = True\n", + " else:\n", + " word_item['label'] = \"Others\"\n", + " have_label = True\n", + " break\n", + "\n", + " if not have_label:\n", + " word_item['label'] = \"Others\"\n", + " return word_item\n", + " \n", + "def dict_to_line(item_dict):\n", + " box = item_dict['box']\n", + " text = item_dict['text']\n", + " label = item_dict['label']\n", + " line = \"\\t\".join([str(x) for x in box])\n", + " line = \"\\t\".join([line, text, label])\n", + " return line\n", + "\n", + "def update_kie_label(wildreceipt_data, ocr_word_result, list_labels=['']):\n", + " # wildreceipt_data = read_txt(ori_txt)\n", + " formated_wildreceipt_data = format_txt_data(wildreceipt_data)\n", + " \n", + " # ocr_word_result = read_txt(ocr_txt)\n", + " formated_ocr_word_result = format_txt_data(ocr_word_result)\n", + " new_ocr_word_result = []\n", + " for word_item in formated_ocr_word_result:\n", + " word_item = update_label_for_word(word_item, formated_wildreceipt_data, list_labels, threshold=0.9)\n", + " new_ocr_word_result.append(word_item)\n", + "\n", + " out_txt_data = [dict_to_line(item_dict) for item_dict in new_ocr_word_result]\n", + " return out_txt_data\n", + "\n", + "def process_update_kie_label(wild_txt, ocr_txt, out_dir, list_labels=[]):\n", + " out_dir = Path(out_dir)\n", + " if not out_dir.exists():\n", + " out_dir.mkdir(parents=True)\n", + "\n", + " ocr_txt_paths = Path(ocr_txt).glob(\"*.txt\")\n", + "\n", + " for ocr_path in ocr_txt_paths:\n", + " ocr_data = read_txt(ocr_path)\n", + " wild_txt_path = Path(wild_txt) / ocr_path.name\n", + " wild_data = read_txt(wild_txt_path)\n", + " updated_ocr_data = update_kie_label(wild_data, ocr_data, list_labels)\n", + " \n", + " out_ocr_path = out_dir / ocr_path.name\n", + " write_txt(out_ocr_path, updated_ocr_data)\n", + " \n" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [], + "source": [ + "process_update_kie_label(\n", + " wild_txt=\"/mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/processed/test\",\n", + " ocr_txt=\"/mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/pseudo_ocr/test\",\n", + " out_dir=\"/mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/v1/test\",\n", + " list_labels=[\n", + " \"Store_name_value\",\n", + " \"Total_value\",\n", + " \"Date_value\",\n", + " \"Total_key\"\n", + " ]\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [], + "source": [ + "process_update_kie_label(\n", + " wild_txt=\"/mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/processed/train\",\n", + " ocr_txt=\"/mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/pseudo_ocr/train\",\n", + " out_dir=\"/mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/v1/train\",\n", + " list_labels=[\n", + " \"Store_name_value\",\n", + " \"Total_value\",\n", + " \"Date_value\",\n", + " \"Total_key\"\n", + " ]\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import shutil\n", + "from pathlib import Path\n", + "\n", + "def split_folder_into_batches(data_dir, out_dir, batch_size):\n", + " # create output directory if it doesn't exist\n", + " if not os.path.exists(out_dir):\n", + " os.makedirs(out_dir)\n", + "\n", + " # get list of all .jpg files in data_dir\n", + " jpg_files = [filename for filename in os.listdir(data_dir) if not filename.endswith('.txt')]\n", + "\n", + " # split jpg_files into batches\n", + " num_batches = (len(jpg_files) + batch_size - 1) // batch_size # round up to nearest integer\n", + " batches = [jpg_files[i*batch_size:(i+1)*batch_size] for i in range(num_batches)]\n", + "\n", + " # copy each batch of .txt and .jpg files to out_dir\n", + " for i, batch in enumerate(batches):\n", + " batch_dir = os.path.join(out_dir, f'batch_{i+1}')\n", + " if not os.path.exists(batch_dir):\n", + " os.makedirs(batch_dir)\n", + " for jpg_file in batch:\n", + " txt_file = str(Path(jpg_file).with_suffix(\".txt\"))\n", + " shutil.copy2(os.path.join(data_dir, txt_file), batch_dir)\n", + " shutil.copy2(os.path.join(data_dir, jpg_file), batch_dir)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "ename": "FileExistsError", + "evalue": "[Errno 17] File exists: '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/re_labeling/batches/batch_1'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mFileExistsError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[4], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m split_folder_into_batches(\n\u001b[1;32m 2\u001b[0m data_dir\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39m/mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/re_labeling/train_and_test\u001b[39;49m\u001b[39m\"\u001b[39;49m,\n\u001b[1;32m 3\u001b[0m out_dir\u001b[39m=\u001b[39;49m\u001b[39m\"\u001b[39;49m\u001b[39m/mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/re_labeling/batches\u001b[39;49m\u001b[39m\"\u001b[39;49m,\n\u001b[1;32m 4\u001b[0m batch_size\u001b[39m=\u001b[39;49m\u001b[39m500\u001b[39;49m\n\u001b[1;32m 5\u001b[0m )\n", + "Cell \u001b[0;32mIn[3], line 20\u001b[0m, in \u001b[0;36msplit_folder_into_batches\u001b[0;34m(data_dir, out_dir, batch_size)\u001b[0m\n\u001b[1;32m 18\u001b[0m \u001b[39mfor\u001b[39;00m i, batch \u001b[39min\u001b[39;00m \u001b[39menumerate\u001b[39m(batches):\n\u001b[1;32m 19\u001b[0m batch_dir \u001b[39m=\u001b[39m os\u001b[39m.\u001b[39mpath\u001b[39m.\u001b[39mjoin(out_dir, \u001b[39mf\u001b[39m\u001b[39m'\u001b[39m\u001b[39mbatch_\u001b[39m\u001b[39m{\u001b[39;00mi\u001b[39m+\u001b[39m\u001b[39m1\u001b[39m\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m)\n\u001b[0;32m---> 20\u001b[0m os\u001b[39m.\u001b[39;49mmakedirs(batch_dir)\n\u001b[1;32m 21\u001b[0m \u001b[39mfor\u001b[39;00m jpg_file \u001b[39min\u001b[39;00m batch:\n\u001b[1;32m 22\u001b[0m txt_file \u001b[39m=\u001b[39m \u001b[39mstr\u001b[39m(Path(jpg_file)\u001b[39m.\u001b[39mwith_suffix(\u001b[39m\"\u001b[39m\u001b[39m.txt\u001b[39m\u001b[39m\"\u001b[39m))\n", + "File \u001b[0;32m~/miniconda3/envs/py38_hoanglv/lib/python3.8/os.py:223\u001b[0m, in \u001b[0;36mmakedirs\u001b[0;34m(name, mode, exist_ok)\u001b[0m\n\u001b[1;32m 221\u001b[0m \u001b[39mreturn\u001b[39;00m\n\u001b[1;32m 222\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m--> 223\u001b[0m mkdir(name, mode)\n\u001b[1;32m 224\u001b[0m \u001b[39mexcept\u001b[39;00m \u001b[39mOSError\u001b[39;00m:\n\u001b[1;32m 225\u001b[0m \u001b[39m# Cannot rely on checking for EEXIST, since the operating system\u001b[39;00m\n\u001b[1;32m 226\u001b[0m \u001b[39m# could give priority to other errors like EACCES or EROFS\u001b[39;00m\n\u001b[1;32m 227\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m exist_ok \u001b[39mor\u001b[39;00m \u001b[39mnot\u001b[39;00m path\u001b[39m.\u001b[39misdir(name):\n", + "\u001b[0;31mFileExistsError\u001b[0m: [Errno 17] File exists: '/mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/re_labeling/batches/batch_1'" + ] + } + ], + "source": [ + "split_folder_into_batches(\n", + " data_dir=\"/mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/re_labeling/train_and_test\",\n", + " out_dir=\"/mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/re_labeling/batches\",\n", + " batch_size=500\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "py38_hoanglv", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.8.13" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/cope2n-ai-fi/modules/sdsvkie/requirements.txt b/cope2n-ai-fi/modules/sdsvkie/requirements.txt new file mode 100755 index 0000000..7042116 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/requirements.txt @@ -0,0 +1,15 @@ +protobuf>=3.19.6,<4 +opencv-python>=4.4.0 +torch>=1.4 +torchvision +transformers>=4.25.1 +datasets>=2.5.2 +Pillow==9.5.0 +wandb +easydict==1.10 +terminaltables==3.1.10 +tqdm +rapidfuzz==2.13.7 +PyMuPDF==1.20.2 +sentencepiece +underthesea \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/common/2023-04-20_0101803564_0300741922_1C23TYY_714.pdf b/cope2n-ai-fi/modules/sdsvkie/scripts/common/2023-04-20_0101803564_0300741922_1C23TYY_714.pdf new file mode 100755 index 0000000..969cfac --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/common/2023-04-20_0101803564_0300741922_1C23TYY_714.pdf @@ -0,0 +1,49 @@ +%PDF-1.3 +% ReportLab Generated PDF document http://www.reportlab.com +1 0 obj +<< +/F1 2 0 R +>> +endobj +2 0 obj +<< +/BaseFont /Helvetica /Encoding /WinAnsiEncoding /Name /F1 /Subtype /Type1 /Type /Font +>> +endobj +3 0 obj +<< +/PageMode /UseNone /Pages 5 0 R /Type /Catalog +>> +endobj +4 0 obj +<< +/Author (anonymous) /CreationDate (D:20230522134603-07'00') /Creator (ReportLab PDF Library - www.reportlab.com) /Keywords () /ModDate (D:20230522134603-07'00') /Producer (ReportLab PDF Library - www.reportlab.com) + /Subject (unspecified) /Title (untitled) /Trapped /False +>> +endobj +5 0 obj +<< +/Count 0 /Kids [ ] /Type /Pages +>> +endobj +xref +0 6 +0000000000 65535 f +0000000073 00000 n +0000000104 00000 n +0000000211 00000 n +0000000279 00000 n +0000000575 00000 n +trailer +<< +/ID +[<4d2762f6f45f96a78f66af9b0251b167><4d2762f6f45f96a78f66af9b0251b167>] +% ReportLab generated PDF document -- digest (http://www.reportlab.com) + +/Info 4 0 R +/Root 3 0 R +/Size 6 +>> +startxref +629 +%%EOF diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/common/build_batch_2.py b/cope2n-ai-fi/modules/sdsvkie/scripts/common/build_batch_2.py new file mode 100755 index 0000000..ace5128 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/common/build_batch_2.py @@ -0,0 +1,10 @@ +import os +from pathlib import Path +import shutil +data_dir = "/mnt/hdd2T/AICR/Projects/2023/FI_Invoices/Data" + +data_dir = Path(data_dir) + +for path in data_dir.glob("*/*.pdf"): + if path.with_suffix(".xml").exists(): + shutil.copy(str(path), "/mnt/ssd1T/hoanglv/Projects/KIE/DATA/SS_Invoice/multi_page_vat/batch_2") \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/common/check_duplicate_vat.py b/cope2n-ai-fi/modules/sdsvkie/scripts/common/check_duplicate_vat.py new file mode 100755 index 0000000..8ffb9f2 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/common/check_duplicate_vat.py @@ -0,0 +1,117 @@ + +from pathlib import Path +import shutil +import json + +def write_txt(txt, data, mode="w"): + with open(txt, mode, encoding="utf8") as f: + for line in data: + f.write(line + "\n") + + +def read_txt(txt): + with open(txt, "r", encoding="utf8") as f: + data = [line.strip() for line in f] + return data + +def get_no(items): + no = "xxxx" + for item in items: + if "No_value" in item: + tmp = item.split("\t") + no = tmp[-2] + + return no + +def write_json(json_path, data): + with open(json_path, "w", encoding="utf8") as f: + json.dump(data, f, ensure_ascii=False, sort_keys=True) + + +def read_json(json_path): + with open(json_path, "r", encoding="utf8") as f: + data = json.load(f) + return data + + +def check(txt_dir): + log_dict = {} + txt_dir = Path(txt_dir) + txt_paths = txt_dir.rglob("*.txt") + for txt_path in txt_paths: + items = read_txt(str(txt_path)) + no_doc = get_no(items) + if no_doc not in log_dict: + log_dict[no_doc] = [str(txt_path.with_suffix(".jpg"))] + else: + log_dict[no_doc].append(str(txt_path.with_suffix(".jpg"))) + + not_dups = [] + for no, paths in log_dict.items(): + if len(paths) == 1: + not_dups.append(no) + # if "xxxx" in log_dict.keys(): + # log_dict.pop("xxxx") + for _ in not_dups: + log_dict.pop(_) + + print(log_dict.keys()) + return log_dict + +# print(check("/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/train/SS_Invoice")) + + +def get_leak_test(data_dir): + test_keys = [] + data_dir = Path(data_dir) + test_paths = data_dir.rglob("test_*") + # print(list(test_paths)) + for path in test_paths: + img_name = path.stem + img_name = img_name.replace("test_","") + test_keys.append(img_name) + + + # write_txt("leak.txt", test_keys) + return test_keys + + +def create_new_test(ori_dir, out_dir, test_keys): + ori_dir = Path(ori_dir) + out_dir = Path(out_dir) + if not out_dir.exists(): + out_dir.mkdir(parents=True, exist_ok=True) + + img_paths = ori_dir.rglob("*.jpg") + for img_path in img_paths: + img_key = img_path.stem + if img_key in test_keys: + continue + txt_path = img_path.with_suffix(".txt") + shutil.copy(str(img_path), str(out_dir)) + shutil.copy(str(txt_path), str(out_dir)) + +def create_new_e2e_test(ori_json, out_json, test_keys): + ori_data = read_json(ori_json) + out_dict = {} + for k, v in ori_data.items(): + if k in test_keys: + continue + out_dict[k] = v + + write_json(out_json, out_dict) + + +test_keys = get_leak_test("/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/EXCESS") +# create_new_test( +# ori_dir="/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/test_ss", +# out_dir="/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/test_ss_rm_leak", +# test_keys=test_keys +# ) + +create_new_e2e_test( + ori_json="/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/test_ss_e2e.json", + out_json="/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/test_ss_e2e_rm_leak.json", + test_keys=test_keys +) + diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/common/clean_json.py b/cope2n-ai-fi/modules/sdsvkie/scripts/common/clean_json.py new file mode 100755 index 0000000..6e8b29c --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/common/clean_json.py @@ -0,0 +1,39 @@ +import argparse +from pathlib import Path +from tqdm import tqdm +from sdsvkie.utils.io_file import read_json, write_json + + +def clean_json(in_json, out_json, pdf_dir): + data_src = read_json(in_json) + + pdf_dir = Path(pdf_dir) + pdf_paths = pdf_dir.glob("*.pdf") + pdf_keys = set([pdf_path.stem for pdf_path in pdf_paths]) + + data_tgt = {} + for src_pdf_key in data_src.keys(): + if src_pdf_key in pdf_keys: + data_tgt[src_pdf_key] = data_src[src_pdf_key] + + write_json(out_json, data_tgt, sort_keys=False) + + + + + + + + +if __name__ == "__main__": + parser = argparse.ArgumentParser(prog="Rename labels") + parser.add_argument("--input", type=str, required=True, help="dataset directory") + parser.add_argument("--out", type=str, required=False, help="output") + parser.add_argument("--dir", type=str, required=True, help="document type: receipt / invoice") + + args = parser.parse_args() + clean_json( + in_json=args.input, + out_json=args.out, + pdf_dir=args.dir + ) diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/common/clean_multipage_data.py b/cope2n-ai-fi/modules/sdsvkie/scripts/common/clean_multipage_data.py new file mode 100755 index 0000000..ca437ec --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/common/clean_multipage_data.py @@ -0,0 +1,49 @@ +import os + +import json +from pathlib import Path + +def read_json(json_path): + with open(json_path, 'r') as f: + data = json.load(f) + return data + +def write_json(json_path, data): + with open(json_path, 'w') as f: + json.dump(data, f, ensure_ascii=False) + + +def clean_json(json_in, json_out, valid_names): + out_data = {} + data = read_json(json_in) + for name_key, items in data.items(): + if name_key in valid_names: + out_data[name_key] = items + + write_json(json_out, out_data) + +# DIRNAMES = ['SL_HCM', 'SL_HN_batch_1', 'SL_HN_batch_2', 'Invoices_SAVINA'] +# ROOT_DIR = "/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/PDF/multi_page" + +DIRNAMES = ['test_sbt_v2'] +ROOT_DIR = "/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed" +for dirname in DIRNAMES: + json_path = "/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed/test_end2end/sbt_validation_e2e.json" + json_out_path = "/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed/test_end2end/sbt_validation_e2e_v2.json" + valid_names = [p.stem for p in (Path(ROOT_DIR) / dirname).glob("*")] + print(valid_names) + clean_json(json_path, json_out_path, valid_names) + + +# def combine_json(json_paths, json_out): +# datas = [read_json(json_path) for json_path in json_paths] +# out_data = {} +# for data in datas: +# out_data.update(data) +# write_json(json_out, out_data) + + +# json_paths = [Path(ROOT_DIR) / (dirname + "_out.json") for dirname in DIRNAMES] +# json_out = ROOT_DIR + "/test_e2e_multi_pages.json" +# combine_json(json_paths, json_out) + diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/common/copy_img.py b/cope2n-ai-fi/modules/sdsvkie/scripts/common/copy_img.py new file mode 100755 index 0000000..998add2 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/common/copy_img.py @@ -0,0 +1,23 @@ +import os +import shutil +import glob +from pathlib import Path + + +if __name__ == "__main__": + src_dir = "/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/train/SL_HCM_batch_2_multi_pages" + tgt_dir = "/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/intermediate/key_information_extraction/" + num_files = 100 + + files = glob.glob(os.path.join(src_dir, "*.jpg")) + count = 0 + for file in files: + src_path = os.path.join(src_dir, file) + tgt_path = os.path.join(tgt_dir, file) + if os.path.isfile(src_path): + shutil.copy(src_path, tgt_path) + count += 1 + if count == num_files: + break + + print(f"Copied {count} files from {src_dir} to {tgt_dir}") \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/common/create_train_test_data.py b/cope2n-ai-fi/modules/sdsvkie/scripts/common/create_train_test_data.py new file mode 100755 index 0000000..77b8798 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/common/create_train_test_data.py @@ -0,0 +1,25 @@ +import os +import shutil +from pathlib import Path + + +SRC_DIR = "/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed/train/sbt/batch_1" +TEST_DIR = "/mnt/ssd1T/tuanlv/06.KVUCombineStage/datasets/invoices-receipts/SS_invoices/SBT/validation_data/images" +OUT_DIR = "/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed/test_sbt" + +# Get a list of all the files in the test directory +test_files = [Path(f).name for f in os.listdir(TEST_DIR) if ".txt" not in f] + +# Create the output directory if it doesn't exist +os.makedirs(OUT_DIR, exist_ok=True) + +# Move the matching files from the source directory to the output directory +for filename in os.listdir(SRC_DIR): + if Path(filename).name in test_files: + src_path = os.path.join(SRC_DIR, filename) + # out_path = os.path.join(OUT_DIR, filename) + shutil.move(src_path, OUT_DIR) + + #move .txt + src_txt_path = Path(os.path.join(SRC_DIR, filename)).with_suffix(".txt") + shutil.move(str(src_txt_path), OUT_DIR) \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/common/extract_xml.py b/cope2n-ai-fi/modules/sdsvkie/scripts/common/extract_xml.py new file mode 100755 index 0000000..1c3f8bb --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/common/extract_xml.py @@ -0,0 +1,314 @@ +import shutil +import xml.etree.ElementTree as ET +from datetime import datetime +# from sdsvkie.utils.io_file import read_json, write_json +import json + +import csv +import ast +def get_xml_from_csv(csv_file): + data = {} + with open(csv_file, 'r') as file: + csv_reader = csv.DictReader(file) + for row in csv_reader: + # print(row) + pdf_path = row['file_path'] + pdf_key = Path(pdf_path).stem + xml_paths = ast.literal_eval(row['xml_path']) + data[pdf_key] = xml_paths + + return data + +def get_xml_from_dirs(dir_path, pdf_keys): + dir_path = Path(dir_path) + xml_paths = dir_path.rglob("*.xml") + xml_paths = [str(path) for path in xml_paths] + xml_infos = {} + + for pdf_key in pdf_keys: + xml_infos[pdf_key] = xml_paths + return xml_infos + + +def write_json(json_path, data, sort_keys=True): + with open(json_path, "w", encoding="utf8") as f: + json.dump(data, f, ensure_ascii=False, sort_keys=sort_keys) + + +def read_json(json_path): + with open(json_path, "r", encoding="utf8") as f: + data = json.load(f) + return data + + +from pathlib import Path +import tqdm +import logging +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) + +def convert_date(date_str: str, ori_pattern: str = '%Y-%m-%d', tgt_pattern: str = '%d/%m/%Y'): + date_obj = datetime.strptime(date_str, ori_pattern) + + # convert back to string in DD-MM-YY format + new_date_str = date_obj.strftime(tgt_pattern) + return new_date_str + +def extract(xml_in, field_mapping): + + + with open(xml_in, "r") as f: + xml_string = f.read() + # parse the XML string + root = ET.fromstring(xml_string) + + # extract the SHDon and NLap elements + output = {} + for key in field_mapping: + pattern = f".//{field_mapping[key]}" + value = root.find(pattern) + value = "" if value is None else value.text + if key == "date_value" and value != "": + value = convert_date(value) + + if key in ["tax_amount_value", "total_value"] and value != "": + value = str(int(float(value))) + + + output[key] = value + return output + +field_mapping = { + "no_value": "SHDon", + "form_value": "KHMSHDon", + "serial_value": "XXXXXXX", + "date_value": "NLap", # 2023-06-05 -> YY-MM-DD + "seller_company_name_value": "NBan/Ten", + "seller_address_value": "NBan/DChi", + "seller_tel_value": "XXXXXXXXX", + "seller_tax_code_value": "NBan/MST", + "buyer_personal_name_value": "NMua/HVTNMHang", + "buyer_company_name_value": "NMua/Ten", + "buyer_address_value": "NMua/DChi", + "buyer_tax_code_value": "NMua/MST", + "buyer_tel_value": "NMua/SDT", + "tax_amount_value": "TThue", + "total_value": "TgTTTBSo", + "total_in_words_value": "TgTTTBChu" + } + +## fields need care: serial_value, seller_tel_value, buyer_tel_value + +def get_xml_list_info(xml_dir): + xml_dir = Path(xml_dir) + xml_files = xml_dir.glob("*/*.xml") + xml_info = {} + for xml_file in xml_files: + pdf_key = xml_file.stem + xml_info[pdf_key] = str(xml_file) + return xml_info + +def process(json_in, json_out, xml_dir): + assert Path(json_in).exists() == True + assert Path(xml_dir).exists() == True + data_in = read_json(json_in) + data_out = {} + if data_in is None or not data_in: + logger.error("empty file") + return + + xml_info = get_xml_list_info(xml_dir) + for pdf_key in tqdm.tqdm(data_in.keys()): + + xml_path = xml_info[pdf_key] if pdf_key in xml_info else None + if xml_path is None: + continue + else: + output = extract(xml_path, field_mapping) + + data_out[pdf_key] = output + + write_json(json_out, data_out, sort_keys=False) + + +def get_xml_list_info_v2(xml_dir): + xml_dir = Path(xml_dir) + xml_files = xml_dir.glob("*/*.xml") + + xml_info = {} + for xml_file in xml_files: + pdf_key = xml_file.stem + + if pdf_key in xml_info: + xml_info[pdf_key].append(str(xml_file)) + else: + xml_info[pdf_key] = [str(xml_file)] + + return xml_info + +def extract_v2(xml_paths, preds, field_mapping, pdf_key=None): + + + xml_path = None + if len(xml_paths) == 1: + xml_path = xml_paths[0] + else: + # find best xml + for xml_in in xml_paths: + try: + with open(xml_in, "r", encoding='utf8') as f: + xml_string = f.read() + root = ET.fromstring(xml_string, parser = ET.XMLParser(encoding = 'iso-8859-5')) + except Exception as err: + print("Error exception (check) ", err, xml_in) + continue + + key_checks = ["no_value"] + is_exists_xml = False + for key_check in key_checks: + pattern = f".//{field_mapping[key_check]}" + value = root.find(pattern) + value = "" if value is None else value.text + + if value == preds[key_check]: + is_exists_xml = True + if is_exists_xml: + xml_path = xml_in + if xml_path is None: + print("Not found best xml for ",pdf_key, xml_paths) + return None, None + + # + try: + with open(xml_path, "r") as f: + xml_string = f.read() + # parse the XML string + root = ET.fromstring(xml_string) + except Exception as err: + print("Error exception: ", err, xml_path) + return None, None + # extract the SHDon and NLap elements + output = {} + for key in field_mapping: + pattern = f".//{field_mapping[key]}" + value = root.find(pattern) + value = "" if value is None else value.text + if key == "date_value" and value != "": + value = convert_date(value) + if key in ["tax_amount_value", "total_value"] and value != "": + value = str(int(float(value))) + + output[key] = value + + return output, xml_path + +def process_v2(json_in, json_out, csv_file, xml_dir, xml_out_dir, pdf_xml_json): + assert Path(json_in).exists() == True + assert Path(xml_dir).exists() == True + # make dir + if not Path(xml_out_dir).exists(): + Path(xml_out_dir).mkdir(parents=True, exist_ok=True) + + data_in = read_json(json_in) + data_out = {} + if data_in is None or not data_in: + logger.error("empty file") + return + + # xml_info = get_xml_list_info_v2(xml_dir) + # xml_info = get_xml_from_csv(csv_file=csv_file) + xml_info = get_xml_from_dirs(dir_path=csv_file, pdf_keys=list(data_in.keys())) + print("Num xml: ", len(xml_info)) + succes = 0 + pdf_xml_info = {} + set_xml_paths = set() + for pdf_key in tqdm.tqdm(data_in.keys()): + + xml_paths = xml_info[pdf_key] if pdf_key in xml_info else None + # print(xml_paths) + preds = data_in[pdf_key] + if xml_paths is None or len(xml_paths) == 0: + print("Not exist xml because xml_paths is None or len xml_paths = 0", pdf_key) + continue + else: + output, xml_path = extract_v2(xml_paths, preds, field_mapping, pdf_key=pdf_key) + + if output is not None: + pdf_xml_info[pdf_key] = xml_path + shutil.copy(xml_path, xml_out_dir) + # if Path(xml_path).stem in set_xml_paths: + # print(pdf_key, xml_path) + set_xml_paths.add(Path(xml_path).stem) + succes += 1 + data_out[pdf_key] = output + print("Succes: ", succes) + print(len(set_xml_paths)) + write_json(pdf_xml_json, pdf_xml_info, sort_keys=False) + write_json(json_out, data_out, sort_keys=False) + + +def combine_xml(json_src, json_refer): + data_src = read_json(json_src) + data_refer = read_json(json_refer) + + for pdf_key in data_src.keys(): + for field_key in data_src[pdf_key]: + if data_src[pdf_key][field_key] == "": + data_src[pdf_key][field_key] = data_refer[pdf_key][field_key] + + write_json(json_src, data=data_src, sort_keys=False) + + + +def create_data_from_json(in_dir, out_dir, json_path): + in_dir = Path(in_dir) + out_dir = Path(out_dir) + + if not out_dir.exists(): + out_dir.mkdir(parents=True, exist_ok=True) + + data = read_json(json_path) + + for pdf_key in data.keys(): + pdf_path = in_dir / (pdf_key + ".pdf") + shutil.copy(str(pdf_path), str(out_dir)) + +if __name__ == "__main__": + + + # json_in = "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/Invoice_v2_multi_page.json" + # json_out = "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/Invoice_v2_multi_page_from_xml.json" + # xml_dir = "/mnt/hdd2T/AICR/Projects/2023/FI_Invoices/Test" + # process(json_in=json_in, json_out=json_out, xml_dir=xml_dir) + + # json_in = "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/Invoice_v2_multi_page_from_xml.json" + # json_refer = "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/Invoice_v2_multi_page.json" + # json_in = "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/Invoice_v2_one_page_e2e_from_xml.json" + # json_refer = "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/Invoice_v2_one_page_e2e.json" + + # combine_xml(json_src=json_in, json_refer=json_refer) + + ## One page + # json_in = "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/Invoice_v2_one_page_e2e.json" + # json_out = "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/Invoice_v2_one_page_e2e_from_xml.json" + ## Multi page + json_in = "/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/PV2/Invoice_v1_multi_page.json" + json_out = "/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/PV2/Invoice_v1_multi_page_from_xml.json" + + # csv_file = "/mnt/ssd1T/tuanlv/02.KeyValueUnderstanding/inferences/e2e_outputs/FI_June_data.csv" + csv_file = "/mnt/hdd2T/AICR/Projects/2023/FI_Invoices/Data" + pdf_xml_json = "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/Invoice_v1_multi_page_metadata.json" + + xml_dir = "/mnt/hdd2T/AICR/Projects/2023/FI_Invoices/Test" + xml_out_dir = "/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/Invoice_v1_multi_page_xml" + + process_v2(json_in=json_in, json_out=json_out, csv_file=csv_file, xml_dir=xml_dir, xml_out_dir=xml_out_dir, pdf_xml_json=pdf_xml_json) + + # in_dir = "/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/Invoice_v2_multi_page" + # out_dir = "/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/Invoice_v2_multi_page_clean" + # json_path = "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/Invoice_v2_multi_page_from_xml.json" + # in_dir = "/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/Invoice_v2_one_page" + # out_dir = "/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/Invoice_v2_one_page_clean" + # json_path = "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/Invoice_v2_one_page_e2e_from_xml.json" + + # create_data_from_json(in_dir, out_dir, json_path) \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/common/format_json.py b/cope2n-ai-fi/modules/sdsvkie/scripts/common/format_json.py new file mode 100755 index 0000000..b4c40b9 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/common/format_json.py @@ -0,0 +1,42 @@ +import json + + + +json_path = "/mnt/ssd1T/hoanglv/Projects/KIE/DATA/SS_Invoice/multi_page_vat/SL_HCM.json" +with open(json_path, 'r', encoding='utf8') as f: + data = json.load(f) +print(data[list(data.keys())[0]].keys()) + +keys = [ + 'serial_value', + 'no_value', + 'form_value', + 'date', + + 'seller_company_name_value', + 'seller_address_value', + 'seller_mobile_value', + 'seller_tax_code_value', + + 'buyer_name_value', + 'buyer_company_name_value', + 'buyer_address_value', + 'buyer_mobile_value', + 'buyer_tax_code_value', + + 'VAT_amount_value', + 'total_in_words_value', + 'total_value' +] +new_data = {} +for file_name, items in data.items(): + + new_items = {} + for k in keys: + new_items[k] = items[k] + new_data[file_name] = new_items + + +with open(json_path, 'w', encoding='utf8') as f: + json.dump(new_data, f, ensure_ascii=False) + \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/common/get_more_data.py b/cope2n-ai-fi/modules/sdsvkie/scripts/common/get_more_data.py new file mode 100755 index 0000000..fb21455 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/common/get_more_data.py @@ -0,0 +1,31 @@ +import os +import shutil + + +from pathlib import Path + +folder1 = "/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/PV2/Invoice_v2_multi_page" +folder2 = "/mnt/hdd2T/AICR/Projects/2023/FI_Invoices/Invoice_v2_multi_page" + +out_dir = "/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/PV2/Invoice_v2_multi_page_2" +out_dir = Path(out_dir) +if not out_dir.exists(): + out_dir.mkdir(parents=True, exist_ok=True) + +# Get list of files in both folders +files1 = [f for f in os.listdir(folder1) if os.path.isfile(os.path.join(folder1, f))] +files2 = [f for f in os.listdir(folder2) if os.path.isfile(os.path.join(folder2, f))] + +# Get list of file names in both folders +names1 = [os.path.splitext(f)[0] for f in files1] +names2 = [os.path.splitext(f)[0] for f in files2] + +# Find duplicates by comparing names +duplicates = set(names1) ^ set(names2) +print(len(duplicates)) +# Print duplicate file names +for d in duplicates: + print(f"Duplicate file name found: {d}") + pdf_path = Path(folder2) / (d+".pdf") + shutil.copy(str(pdf_path), str(out_dir)) + diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/common/leak.txt b/cope2n-ai-fi/modules/sdsvkie/scripts/common/leak.txt new file mode 100755 index 0000000..a2bfa93 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/common/leak.txt @@ -0,0 +1,106 @@ +200 +Invoice_ho_1007_000 +210 +invoice_126 +inv_SDV_016 +invoice_108 +invoice_215 +invoice_135 +inv_SDV_004 +292 +164 +242 +inv_SDV_240 +207 +invoice_0525_000 +invoice_1279_000 +306 +d2.sc_1261_000 +invoice_90 +304 +s1.sc_1258_000 +ce_1h_0967_000 +invoice_1392_000 +193 +invoice_109 +281 +354 +invoice_1059_000 +es_10_1043_000 +257 +invoice_65 +invoice_1252_006 +331 +scan__1319_000 +230 +20210_1314_000 +328 +o1_aa_1093_000 +342 +invoice_149 +invoice_1304_000 +c2_em_0081_000 +Invoice_En_1074_000 +invoice_89 +Invoice_Sh_0712_000 +invoice_202 +hotel_0209_000 +invoice_0872_000 +invoice_72 +InvoiceofP_0648_000 +invoice_133 +C1_Invoice_0968_000 +invoice_0803_000 +invoice_50 +invoice_208 +253 +inv_SDV_215 +360 +invoice_1393_000 +scan__0953_000 +invoice_22 +O1_Invoice_1348_000 +inv_SDV_231 +252 +273 +156 +330 +invoice_0457_001 +invoice_0180_001 +invoice_182 +326 +14 +301 +334 +01gtk_0199_000 +343 +Invoice201_0930_000 +invoice_1 +344 +inv_SDV_021 +invoice_170 +E2.Invoice_0561_000 +Invoice_Sh_0262_000 +1.1Invoice_1431_000 +invoice_0112_000 +invoice_195 +314 +2021._0035_000 +invoice_0013_000 +invoice_1204_000 +2021._0868_000 +scan__0520_000 +255 +invoice_200 +C3_Invoice_1359_000 +invoice_49 +invoice_1095_000 +hq_20_0003_000 +invoice_180 +invoice_184 +340 +invoice_0447_000 +invoice_6 +invoice_190 +invoice_105 +invoice_0673_000 diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/common/remove_imgs.py b/cope2n-ai-fi/modules/sdsvkie/scripts/common/remove_imgs.py new file mode 100755 index 0000000..d330cd6 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/common/remove_imgs.py @@ -0,0 +1,24 @@ +import os +import shutil +from pathlib import Path + + +SRC_DIR = "/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed/train/sbt/batch_1" +TEST_DIR = "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/exp_9_lr5e_6_no_scheduler/sbt_txt" + +# Get a list of all the files in the test directory +test_files = sorted([Path(f).stem for f in os.listdir(TEST_DIR) if ".txt" in f]) +print(len(test_files)) + +# Create the output directory if it doesn't exist +# Move the matching files from the source directory to the output directory +i = 0 +src_files = sorted(os.listdir(SRC_DIR)) +print(len(src_files)) +for filename in src_files: + # print(Path(filename).stem ) + if Path(filename).stem not in test_files: + print(Path(filename).stem) + i+=1 + +print(i) \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/common/rename.py b/cope2n-ai-fi/modules/sdsvkie/scripts/common/rename.py new file mode 100755 index 0000000..9283ed2 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/common/rename.py @@ -0,0 +1,15 @@ +import os + +def rename_files(folder_path): + # Get a list of all the files in the folder + files = os.listdir(folder_path) + # Iterate over the files and rename them + for i, filename in enumerate(files): + # Construct the new filename + new_filename = filename.replace(" ", "_") + # Rename the file + os.rename(os.path.join(folder_path, filename), os.path.join(folder_path, new_filename)) + +rename_files( + folder_path="/mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/intermediate/sbt/images", +) \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/common/rename.sh b/cope2n-ai-fi/modules/sdsvkie/scripts/common/rename.sh new file mode 100755 index 0000000..889fbe1 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/common/rename.sh @@ -0,0 +1,10 @@ +python rename_labels.py \ + --in_dir /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed \ + --out_dir /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed \ + --doc_type receipt + + +python rename_labels.py \ + --in_dir /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed \ + --out_dir /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed \ + --doc_type invoice \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/common/rename_labels.py b/cope2n-ai-fi/modules/sdsvkie/scripts/common/rename_labels.py new file mode 100755 index 0000000..1f0962f --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/common/rename_labels.py @@ -0,0 +1,191 @@ +import argparse +from pathlib import Path +from tqdm import tqdm +import json + +INVOICE_MAPPING = { + 'no_key': 'No_key', # số hóa đơn + 'no_value': 'No_value', + 'form_key': 'Form_key', # mẫu số hóa đơn + 'form_value': 'Form_value', + 'serial_key': 'Serial_key', # số kí hiệu hoá đơn + 'serial_value': 'Serial_value', + 'date': 'Date_value', + + # seller info + 'seller_company_name_key': 'Seller_company_name_key', + 'seller_company_name_value': 'Seller_company_name_value', + 'seller_tax_code_key': 'Seller_tax_code_key', + 'seller_tax_code_value': 'Seller_tax_code_value', + 'seller_address_value': 'Seller_address_value', + 'seller_address_key': 'Seller_address_key', + 'seller_mobile_key': 'Seller_tel_key', + 'seller_mobile_value': 'Seller_tel_value', + + # buyer info + 'buyer_name_key': 'Buyer_personal_name_key', + 'buyer_name_value': 'Buyer_personal_name_value', + 'buyer_company_name_value': 'Buyer_company_name_value', + 'buyer_company_name_key': 'Buyer_company_name_key', + 'buyer_tax_code_key': 'Buyer_tax_code_key', + 'buyer_tax_code_value': 'Buyer_tax_code_value', + 'buyer_address_key': 'Buyer_address_key', + 'buyer_address_value': 'Buyer_address_value', + 'buyer_mobile_key': 'Buyer_tel_key', + 'buyer_mobile_value': 'Buyer_tel_value', + + # money info + 'VAT_amount_key': 'Tax_amount_key', + 'VAT_amount_value': 'Tax_amount_value', + 'total_key': 'Total_key', + 'total_value': 'Total_value', + 'total_in_words_key': 'Total_in_words_key', + 'total_in_words_value': 'Total_in_words_value', + + 'other': 'Other', +} + +RECEIPT_MAPPING = { + "Store_name_value": "seller_company_name_value", + "Seller_company_name_value": "seller_company_name_value", + "id": "no_value", + "No_value": "no_value", + + "Date_value": "date_value", + "Total_key": "total_key", + "Total_value": "total_value", + + "Others": "other", + "others": "other", + "Other": "other", +} + +def write_txt(txt, data, mode="w"): + with open(txt, mode, encoding="utf8") as f: + for line in data: + f.write(line + "\n") + + +def read_txt(txt): + with open(txt, "r", encoding="utf8") as f: + data = [line.strip() for line in f] + return data + + + +def edit_file(in_txt, out_txt, mapping): + data = read_txt(in_txt) + new_items = [] + not_exits_label = False + not_edit = True + for item in data: + splited_item = item.split("\t") + label = splited_item[-1] + if label in mapping.keys(): + new_label = mapping[label] + splited_item[-1] = new_label + not_edit = False + else: + # print(label, "not in ", mapping.keys()) + not_exits_label = True + splited_item[-1] = label.lower() + + splited_item[-1] = splited_item[-1].lower() + new_item = "\t".join(splited_item) + new_items.append(new_item) + + if not_exits_label: + print("Not exists label: ", in_txt) + + if not not_edit: + print("Not edit: ", in_txt) + write_txt(out_txt, new_items) + +def rename_labels(data_dir, out_dir, doc_type): + data_dir = Path(data_dir) + out_dir = Path(out_dir) + if not out_dir.exists(): + out_dir.mkdir(parents=True, exist_ok=True) + if doc_type == "receipt": + mapping = RECEIPT_MAPPING + elif doc_type == 'invoice': + mapping = INVOICE_MAPPING + else: + raise NotImplementedError() + txt_paths = data_dir.rglob("*.txt") + for txt_path in tqdm(txt_paths): + txt_dir = str(Path(str(txt_path).replace(str(data_dir), "")).parent) # a/b/c/x.txt -> c/x.txt -> c + + if txt_dir[0] == "/": + txt_dir = txt_dir[1:] + out_sub_dir = out_dir / Path(txt_dir) + + if not out_sub_dir.exists(): + out_sub_dir.mkdir(parents=True, exist_ok=True) + + out_txt = out_sub_dir / txt_path.name + + # if "failure" in str(out_txt): + # # print(out_txt) + # print(out_sub_dir) + # print(out_txt) + # print(out_txt) + edit_file(str(txt_path), out_txt=out_txt, mapping=mapping) + +def write_json(json_path, data): + with open(json_path, "w", encoding="utf8") as f: + json.dump(data, f, ensure_ascii=False, sort_keys=True) + + +def read_json(json_path): + with open(json_path, "r", encoding="utf8") as f: + data = json.load(f) + return data +def rename_label_in_json(json_in, json_out, doc_type): + if doc_type == "invoice": + mapping = INVOICE_MAPPING + else: + mapping = RECEIPT_MAPPING + ori_data = read_json(json_in) + new_data = {} + for img_key, field_item in ori_data.items(): + new_field_item = {} + for field_key, field_value in field_item.items(): + if field_key in mapping: + new_field_key = mapping[field_key] + else: + new_field_key = field_key + new_field_key = new_field_key.lower() + new_field_item[new_field_key] = field_value + + new_data[img_key] = new_field_item + + write_json(json_out, new_data) + + + + + +if __name__ == "__main__": + parser = argparse.ArgumentParser(prog="Rename labels") + parser.add_argument("--in_dir", type=str, required=True, help="dataset directory") + parser.add_argument("--out_dir", type=str, required=False, help="output") + parser.add_argument("--doc_type", type=str, required=True, help="document type: receipt / invoice") + + args = parser.parse_args() + rename_labels( + data_dir=args.in_dir, + out_dir=args.out_dir, + doc_type=args.doc_type + ) + + # rename_label_in_json( + # json_in=args.in_dir, + # json_out=args.out_dir, + # doc_type=args.doc_type + # ) + + +""" + +""" \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/common/sort_e2e.py b/cope2n-ai-fi/modules/sdsvkie/scripts/common/sort_e2e.py new file mode 100755 index 0000000..6484787 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/common/sort_e2e.py @@ -0,0 +1,83 @@ +import argparse +from sdsvkie.utils import read_json, yaml_load, write_json +# from sdsvkie.utils.post_processing.invoice_post_processing import * +# from sdsvkie.utils.post_processing.common_post_processing import normalize_number +from tqdm import tqdm + +INVOICE_KEYS = [ + 'no_key', + 'no_value', + 'form_key', + 'form_value', + 'serial_key', + 'serial_value', + + 'date_value', + + 'seller_company_name_key', + 'seller_company_name_value', + 'seller_address_value', + 'seller_address_key', + 'seller_tel_key', + 'seller_tel_value', + 'seller_tax_code_key', + 'seller_tax_code_value', + + 'buyer_personal_name_key', + 'buyer_personal_name_value', + 'buyer_company_name_value', + 'buyer_company_name_key', + + 'buyer_address_key', + 'buyer_address_value', + 'buyer_tax_code_key', + 'buyer_tax_code_value', + 'buyer_tel_key', + 'buyer_tel_value', + + 'tax_amount_key', + 'tax_amount_value', + 'total_key', + 'total_value', + 'total_in_words_key', + 'total_in_words_value', + 'other' +] + +def sort_invoice(data): + + sorted_data = {} + for img_key, img_data in tqdm(data.items()): + sorted_img_data = {} + for field_key in INVOICE_KEYS: + if "_key" in field_key or "other" in field_key: + continue + sorted_img_data[field_key] = img_data.get(field_key, "") + + sorted_data[img_key] = sorted_img_data + + return sorted_data + + +def sort_receipt(data): + return data + + + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument("--input", type=str, help="e2e label file path") + parser.add_argument("--out", type=str, help='postprocess e2e label') + parser.add_argument("--doc_type", default="invoice") + args = parser.parse_args() + + data = read_json(args.input) + if args.doc_type: + + sorted_data = sort_invoice(data) + else: + sorted_data = sort_receipt(data) + + write_json(args.out, sorted_data, sort_keys=False) + + diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/common/split_batches.py b/cope2n-ai-fi/modules/sdsvkie/scripts/common/split_batches.py new file mode 100755 index 0000000..8055195 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/common/split_batches.py @@ -0,0 +1,34 @@ +import os +import shutil + +def split_folder_into_batches(input_folder, output_folder, n): + # Get the list of image files in the input folder + image_files = [f for f in os.listdir(input_folder) if f.lower().endswith(('.jpg', '.jpeg', '.png'))] + # Sort the list of image files + image_files.sort() + print("len: ", len(image_files)) + # Calculate the number of images per batch + batch_size = len(image_files) // n + # Create the output directories + for i in range(n): + batch_dir = os.path.join(output_folder, f"batch_{i+1}") + os.makedirs(batch_dir, exist_ok=True) + # Split the images into batches + for i, image_file in enumerate(image_files): + # print(i, image_file) + batch_index = i // batch_size + batch_dir = os.path.join(output_folder, f"batch_{batch_index+1}") + if not os.path.exists(batch_dir): + os.makedirs(batch_dir, exist_ok=True) + # print(batch_dir) + # Find the corresponding label file + image_name, image_ext = os.path.splitext(image_file) + label_file = f"{image_name}.txt" + label_path = os.path.join(input_folder, label_file) + # Copy the image and label files into the appropriate batch directory + print(label_path, os.path.join(input_folder, image_file), batch_dir) + shutil.copy(os.path.join(input_folder, image_file), batch_dir) + shutil.copy(label_path, batch_dir) + +# Example usage: +split_folder_into_batches("/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/pseudo_ocr/invoice_receipt_sbt", "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/pseudo_ocr/invoice_receipt_sbt_split", 3) diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/common/xml2pdf.py b/cope2n-ai-fi/modules/sdsvkie/scripts/common/xml2pdf.py new file mode 100755 index 0000000..b9e5b07 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/common/xml2pdf.py @@ -0,0 +1,31 @@ +# import xml.etree.ElementTree as ET +# from reportlab.pdfgen import canvas +# from reportlab.lib.pagesizes import letter + +# # Load XML file +# tree = ET.parse('/mnt/hdd2T/AICR/Projects/2023/Xml_SAVINA/2023-04-20_0101803564_0300741922_1C23TYY_714.xml') +# root = tree.getroot() + +# # Create PDF canvas +# pdf_canvas = canvas.Canvas('./2023-04-20_0101803564_0300741922_1C23TYY_714.pdf', pagesize=letter) + +# # Iterate over XML elements and draw on PDF canvas +# for element in root.iter(): +# if element.tag == 'paragraph': +# pdf_canvas.drawString(int(element.get('x')), int(element.get('y')), element.text) +# elif element.tag == 'image': +# pdf_canvas.drawImage(element.get('src'), int(element.get('x')), int(element.get('y')), int(element.get('width')), int(element.get('height'))) + +# # Save PDF file +# pdf_canvas.save() + +import pyxml2pdf + +# Create an XML file + + +# Create a new xml2pdf object +xml2pdf = pyxml2pdf.("/mnt/hdd2T/AICR/Projects/2023/Xml_SAVINA/2023-04-20_0101803564_0300741922_1C23TYY_714.xml") + +# Save the output PDF file +xml2pdf.save("my_pdf_file.pdf") \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/cvat_tool.sh b/cope2n-ai-fi/modules/sdsvkie/scripts/cvat_tool.sh new file mode 100755 index 0000000..cf42f3a --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/cvat_tool.sh @@ -0,0 +1,256 @@ +python tools/cvat.py --task pseudo_from_txt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/labeling/Pseudo/batch_1/Good/batch_1_taxi_sub_1_raw.xml \ + --xml_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/labeling/Pseudo/batch_1/Good/batch_1_taxi_sub_1_pseudo.xml \ + --pseudo_path /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/labeling/Pseudo_OCR/Batch_1_Good/Taxi_sub_1 + +python tools/cvat.py --task pseudo_from_txt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/labeling/Pseudo/batch_1/Good/batch_1_taxi_sub_2_raw.xml \ + --xml_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/labeling/Pseudo/batch_1/Good/batch_1_taxi_sub_2_pseudo.xml \ + --pseudo_path /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/labeling/Pseudo/batch_1/Good/Taxi_sub_2 + +python rename_labels.py \ + --in_dir /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed \ + --out_dir /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed \ + --doc_type receipt + + +python rename_labels.py \ + --in_dir /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed \ + --out_dir /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed \ + --doc_type receipt +# text detect + +python sdsvkie/tools/cvat.py --task pseudo_from_txt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/label_ocr/all/batch_1/batch_1_taxi_sub_1_raw.xml \ + --xml_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/label_ocr/all/batch_1/batch_1_taxi_sub_1_pseudo.xml \ + --pseudo_path /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/label_ocr/all/batch_1/taxi_sub_1 + +python sdsvkie/tools/cvat.py --task pseudo_from_txt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/label_ocr/all/batch_1/batch_1_food.xml \ + --xml_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/label_ocr/all/batch_1/batch_1_food_pseudo.xml \ + --pseudo_path /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/label_ocr/all/batch_1/food + + +python sdsvkie/tools/cvat.py --task pseudo_from_txt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SS_Invoice/labeling/train_vnpt_raw.xml \ + --xml_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SS_Invoice/labeling/train_vnpt_pseudo.xml \ + --pseudo_path /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SS_Invoice/train_with_vnpt + +########## +python tools/cvat.py --task update_txt_from_xml \ + --txt_in /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/labeling/Pseudo_OCR/Batch_1_Good/Taxi_sub_1 \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/labeling/Pseudo/batch_1/Good/batch_1_taxi_sub_1_done.xml \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/processed/batch_1/Good/Taxi_sub_1 \ + --line_to_word \ + --other_class Others + +python tools/cvat.py --task update_txt_from_xml \ + --txt_in /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/labeling/Pseudo/batch_1/Good/Taxi_sub_2 \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/labeling/Pseudo/batch_1/Good/batch_1_taxi_sub_2_done.xml \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/processed/batch_1/Good/Taxi_sub_2 \ + --other_class Others + +python tools/cvat.py --task update_txt_from_xml \ + --txt_in /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/labeling/Pseudo/batch_1/Good/Food \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/labeling/Pseudo/batch_1/Good/batch_1_food_done.xml \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/processed/batch_1/Good/Food \ + --other_class Others + +python tools/cvat.py --task update_txt_from_xml \ + --txt_in /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/labeling/Pseudo/batch_2/Good/Food \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/labeling/Pseudo/batch_2/batch_2_food_done.xml \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/processed/batch_2/Good/Food \ + --other_class Others + +# WILD RECEIPT + +python sdsvkie/tools/cvat.py --task update_txt_from_xml \ + --txt_in /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/WildReceipt/re_labeling/batches/batch_1 \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/WildReceipt/re_labeling/batches/batch_1 \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/WildReceipt/re_labeling/wild_batch_1_done.xml \ + --other_class Others + + + +# SS RECEIPT +python sdsvkie/tools/cvat.py --task pseudo_from_txt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/SS_Receipt/Images_splitted/ss_receipt_batch_1_raw.xml \ + --xml_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/SS_Receipt/Images_splitted/ss_receipt_batch_1_pseudo.xml \ + --pseudo_path /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/SS_Receipt/Images_splitted_txt/batch_1 \ + --other_class Others + + + +python sdsvkie/tools/cvat.py --task pseudo_from_txt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/MC-OCR/raw/Images_aligned/train_splitted_txt/mc_ocr_batch_3_raw.xml \ + --xml_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/MC-OCR/raw/Images_aligned/train_splitted_txt/mc_ocr_batch_3_pseudo.xml \ + --pseudo_path /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/MC-OCR/raw/Images_aligned/train_splitted_v2/batch_3 \ + --other_class Others \ + --resever_parent_dir + +python sdsvkie/tools/cvat.py --task pseudo_from_txt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/SS_Receipt/ss_receipt_all_raw.xml \ + --xml_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/SS_Receipt/ss_receipt_all_pseudo.xml \ + --pseudo_path /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/SS_Receipt/Done \ + --other_class Others \ + --resever_parent_dir + + +python sdsvkie/tools/cvat.py --task pseudo_from_txt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/intermediate/pseudo_label/mcocr_raw.xml \ + --xml_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/intermediate/pseudo_label/mcocr_pseudo.xml \ + --pseudo_path /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed/train/mc_ocr \ + --other_class Others \ + --resever_parent_dir +python sdsvkie/tools/cvat.py --task pseudo_from_txt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/intermediate/pseudo_label/sdsap_receipt_raw.xml \ + --xml_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/intermediate/pseudo_label/sdsap_receipt_pseudo.xml \ + --pseudo_path /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed/train/sdsap_receipt \ + --other_class Others \ + --resever_parent_dir +python sdsvkie/tools/cvat.py --task pseudo_from_txt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/intermediate/pseudo_label/ss_receipt_raw.xml \ + --xml_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/intermediate/pseudo_label/ss_receipt_pseudo.xml \ + --pseudo_path /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed/train/ss_receipt \ + --other_class Others \ + --resever_parent_dir + +python sdsvkie/tools/cvat.py --task pseudo_from_txt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/intermediate/pseudo_label/wildreceipt_raw.xml \ + --xml_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/intermediate/pseudo_label/wildreceipt_pseudo.xml \ + --pseudo_path /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed/train/wildreceipt \ + --other_class Others \ + --resever_parent_dir + +# INVOICE + +python sdsvkie/tools/cvat.py --task pseudo_from_txt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/Labeling/invoice_sl_hn_raw.xml \ + --xml_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/Labeling/invoice_sl_hn_pseudo.xml \ + --pseudo_path /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/SL_HN_Invoice_txt \ + --other_class other + + +python sdsvkie/tools/cvat.py --task pseudo_from_txt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/Labeling/invoice_sl_hcm_tmp_done.xml \ + --xml_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/Labeling/invoice_sl_hcm_tmp_done_2.xml \ + --pseudo_path /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/invoice_add_sl_hcm_finetuning/SL_HCM_Invoice_wg_txt_need_review \ + --other_class other + +python sdsvkie/tools/cvat.py --task pseudo_from_txt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/Labeling/invoice_ss_raw.xml \ + --xml_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/Labeling/invoice_ss_wg_pseudo.xml \ + --pseudo_path /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/intermediate/parse_wg/SS_Invoice \ + --other_class other + + +python sdsvkie/tools/cvat.py --task pseudo_from_txt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/intermediate/multi_pages/labels/ss_hcm_batch_2_multi_pages_raw.xml \ + --xml_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/intermediate/multi_pages/labels/ss_hcm_batch_2_multi_pages_pseudo.xml \ + --pseudo_path /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/SL_HCM_batch_2_first_last_page_txt \ + --other_class other + +python sdsvkie/tools/cvat.py --task pseudo_from_txt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/intermediate/sbt/sbt_craw_raw.xml \ + --xml_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/intermediate/sbt/sbt_craw_pseudo.xml \ + --pseudo_path /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/receipt/13062023_4/Crawled_invoices_SBT \ + --other_class other + +python sdsvkie/tools/cvat.py --task pseudo_from_txt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/receipt/13062023_6/sbt_test_raw.xml \ + --xml_out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/receipt/13062023_6/sbt_test_pseudo.xml \ + --pseudo_path /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed/test_sbt_wg \ + --other_class other + +python sdsvkie/tools/cvat.py --task pseudo_from_txt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/viettinbank_pocr_raw.xml \ + --xml_out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/viettinbank_pocr_pseudo.xml \ + --pseudo_path /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/invoice_viettinbank_poc_txt \ + --other_class other + + + +# UPDATE TXT +python sdsvkie/tools/cvat.py --task update_txt_from_xml \ + --txt_in /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/MC-OCR/raw/Images_aligned/train_splitted_txt/batch_1 \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/MC-OCR/raw/Images_aligned/train_splitted/batch_1 \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/MC-OCR/raw/Images_aligned/train_splitted_txt/mc_ocr_batch_1_done.xml \ + --other_class Others + +python sdsvkie/tools/cvat.py --task update_txt_from_xml \ + --txt_in /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/MC-OCR/raw/Images_aligned/train_splitted_txt/batch_2 \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/MC-OCR/raw/Images_aligned/train_splitted/batch_2 \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/MC-OCR/raw/Images_aligned/train_splitted_txt/mc_ocr_batch_2_done.xml \ + --other_class Others + + +python sdsvkie/tools/cvat.py --task update_txt_from_xml \ + --txt_in /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/MC-OCR/raw/Images_aligned/train_splitted_v2/batch_3 \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/MC-OCR/raw/Images_aligned/train_splitted_v2/batch_3_2 \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/MC-OCR/raw/Images_aligned/train_splitted_txt/mc_ocr_batch_3_done.xml \ + --other_class Others \ + --resever_parent_dir + +python sdsvkie/tools/cvat.py --task update_txt_from_xml \ + --txt_in /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/SS_Receipt/Done \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/SS_Receipt/Done \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/SS_Receipt/ss_receipt_by_store_done.xml \ + --other_class Others \ + --resever_parent_dir + + +python sdsvkie/tools/cvat.py --task update_txt_from_xml \ + --txt_in /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/SS_Receipt/Images_splitted_txt/batch_1 \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/SS_Receipt/Images_splitted/batch_1 \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/SS_Receipt/Images_splitted/ss_receipt_batch_1_done.xml \ + --other_class Others + +python sdsvkie/tools/cvat.py --task update_txt_from_xml \ + --txt_in /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/SS_Receipt/Images_splitted_txt/batch_2 \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/SS_Receipt/Images_splitted/batch_2 \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/SS_Receipt/Images_splitted/ss_receipt_batch_2_done.xml \ + --other_class Others + +python sdsvkie/tools/cvat.py --task update_txt_from_xml \ + --txt_in /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/SL_HN_Invoice \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/SL_HN_Invoice \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/Labeling/invoice_sl_hn_done.xml \ + --other_class other \ + --line_to_word + +python sdsvkie/tools/cvat.py --task update_txt_from_xml \ + --txt_in /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/train/SS_Invoice \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/train/SS_Invoice \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/Labeling/ss_invoice_done.xml \ + --other_class other \ + --line_to_word + + +python sdsvkie/tools/cvat.py --task update_txt_from_xml \ + --txt_in /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/intermediate/multi_pages/SL_HCM_batch_2_first_last_page \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/intermediate/multi_pages/SL_HCM_batch_2_first_last_page \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/intermediate/multi_pages/labels/sl_hcm_batch_2_multi_pages_done.xml \ + --other_class other \ + --line_to_word + + +python sdsvkie/tools/cvat.py --task update_txt_from_xml \ + --txt_in /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/receipt/13062023_4/Crawled_invoices_SBT_no_wg_txt \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/receipt/13062023_4/Crawled_invoices_SBT_no_wg_txt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/intermediate/sbt/sbt_craw_done.xml \ + --other_class other \ + --line_to_word + +python sdsvkie/tools/cvat.py --task update_txt_from_xml \ + --txt_in /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed/test_sbt \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed/test_sbt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/receipt/13062023_6/sbt_test_done.xml \ + --other_class other \ + --line_to_word + +python sdsvkie/tools/cvat.py --task update_txt_from_xml \ + --txt_in /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/invoice_viettinbank_poc_txt \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/invoice_viettinbank_poc_txt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/viettinbank_poc_done.xml \ + --other_class other \ + --line_to_word diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/eval_e2e.sh b/cope2n-ai-fi/modules/sdsvkie/scripts/eval_e2e.sh new file mode 100755 index 0000000..9a845c8 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/eval_e2e.sh @@ -0,0 +1,96 @@ +#SDSAP +python sdsvkie/utils/eval_kie.py \ +--gt /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/done/test_end2end/food_e2e.json \ +--pred /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/test_end2end_food_pred_v1.json \ +--cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/config.yaml + + + +python sdsvkie/utils/eval_kie.py \ +--cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/config.yaml \ +--gt /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/done/test_end2end/all_e2e.json \ +--pred /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/test_all_end2end_w0.1_h0.3_thr5.json \ +--log_failure_case /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/test_all_end2end_w0.1_h0.3_thr5.json + + +python sdsvkie/utils/eval_kie.py \ +--cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/config.yaml \ +--gt /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/done/test_end2end/taxi_e2e.json \ +--pred /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/test_taxi_end2end_text_det_20230425.json \ +--log_failure_case /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/test_taxi_end2end_text_det_20230425_fail.json + + +python sdsvkie/utils/eval_kie.py \ +--cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/config.yaml \ +--gt /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/done/test_end2end/taxi_e2e.json \ +--pred /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/test_taxi_end2end_w0.2_h0.2_thr5.json \ +--log_failure_case /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/test_taxi_end2end_w0.2_h0.2_thr5_fail.json + + +# 10/5/2023 +python sdsvkie/utils/eval_kie.py \ +--cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/exp_8_lr9e_6/config.yaml \ +--gt /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/test_end2end/all_e2e.json \ +--pred /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/exp_8_lr9e_6/receipt_e2e.json \ +--log_failure_case /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/exp_8_lr9e_6/receipt_e2e_fail.json + +python sdsvkie/utils/eval_kie.py \ +--cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/exp_9_lr5e_6_no_scheduler/config.yaml \ +--gt /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed/test_end2end/all_e2e.json \ +--pred /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/exp_9_lr5e_6_no_scheduler/receipt_e2e_best.json \ +--log_failure_case /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/exp_9_lr5e_6_no_scheduler/receipt_e2e_best_fail.json + + + + + + + + + +=============================== INVOICE ==================================================================== +python sdsvkie/utils/eval_kie.py \ +--gt /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SS_Invoice/test_end2end/test_e2e.json \ +--pred /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/e2e/test_vnpt_epx_4_best_not_ocr_merge_use_label.json \ +--cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/config.yaml \ +--log_failure_case /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/failure_of_test_vnpt_epx_4_best_not_ocr_merge_use_label.json + + +python sdsvkie/utils/eval_kie.py \ +--gt /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SS_Invoice/test_end2end/test_e2e.json \ +--pred /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/pred_test_end2end.json \ +--cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/config.yaml \ +--log_failure_case /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/vnpt_epx_falures_v2.json + +python sdsvkie/utils/eval_kie.py \ +--gt /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/test_ss_e2e_rm_leak.json \ +--pred /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/test_ss_rm_leak.json \ +--cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/config.yaml \ +--log_failure_case /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/test_ss_e2e_rm_leak_fail.json + +python sdsvkie/utils/eval_kie.py \ +--gt /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/PDF/multi_page/test_e2e_multi_pages.json \ +--pred /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/test_e2e_multi_page.json \ +--cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/config.yaml \ +--log_failure_case /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/test_e2e_multi_page_fail.json + + + +python sdsvkie/utils/eval_kie.py \ +--gt /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/test_ss_e2e_rm_leak.json \ +--pred /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/26052023/test_ss_rm_leak.json \ +--cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/26052023/config.yaml \ +--log_failure_case /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/26052023/test_ss_rm_leak_fail.json + +python sdsvkie/utils/eval_kie.py \ +--gt /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/PDF/multi_page/test_e2e_multi_pages.json \ +--pred /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/26052023/test_e2e_multi_page.json \ +--cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/26052023/config.yaml \ +--log_failure_case /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/26052023/test_e2e_multi_page_fail.json + + +python sdsvkie/utils/eval_kie.py \ +--gt /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed/test_end2end/sbt_validation_e2e.json \ +--pred /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/receipt/13062023_6/sbt_validation_e2e_ep50.json \ +--cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/receipt/13062023_6/config.yaml \ +--log_failure_case /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/receipt/13062023_6/sbt_validation_e2e_ep50_fail.json \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/infer.sh b/cope2n-ai-fi/modules/sdsvkie/scripts/infer.sh new file mode 100755 index 0000000..79ef2bd --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/infer.sh @@ -0,0 +1,199 @@ +python sdsvkie/tools/infer.py --cfg workdirs/invoice/exp1/config.yaml --inference_weights workdirs/invoice/exp1/best --device cuda --img ../TokenClassification_invoice/DATA/test/01067_0452_000.jpg + +python sdsvkie/tools/infer.py --cfg workdirs/invoice/exp1/config.yaml --inference_weights workdirs/invoice/exp1/best --device "cuda:1" \ + --img ../craw_data/output/synth_template_4/one_line --txt_out workdirs/visualize/vnpt_one_line_txt --kie_wordgroup_out + + + +python sdsvkie/tools/infer.py --cfg workdirs/invoice/exp1/config.yaml --inference_weights workdirs/invoice/exp1/best --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/craw_data/output/synth_vnpt_r20/one_line --txt_out workdirs/visualize/vnpt_one_line_r20_txt --kie_wordgroup_out + + +python sdsvkie/tools/infer.py --cfg workdirs/invoice/exp_add_vnpt_template/config.yaml --inference_weights workdirs/invoice/exp_add_vnpt_r2/best --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/craw_data/output/synth_vnpt_r2_2/one_line \ + --vis_out workdirs/visualize/vnpt_r2_phase_2 \ + --txt_out workdirs/visualize/vnpt_r2_phase_2_txt --kie_wordgroup_out + + + +python sdsvkie/tools/infer.py --cfg workdirs/invoice/exp_add_vnpt_template/config.yaml --inference_weights workdirs/invoice/exp_add_vnpt_r2/best --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/craw_data/output/synth_vnpt_r2_2/one_line \ + --vis_out workdirs/visualize/vnpt_r2_phase_2 \ + --txt_out workdirs/visualize/vnpt_r2_phase_2_txt --kie_wordgroup_out + + +python sdsvkie/tools/infer.py --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoiceadd_vnpt_final/config.yaml --inference_weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoiceadd_vnpt_final/epoch_60 --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/test \ + --vis_out workdirs/visualize/test_sorted + + +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoiceadd_vnpt_final/config.yaml \ + --inference_weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoiceadd_vnpt_final/epoch_60 \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/test \ + --vis_out workdirs/visualize/test_sorted + +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoiceadd_vnpt_final/config.yaml \ + --inference_weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoiceadd_vnpt_final/epoch_60 \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/test \ + + +# test e2e +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/exp_wild_1/config.yaml \ + --inference_weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/exp_wild_1/best \ + --device "cuda:0" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/intermediate/labeling/phase_1/batch_1 \ + --vis_out workdirs/visualize/SDSAP_Invoice_exp_wild_1 + +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/config.yaml \ + --inference_weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/best \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/test \ + --e2e workdirs/e2e/test_sampling_sortword_exp4_best.json + +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/config.yaml \ + --inference_weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/last \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Dataset/common_tools/JPG/one_page/vat \ + --e2e workdirs/e2e/test_invoice_vnpt_exp4_sdsv_invoice.json \ + --vis workdirs/e2e/test_invoice_vnpt_exp4_sdsv_invoice_visualize + +# sdsAP +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_1/config.yaml \ + --inference_weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_1/best \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/processed/batch_1/Good/Taxi_sub_2 \ + --vis_out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/infer/visualize/exp_1_batch_1_taxi_sub_2 + +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_2/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_2/best \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/processed/batch_2/Noise \ + --vis_out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/infer/visualize/exp_2_batch_2_noise + + +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/best \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/processed/batch_2/Good/Taxi \ + --vis_out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/infer/visualize/exp_3_batch_2_good_taxi + + +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/best \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/done/test_end2end/Taxi \ + --vis_out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/infer/visualize/exp_3_batch_2_good_taxi + + +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/best \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/label_ocr/all/batch_1/food \ + --vis_out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/infer/visualize/exp_3_batch_1_food + + + +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/best \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/done/test_end2end/Taxi \ + --vis_out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/infer/visualize/exp_3_test_end2end_taxi_2 + + +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/exp_9_lr5e_6_no_scheduler/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/exp_9_lr5e_6_no_scheduler/best \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/test_end2end/All \ + --vis_out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/exp_9_lr5e_6_no_scheduler/receipt_e2e_infer_best + + +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/receipt/13062023_4/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/receipt/13062023_4/last \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed/test_sbt \ + --vis_out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/receipt/13062023_4/test_sbt_infer + + + + +# MCOCR +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/best \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/MC-OCR/raw/Images_aligned/train_splitted/batch_1 \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/MC-OCR/raw/Images_aligned/train_splitted_txt/batch_1 + + +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/best \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/SS_Receipt/Images_splitted/batch_1 \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/SS_Receipt/Images_splitted_txt/batch_1 + + + + +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/02062023/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/02062023/best \ + --device "cuda:0" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/sl_hcm_hn_savina \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/02062023/multi_pages_sl_hcm_hn_savina_wg_txt \ + --kie_wordgroup_out + +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/receipt/13062023_4/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/receipt/13062023_4/last \ + --device "cuda:0" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/raw/Crawled_invoices_SBT \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/receipt/13062023_4/Crawled_invoices_SBT \ + --kie_wordgroup_out + + +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/receipt/13062023_4/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/receipt/13062023_4/last \ + --device "cuda:0" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/raw/Crawled_invoices_SBT \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/receipt/13062023_4/Crawled_invoices_SBT_no_wg_txt + + +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/receipt/13062023_6/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/receipt/13062023_6/epoch_50 \ + --device "cuda:0" \ + --img /mnt/ssd1T/tuanlv/06.KVUCombineStage/datasets/invoices-receipts/SS_invoices/SBT/validation_data/valid_images \ + --vis_out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/receipt/13062023_6/sbt_validation_e2e_ep50_old_textdet_infer + + +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/best \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/PDF/Viettinbank_POC/POC_OCR/invoice_JPG \ + --vis_out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/visualize/vietinbank + + +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/best \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/intermediate/1000416613 \ + --vis_out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/visualize/intermediate_1000416613 \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/infer_e2e.sh b/cope2n-ai-fi/modules/sdsvkie/scripts/infer_e2e.sh new file mode 100755 index 0000000..b177280 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/infer_e2e.sh @@ -0,0 +1,210 @@ +# SDSAP_Receipt +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/best \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/done/test_end2end/All \ + --e2e /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/test_all_end2end.json \ + --vis /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/test_all_end2end + + +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/best \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/OTHER_DATA/MC-OCR/raw/Images/train \ + --e2e /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/train_mcocr_end2end.json \ + --vis /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/train_mcocr_end2end + + +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/best \ + --text_det /mnt/ssd500/datnt/mmdetection/logs/textdet-fwd-table-receipt-20230425/best_bbox_mAP_epoch_15_lite.pth \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/done/test_end2end/Taxi \ + --e2e /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/test_taxi_end2end_text_det_20230425.json \ + --vis /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/test_taxi_end2end_text_det_20230425 + + +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/best \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/done/v1/train \ + --e2e /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/test_end2end.json + +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/best \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/done/test_end2end/Taxi \ + --e2e /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/test_taxi_end2end_w0.2_h0.2_thr5.json \ + --vis /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/test_taxi_end2end_w0.2_h0.2_thr5 + +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/best \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/test_end2end/All \ + --e2e /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/test_all_end2end_w0.1_h0.3_thr5_v2.json \ + --vis /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/test_taxi_end2end_w0.1_h0.3_thr5_v2 + +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/exp_8_lr9e_6/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/exp_8_lr9e_6/best \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/test_end2end/All \ + --e2e /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/exp_8_lr9e_6/receipt_e2e.json \ + --vis /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/exp_8_lr9e_6/receipt_e2e + + +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/exp_9_lr5e_6_no_scheduler/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/exp_9_lr5e_6_no_scheduler/best \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/test_end2end/All \ + --e2e /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/exp_9_lr5e_6_no_scheduler/receipt_e2e_best.json \ + --vis /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/sdsap_receipt/exp_9_lr5e_6_no_scheduler/receipt_e2e_best + + +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/best \ + --device "cuda:0" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/Webcash/testing \ + --e2e /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/pred_webcash_testing.json \ + --vis /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_3/pred_webcash_testing + + + +#invoice +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/last \ + --device "cuda:0" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SS_Invoice/test \ + --e2e /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/invoice_end2end_last.json + + + +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/last \ + --device "cuda:0" \ + --img /mnt/ssd1T/hoanglv/Dataset/common_tools/Split_by_pages/multi_page/vat \ + --e2e /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/pred_vat_multi_page_v2.json + + +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/last \ + --device "cuda:0" \ + --img /mnt/ssd1T/hoanglv/Dataset/common_tools/Split_by_pages/multi_page/vat \ + --e2e /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/pred_vat_multi_page_v2.json + + +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/last \ + --device "cuda:0" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SS_Invoice/multi_page_vat/SL_HCM \ + --e2e /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SS_Invoice/multi_page_vat/SL_HCM.json + + +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/last \ + --device "cuda:0" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/test_ss_rm_leak \ + --e2e /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/test_ss_rm_leak.json + +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/last \ + --device "cuda:0" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/test_ss \ + --e2e /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/test_ss.json + + +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/last \ + --device "cuda:0" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/SL_HCM_Invoice \ + --e2e /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/SL_HCM_Invoice.json \ + --vis /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/SL_HCM_Invoice + + +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/26052023/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/26052023/best \ + --device "cuda:0" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/test_ss_rm_leak \ + --e2e /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/26052023/test_ss_rm_leak.json \ + --vis /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/26052023/test_ss_rm_leak + +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/26052023/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/26052023/best \ + --device "cuda:0" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/multi_pages/SL_HCM_batch_2 \ + --e2e /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/26052023/test_ss_sl_hcm_batch_2_multi_page_jpg.json \ + --vis /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/26052023/test_ss_sl_hcm_batch_2_multi_page_jpg + +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/26052023/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/26052023/best \ + --device "cuda:0" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/PDF/multi_page/SL_HN_batch_2 \ + --e2e /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/26052023/multi_page_SL_HN_batch_2.json + + +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/26052023/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/26052023/best \ + --device "cuda:0" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/PDF/multi_page/test_e2e_multi_page \ + --e2e /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/26052023/test_e2e_multi_page.json + + +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/02062023/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/02062023/best \ + --device "cuda:0" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/PDF/multi_page/SL_HN_batch_2 \ + --e2e /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/02062023/multi_page_SL_HN_batch_2.json + + +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/best \ + --device "cuda:0" \ + --img /mnt/hdd2T/AICR/Projects/2023/Vietinbank_POC/Invoice_JPG/ \ + --e2e /mnt/hdd2T/AICR/Projects/2023/Vietinbank_POC/Invoice_KIE_Results/result.json + + +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/best \ + --device "cuda:0" \ + --img /mnt/hdd2T/AICR/Projects/2023/FI_Invoices/Invoice_v2_multi_page \ + --e2e /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/Invoice_v2_multi_page.json + + +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/19072023/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/19072023/best \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/PDF/Viettinbank_POC/POC_OCR/invoice_JPG/ \ + --e2e /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/19072023/vietinbank_poc_infer.json \ + --vis workdirs/invoice/19072023/visualize/vietinbank_infer + + +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/best \ + --device "cuda:0" \ + --img /mnt/hdd2T/AICR/Projects/2023/FI_Invoices/Test/1000416613/1000416613_0102310385_26062023163233062_001.pdf \ + --e2e /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/1000416613_0102310385_26062023163233062_001.json + \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/label_cvat.json b/cope2n-ai-fi/modules/sdsvkie/scripts/label_cvat.json new file mode 100755 index 0000000..53141c8 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/label_cvat.json @@ -0,0 +1,226 @@ +[ + { + "name": "total_in_words_key", + "id": 92, + "color": "#33ddff", + "type": "any", + "attributes": [] + }, + { + "name": "no_value", + "id": 93, + "color": "#fa3253", + "type": "any", + "attributes": [] + }, + { + "name": "form_key", + "id": 94, + "color": "#34d1b7", + "type": "any", + "attributes": [] + }, + { + "name": "no_key", + "id": 95, + "color": "#ff007c", + "type": "any", + "attributes": [] + }, + { + "name": "form_value", + "id": 96, + "color": "#ddff33", + "type": "any", + "attributes": [] + }, + { + "name": "serial_key", + "id": 97, + "color": "#24b353", + "type": "any", + "attributes": [] + }, + { + "name": "serial_value", + "id": 98, + "color": "#b83df5", + "type": "any", + "attributes": [] + }, + { + "name": "date_value", + "id": 99, + "color": "#66ff66", + "type": "any", + "attributes": [] + }, + { + "name": "seller_company_name_key", + "id": 100, + "color": "#32b7fa", + "type": "any", + "attributes": [] + }, + { + "name": "seller_company_name_value", + "id": 101, + "color": "#ffcc33", + "type": "any", + "attributes": [] + }, + { + "name": "seller_tax_code_key", + "id": 102, + "color": "#83e070", + "type": "any", + "attributes": [] + }, + { + "name": "seller_tax_code_value", + "id": 103, + "color": "#fafa37", + "type": "any", + "attributes": [] + }, + { + "name": "seller_address_value", + "id": 104, + "color": "#5986b3", + "type": "any", + "attributes": [] + }, + { + "name": "seller_address_key", + "id": 105, + "color": "#8c78f0", + "type": "any", + "attributes": [] + }, + { + "name": "seller_tel_key", + "id": 106, + "color": "#ff6a4d", + "type": "any", + "attributes": [] + }, + { + "name": "seller_tel_value", + "id": 107, + "color": "#f078f0", + "type": "any", + "attributes": [] + }, + { + "name": "buyer_personal_name_key", + "id": 108, + "color": "#2a7dd1", + "type": "any", + "attributes": [] + }, + { + "name": "buyer_personal_name_value", + "id": 109, + "color": "#83e070", + "type": "any", + "attributes": [] + }, + { + "name": "buyer_company_name_value", + "id": 110, + "color": "#5986b3", + "type": "any", + "attributes": [] + }, + { + "name": "buyer_company_name_key", + "id": 111, + "color": "#8c78f0", + "type": "any", + "attributes": [] + }, + { + "name": "buyer_tax_code_key", + "id": 112, + "color": "#ff6a4d", + "type": "any", + "attributes": [] + }, + { + "name": "buyer_tax_code_value", + "id": 113, + "color": "#f078f0", + "type": "any", + "attributes": [] + }, + { + "name": "buyer_address_key", + "id": 114, + "color": "#2a7dd1", + "type": "any", + "attributes": [] + }, + { + "name": "buyer_address_value", + "id": 115, + "color": "#b25050", + "type": "any", + "attributes": [] + }, + { + "name": "buyer_tel_key", + "id": 116, + "color": "#cc3366", + "type": "any", + "attributes": [] + }, + { + "name": "buyer_tel_value", + "id": 117, + "color": "#cc9933", + "type": "any", + "attributes": [] + }, + { + "name": "tax_amount_key", + "id": 118, + "color": "#aaf0d1", + "type": "any", + "attributes": [] + }, + { + "name": "tax_amount_value", + "id": 119, + "color": "#ff00cc", + "type": "any", + "attributes": [] + }, + { + "name": "total_key", + "id": 120, + "color": "#3df53d", + "type": "any", + "attributes": [] + }, + { + "name": "total_value", + "id": 121, + "color": "#fa32b7", + "type": "any", + "attributes": [] + }, + { + "name": "total_in_words_value", + "id": 122, + "color": "#3d3df5", + "type": "any", + "attributes": [] + }, + { + "name": "other", + "id": 123, + "color": "#733380", + "type": "any", + "attributes": [] + } +] \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/post_eval_res.sh b/cope2n-ai-fi/modules/sdsvkie/scripts/post_eval_res.sh new file mode 100755 index 0000000..1d79b23 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/post_eval_res.sh @@ -0,0 +1,10 @@ +python sdsvkie/tools/postprocess_e2e_label.py \ + --cfg workdirs/invoice/vnpt_exp_4/config.yaml \ + --input /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SS_Invoice/test_end2end/test_e2e.json \ + --out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SS_Invoice/test_end2end/test_e2e_post.json + + +python sdsvkie/tools/postprocess_e2e_label.py \ + --cfg workdirs/invoice/vnpt_exp_4/config.yaml \ + --input /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/invoice_exp4/test_end2end_post.json \ + --out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/invoice_exp4/test_end2end_post.json \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/pseudo_label.sh b/cope2n-ai-fi/modules/sdsvkie/scripts/pseudo_label.sh new file mode 100755 index 0000000..b673c16 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/pseudo_label.sh @@ -0,0 +1,36 @@ +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/exp_wild_1/config.yaml \ + --inference_weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/exp_wild_1/best \ + --device "cuda:0" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/processed/batch_2/Good/Food \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/labeling/Pseudo/batch_2/Good/Food + + +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_2/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/training/sdsap_receipt/exp_2/best \ + --device "cuda:0" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/processed/batch_1/Good/Taxi_sub_2 \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/labeling/Pseudo/batch_1/Good/Taxi_sub_2 + + + + +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/best \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/intermediate/multi_pages/SL_HCM_batch_2_first_last_page \ + --vis_out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/SL_HCM_batch_2_first_last_page_vis \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/SL_HCM_batch_2_first_last_page_txt \ + --kie_wordgroup_out + + +python sdsvkie/tools/infer.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/best \ + --device "cuda:1" \ + --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/invoice_viettinbank_poc \ + --vis_out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/invoice_viettinbank_poc_vis \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/invoice_viettinbank_poc_txt \ + --kie_wordgroup_out \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/run_ocr.sh b/cope2n-ai-fi/modules/sdsvkie/scripts/run_ocr.sh new file mode 100755 index 0000000..c37231b --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/run_ocr.sh @@ -0,0 +1,19 @@ +python sdsvkie/tools/run_ocr.py \ +--img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/raw/IMGS \ +--out_dir /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/SDSAP_Invoice/visualize_ocr \ +--device "cuda:1" \ +--reserve_parent_dir + + +# python sdsvkie/tools/run_ocr.py \ +# --img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/raw/IMGS \ +# --out_dir /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/SDSAP_Invoice/visualize_ocr \ +# --device "cuda:1" \ +# --reserve_parent_dir + + +python sdsvkie/tools/run_ocr.py \ +--img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/done/test_end2end/Taxi \ +--device "cuda:1" \ +--out_dir /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/label_ocr/test_v2/taxi \ +--text_det "/mnt/ssd500/datnt/mmdetection/logs/textdet-fwd-table-receipt-20230425/best_bbox_mAP_epoch_15_lite.pth" \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/run_ocr_gen_txt.sh b/cope2n-ai-fi/modules/sdsvkie/scripts/run_ocr_gen_txt.sh new file mode 100755 index 0000000..806fe74 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/run_ocr_gen_txt.sh @@ -0,0 +1,35 @@ +python sdsvkie/tools/run_ocr.py \ +--img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/pseudo_ocr \ +--out_dir ./workdirs/visualize/WildReceipt \ +--device "cuda:0" \ +--out_txt /mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/pseudo_ocr + + +python sdsvkie/tools/run_ocr.py \ +--img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/processed/batch_1/Good/Taxi_sub_1 \ +--device "cuda:0" \ +--out_txt /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/labeling/Pseudo_OCR/Batch_1_Good/Taxi_sub_1 + + +# pseudo for edit text detect boxes +python sdsvkie/tools/run_ocr.py \ +--img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/label_ocr/all/batch_1/taxi_sub_1 \ +--device "cuda:0" \ +--out_txt /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/label_ocr/all/batch_1/taxi_sub_1 + + +python sdsvkie/tools/run_ocr.py \ +--img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/label_ocr/all/batch_1/taxi_sub_1 \ +--device "cuda:0" \ +--out_txt /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/label_ocr/all/batch_1/taxi_sub_1 + + +python sdsvkie/tools/run_ocr.py \ +--img /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/label_ocr/all/batch_1/food \ +--device "cuda:0" \ +--out_txt /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/label_ocr/all/batch_1/food + +python sdsvkie/tools/run_ocr.py \ +--img /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/demos/invoice \ +--device "cuda:0" \ +--out_txt /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/demos/invoice \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/run_pdf2img.sh b/cope2n-ai-fi/modules/sdsvkie/scripts/run_pdf2img.sh new file mode 100755 index 0000000..1f9e644 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/run_pdf2img.sh @@ -0,0 +1,15 @@ +python sdsvkie/utils/pdf2image.py \ +--pdf_dir /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/raw/batch_1/PDF \ +--out_dir /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/raw/batch_1/IMGS_dpi_300 \ +--reserve_parent_dir + + +python sdsvkie/utils/pdf2image.py \ +--pdf_dir /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/PDF/multi_page/Invoices_SL_HCM \ +--out_dir /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/raw/JPG/Invoices_SL_HCM + + + +python sdsvkie/utils/pdf2image.py \ +--pdf_dir /mnt/hdd2T/AICR/Projects/2023/Invoice_SDSV/SDSV_Invoice_2023/All \ +--out_dir /mnt/hdd2T/AICR/Projects/2023/Invoice_SDSV/SDSV_Invoice_2023/JPG \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/split_data.sh b/cope2n-ai-fi/modules/sdsvkie/scripts/split_data.sh new file mode 100755 index 0000000..6569eac --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/split_data.sh @@ -0,0 +1,25 @@ +python sdsvkie/utils/split_data.py \ + --path /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/processed/batch_1/Good/Food \ + --out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/done/v2/ \ + --test_ratio 0.05 + +python sdsvkie/utils/split_data.py \ + --path /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/processed/batch_1/Good/Taxi_sub_1 \ + --out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/done/v2/ \ + --test_ratio 0.05 + +python sdsvkie/utils/split_data.py \ + --path /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/processed/batch_1/Good/Taxi_sub_2 \ + --out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/done/v2/ \ + --test_ratio 0.05 + +python sdsvkie/utils/split_data.py \ + --path /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/processed/batch_2/Good/Food \ + --out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/done/v2/ \ + --test_ratio 0.05 + + +python sdsvkie/utils/split_data.py \ + --path /mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/re_labeling/batches/batch_1 \ + --out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/done/v2/ \ + --test_ratio 0.0 \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/scripts/train.sh b/cope2n-ai-fi/modules/sdsvkie/scripts/train.sh new file mode 100755 index 0000000..442cc9c --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/scripts/train.sh @@ -0,0 +1,7 @@ +python sdsvkie/tools/train.py --cfg sdsvkie/cfg/wildreciept.yaml --device cuda:0 --save_dir workdirs/invoice/exp_wild_1 + + +python sdsvkie/tools/train.py --cfg sdsvkie/cfg/sdsap_receipt_scheduler_linear.yaml --device cuda:0 --save_dir workdirs/sdsap_receipt/exp_4_scheduler_linear + + +python sdsvkie/tools/train.py --cfg sdsvkie/cfg/sdsap_receipt.yaml --device cuda:1 --save_dir workdirs/sdsap_receipt/exp_5 \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/__init__.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/__init__.py new file mode 100755 index 0000000..44d01d8 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/__init__.py @@ -0,0 +1,5 @@ +import os +import sys +sys.path.append(__file__) + +from .engine.predictor import Predictor \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/__init__.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/__init__.py new file mode 100755 index 0000000..227e6a4 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/__init__.py @@ -0,0 +1,33 @@ +from types import SimpleNamespace +from sdsvkie.utils.io_file import yaml_load +from pathlib import Path +from copy import copy, deepcopy + +def load_cfg(cfg, args=None): + """ + Convert a configuration object to a dictionary, whether it is a file path, a string, or a SimpleNamespace object. + Inputs: + cfg (str) or (Path) or (SimpleNamespace): Configuration object to be converted to a dictionary. + Returns: + cfg (dict): Configuration object in dictionary format. + """ + if isinstance(cfg, (str, Path)): + cfg = yaml_load(cfg) # load dict + elif isinstance(cfg, SimpleNamespace): + cfg = vars(cfg) # convert to dict + + + if args is not None: + _args = deepcopy(args) + for k, v in args.items(): + if v is None or v == "cfg" : + _args.pop(k) + + if v is not None and k == "weights": + _args['inference_weights'] = v + _args.pop(k) + + cfg.update(_args) + return cfg + + diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/class_list.txt b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/class_list.txt new file mode 100755 index 0000000..090b226 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/class_list.txt @@ -0,0 +1,39 @@ +no_key +no_value +form_key +form_value +serial_key +serial_value +date_key +date_value +subtotal_key +subtotal_value +tax_rate_key +tax_rate_value +tax_amount_key +tax_amount_value +tips_key +tips_value +total_key +total_value +total_in_words_key +total_in_words_value +seller_company_name_key +seller_company_name_value +seller_address_key +seller_address_value +seller_tel_key +seller_tel_value +seller_tax_code_key +seller_tax_code_value +buyer_company_name_key +buyer_company_name_value +buyer_personal_name_key +buyer_personal_name_value +buyer_tax_code_key +buyer_tax_code_value +buyer_address_key +buyer_address_value +buyer_tel_key +buyer_tel_value +other \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/default.yaml b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/default.yaml new file mode 100755 index 0000000..6e150f6 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/default.yaml @@ -0,0 +1,79 @@ + +debug: False +v3: False +# common +device: 'cpu' # 'cpu' / 'cuda:0' / 'cuda:1' / 'cuda' + +#dataset +train_dir: /mnt/ssd1T/hoanglv/Projects/KIE/DATA/train_with_vnpt +val_dir: /mnt/ssd1T/hoanglv/Projects/KIE/DATA/test +slice_interval: 75 +postprocess_type: invoice_postprocess +classes: [ + # id invoice + 'no_key', # số hóa đơn + 'no_value', + 'form_key', # mẫu số hóa đơn + 'form_value', + 'serial_key', # số kí hiệu hoá đơn + 'serial_value', + 'date', + + # seller info + 'seller_company_name_key', + 'seller_company_name_value', + 'seller_tax_code_key', + 'seller_tax_code_value', + 'seller_address_value', + 'seller_address_key', + 'seller_mobile_key', + 'seller_mobile_value', + + # buyer info + 'buyer_name_key', + 'buyer_name_value', + 'buyer_company_name_value', + 'buyer_company_name_key', + 'buyer_tax_code_key', + 'buyer_tax_code_value', + 'buyer_address_key', + 'buyer_address_value', + 'buyer_mobile_key', + 'buyer_mobile_value', + + # money info + 'VAT_amount_key', + 'VAT_amount_value', + 'total_key', + 'total_value', + 'total_in_words_key', + 'total_in_words_value', + + 'other', +] +sampling: true # sampling window - fix long document (larger than 512 token) + +#model +img_size: 224 # fixed +max_seq_length: 512 # fixed +max_num_words: 150 +tokenizer_weights: "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/microsoft/microsoft/layoutxlm-base" # fixed +weights: "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/microsoft/microsoft/layoutxlm-base" + +# opt + scheduler +batch_size: 8 +epochs: 100 +lr: 5.0e-6 +shuffle: True +num_workers: 4 +scheduler: False # False or "linear" / "cosine" / "cosine_with_restarts" / "polynomial" / "constant" / "constant_with_warmup" / "inverse_sqrt" +save_dir: workdirs/invoice/exp1 +save_weight_interval: 10 +eval_delay: 0 +wandb: null + +# inference +inference_weights: null +text_det: yolox-s-general-text-pretrain-20221226 +text_reg: satrn-lite-general-pretrain-20230106 + diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/invoice.yaml b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/invoice.yaml new file mode 100755 index 0000000..24c7192 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/invoice.yaml @@ -0,0 +1,74 @@ + +debug: False +v3: False +# common +device: 'cpu' # 'cpu' / 'cuda:0' / 'cuda:1' / 'cuda' + +#dataset +train_dir: /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/train +val_dir: /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/test_ss +slice_interval: 75 +postprocess_type: invoice_postprocess +classes: [ + 'no_key', + 'no_value', + 'form_key', + 'form_value', + 'serial_key', + 'serial_value', + 'date_value', + + 'seller_company_name_key', + 'seller_company_name_value', + 'seller_tax_code_key', + 'seller_tax_code_value', + 'seller_address_value', + 'seller_address_key', + 'seller_tel_key', + 'seller_tel_value', + + 'buyer_personal_name_key', + 'buyer_personal_name_value', + 'buyer_company_name_value', + 'buyer_company_name_key', + 'buyer_tax_code_key', + 'buyer_tax_code_value', + 'buyer_address_key', + 'buyer_address_value', + 'buyer_tel_key', + 'buyer_tel_value', + 'tax_amount_key', + 'tax_amount_value', + 'total_key', + 'total_value', + 'total_in_words_key', + 'total_in_words_value', + 'other' +] + +sampling: true # sampling window - fix long document (larger than 512 token) + +#model +img_size: 224 # fixed +max_seq_length: 512 # fixed +max_num_words: 145 +tokenizer_weights: "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/microsoft/microsoft/layoutxlm-base" # fixed +weights: "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/microsoft/microsoft/layoutxlm-base" + +# opt + scheduler +batch_size: 8 +epochs: 100 +lr: 5.0e-6 +shuffle: True +num_workers: 4 +scheduler: "linear" # False or "linear" / "cosine" / "cosine_with_restarts" / "polynomial" / "constant" / "constant_with_warmup" / "inverse_sqrt" +save_dir: workdirs/invoice/19072023 +save_weight_interval: 10 +eval_delay: 50 +wandb: null + +# inference +inference_weights: null +text_det: yolox-s-general-text-pretrain-20221226 +text_reg: satrn-lite-general-pretrain-20230106 + diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/invoice_relabel.yaml b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/invoice_relabel.yaml new file mode 100755 index 0000000..7d01ccc --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/invoice_relabel.yaml @@ -0,0 +1,74 @@ + +debug: False +v3: False +# common +device: 'cpu' # 'cpu' / 'cuda:0' / 'cuda:1' / 'cuda' + +#dataset +train_dir: /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/train +val_dir: /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/test_ss +slice_interval: 75 +postprocess_type: invoice_postprocess +classes: [ + 'no_key', + 'no_value', + 'form_key', + 'form_value', + 'serial_key', + 'serial_value', + 'date_value', + + 'seller_company_name_key', + 'seller_company_name_value', + 'seller_tax_code_key', + 'seller_tax_code_value', + 'seller_address_value', + 'seller_address_key', + 'seller_tel_key', + 'seller_tel_value', + + 'buyer_personal_name_key', + 'buyer_personal_name_value', + 'buyer_company_name_value', + 'buyer_company_name_key', + 'buyer_tax_code_key', + 'buyer_tax_code_value', + 'buyer_address_key', + 'buyer_address_value', + 'buyer_tel_key', + 'buyer_tel_value', + 'tax_amount_key', + 'tax_amount_value', + 'total_key', + 'total_value', + 'total_in_words_key', + 'total_in_words_value', + 'other' +] + +sampling: true # sampling window - fix long document (larger than 512 token) + +#model +img_size: 224 # fixed +max_seq_length: 512 # fixed +max_num_words: 145 +tokenizer_weights: "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/microsoft/microsoft/layoutxlm-base" # fixed +weights: "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/microsoft/microsoft/layoutxlm-base" + +# opt + scheduler +batch_size: 8 +epochs: 100 +lr: 5.0e-6 +shuffle: True +num_workers: 4 +scheduler: "cosine" # False or "linear" / "cosine" / "cosine_with_restarts" / "polynomial" / "constant" / "constant_with_warmup" / "inverse_sqrt" +save_dir: workdirs/invoice/26052023 +save_weight_interval: 10 +eval_delay: 50 +wandb: null + +# inference +inference_weights: null +text_det: yolox-s-general-text-pretrain-20221226 +text_reg: satrn-lite-general-pretrain-20230106 + diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/invoice_relabel_finetuning.yaml b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/invoice_relabel_finetuning.yaml new file mode 100755 index 0000000..b5a7231 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/invoice_relabel_finetuning.yaml @@ -0,0 +1,74 @@ + +debug: False +v3: False +# common +device: 'cpu' # 'cpu' / 'cuda:0' / 'cuda:1' / 'cuda' + +#dataset +train_dir: /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/train +val_dir: /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/test_ss +slice_interval: 75 +postprocess_type: invoice_postprocess +classes: [ + 'no_key', + 'no_value', + 'form_key', + 'form_value', + 'serial_key', + 'serial_value', + 'date_value', + + 'seller_company_name_key', + 'seller_company_name_value', + 'seller_tax_code_key', + 'seller_tax_code_value', + 'seller_address_value', + 'seller_address_key', + 'seller_tel_key', + 'seller_tel_value', + + 'buyer_personal_name_key', + 'buyer_personal_name_value', + 'buyer_company_name_value', + 'buyer_company_name_key', + 'buyer_tax_code_key', + 'buyer_tax_code_value', + 'buyer_address_key', + 'buyer_address_value', + 'buyer_tel_key', + 'buyer_tel_value', + 'tax_amount_key', + 'tax_amount_value', + 'total_key', + 'total_value', + 'total_in_words_key', + 'total_in_words_value', + 'other' +] + +sampling: true # sampling window - fix long document (larger than 512 token) + +#model +img_size: 224 # fixed +max_seq_length: 512 # fixed +max_num_words: 150 +tokenizer_weights: "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/microsoft/microsoft/layoutxlm-base" # fixed +weights: "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/vnpt_exp_4/last" + +# opt + scheduler +batch_size: 8 +epochs: 100 +lr: 1.0e-5 +shuffle: True +num_workers: 4 +scheduler: "cosine" # False or "linear" / "cosine" / "cosine_with_restarts" / "polynomial" / "constant" / "constant_with_warmup" / "inverse_sqrt" +save_dir: workdirs/invoice/add_sl_hcm +save_weight_interval: 1 +eval_delay: 1 +wandb: null + +# inference +inference_weights: null +text_det: yolox-s-general-text-pretrain-20221226 +text_reg: satrn-lite-general-pretrain-20230106 + diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/sdsap_receipt.yaml b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/sdsap_receipt.yaml new file mode 100755 index 0000000..ecb1285 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/sdsap_receipt.yaml @@ -0,0 +1,47 @@ + +debug: False +v3: False + +# common +device: 'cpu' # 'cpu' / 'cuda:0' / 'cuda:1' / 'cuda' + +#dataset +train_dir: /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed/train +val_dir: /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed/test +slice_interval: 75 +postprocess_type: receipt_postprocess + +classes: [ + "seller_company_name_value", + "no_value", + "date_value", + "total_key", + "total_value", + "other" +] +sampling: true # sampling window - fix long document (larger than 512 token) + +#model +img_size: 224 # fixed +max_seq_length: 512 # fixed +max_num_words: 150 +tokenizer_weights: "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/microsoft/microsoft/layoutxlm-base" # fixed +weights: "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/microsoft/microsoft/layoutxlm-base" + +# opt + scheduler +batch_size: 8 +epochs: 100 +lr: 5.0e-6 +scheduler: False +shuffle: True +num_workers: 4 +save_dir: workdirs/receipt/13062023 +save_weight_interval: 10 +eval_delay: 0 +wandb: null + +# inference +inference_weights: null +text_det: yolox-s-general-text-pretrain-20221226 +text_reg: satrn-lite-general-pretrain-20230106 + diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/sdsap_receipt_finetuning.yaml b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/sdsap_receipt_finetuning.yaml new file mode 100755 index 0000000..c5a5bca --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/sdsap_receipt_finetuning.yaml @@ -0,0 +1,47 @@ + +debug: False +v3: False + +# common +device: 'cpu' # 'cpu' / 'cuda:0' / 'cuda:1' / 'cuda' + +#dataset +train_dir: /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed/train +val_dir: /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/processed/test +slice_interval: 75 +postprocess_type: receipt_postprocess + +classes: [ + "seller_company_name_value", + "no_value", + "date_value", + "total_key", + "total_value", + "other" +] +sampling: true # sampling window - fix long document (larger than 512 token) + +#model +img_size: 224 # fixed +max_seq_length: 512 # fixed +max_num_words: 150 +tokenizer_weights: "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/microsoft/microsoft/layoutxlm-base" # fixed +weights: "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/receipt/13062023_4/last" + +# opt + scheduler +batch_size: 8 +epochs: 30 +lr: 3.0e-6 +scheduler: False +shuffle: True +num_workers: 4 +save_dir: workdirs/receipt/13062023 +save_weight_interval: 10 +eval_delay: 0 +wandb: null + +# inference +inference_weights: null +text_det: yolox-s-general-text-pretrain-20221226 +text_reg: satrn-lite-general-pretrain-20230106 + diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/sdsap_receipt_relabel.yaml b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/sdsap_receipt_relabel.yaml new file mode 100755 index 0000000..2a276a3 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/sdsap_receipt_relabel.yaml @@ -0,0 +1,47 @@ + +debug: False +v3: False + +# common +device: 'cpu' # 'cpu' / 'cuda:0' / 'cuda:1' / 'cuda' + +#dataset +train_dir: /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/train +val_dir: /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/test +slice_interval: 75 +postprocess_type: receipt_postprocess + +classes: [ + "Seller_company_name_value", + "ID_value", + "Date_value", + "Total_key", + "Total_value", + "Other" +] +sampling: true # sampling window - fix long document (larger than 512 token) + +#model +img_size: 224 # fixed +max_seq_length: 512 # fixed +max_num_words: 150 +tokenizer_weights: "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/microsoft/microsoft/layoutxlm-base" # fixed +weights: "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/microsoft/microsoft/layoutxlm-base" + +# opt + scheduler +batch_size: 8 +epochs: 100 +lr: 9.0e-6 +scheduler: "linear" +shuffle: True +num_workers: 4 +save_dir: workdirs/invoice/exp1 +save_weight_interval: 10 +eval_delay: 50 +wandb: null + +# inference +inference_weights: null +text_det: yolox-s-general-text-pretrain-20221226 +text_reg: satrn-lite-general-pretrain-20230106 + diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/sdsap_receipt_scheduler_linear.yaml b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/sdsap_receipt_scheduler_linear.yaml new file mode 100755 index 0000000..200d1f8 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/sdsap_receipt_scheduler_linear.yaml @@ -0,0 +1,47 @@ + +debug: False +v3: False + +# common +device: 'cpu' # 'cpu' / 'cuda:0' / 'cuda:1' / 'cuda' + +#dataset +train_dir: /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/train +val_dir: /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Receipt/test +slice_interval: 75 +postprocess_type: receipt_postprocess + +classes: [ + "Store_name_value", + "id", + "Date_value", + "Total_key", + "Total_value", + "Others" +] +sampling: true # sampling window - fix long document (larger than 512 token) + +#model +img_size: 224 # fixed +max_seq_length: 512 # fixed +max_num_words: 150 +tokenizer_weights: "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/microsoft/microsoft/layoutxlm-base" # fixed +weights: "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/microsoft/microsoft/layoutxlm-base" + +# opt + scheduler +batch_size: 8 +epochs: 100 +lr: 9.0e-6 +scheduler: "linear" +shuffle: True +num_workers: 4 +save_dir: workdirs/invoice/exp1 +save_weight_interval: 10 +eval_delay: 50 +wandb: null + +# inference +inference_weights: null +text_det: yolox-s-general-text-pretrain-20221226 +text_reg: satrn-lite-general-pretrain-20230106 + diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/wildreciept.yaml b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/wildreciept.yaml new file mode 100755 index 0000000..17f2ea4 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/cfg/wildreciept.yaml @@ -0,0 +1,47 @@ +debug: False +v3: False +scheduler: False +# common +device: 'cpu' # 'cpu' / 'cuda:0' / 'cuda:1' / 'cuda' + +#dataset +train_dir: /mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/v1/train +val_dir: /mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/v1/test +slice_interval: 75 +postprocess_type: receipt_postprocess + +classes: [ + "Store_name_value", + "Date_value", + "Total_key", + "Total_value", + "Others" +] +sampling: True # sampling window - fix long document (larger than 512 token) + +#model +img_size: 224 # fixed +max_seq_length: 512 # fixed +max_num_words: 150 + +# tokenizer_weights: "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/microsoft/layoutlmv3-base" # fixed +# weights: "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/microsoft/layoutlmv3-base" +tokenizer_weights: "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/microsoft/microsoft/layoutxlm-base" # fixed +weights: "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/microsoft/microsoft/layoutxlm-base" + +# opt + scheduler +batch_size: 8 +epochs: 100 +lr: 5.0e-6 +shuffle: True +num_workers: 4 +save_dir: workdirs/invoice/exp1 +save_weight_interval: 10 +eval_delay: 0 +wandb: null + +# inference +inference_weights: null +text_det: yolox-s-general-text-pretrain-20221226 +text_reg: satrn-lite-general-pretrain-20230106 + diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/datasets/base_dataset.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/datasets/base_dataset.py new file mode 100755 index 0000000..661bab0 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/datasets/base_dataset.py @@ -0,0 +1,314 @@ +import logging +import os +import pickle +import random +from copy import deepcopy +from pathlib import Path + +import cv2 +import pandas as pd +import torch +from datasets import (Array2D, Array3D, ClassLabel, Dataset, Features, + Sequence, Value, concatenate_datasets) +from easydict import EasyDict +from PIL import Image +from tqdm import tqdm +from sdsvkie.utils.io_file import read_txt + +from sdsvkie.utils import normalize_box, visualize_kie +from sdsvkie.utils.augmentation import perturbate_character, sampling_data +from sdsvkie.utils.word_formation import sliding_windows, sort_words +import glob + +logger = logging.getLogger(__name__) +logging.basicConfig(level=logging.INFO) + + +IMG_EXTENSION = [".jpg", ".jpeg", ".png"] + +class BaseDataset: + def __init__(self, cfg): + + self.cfg = cfg + self.feature_format = Features( + { + "image": Array3D( + dtype="int64", shape=(3, self.cfg.img_size, self.cfg.img_size) + ), + "input_ids": Sequence(feature=Value(dtype="int64")), + "attention_mask": Sequence(Value(dtype="int64")), + "bbox": Array2D(dtype="int64", shape=(self.cfg.max_seq_length, 4)), + "labels": Sequence(ClassLabel(names=self.cfg.classes)), + } + ) if not self.cfg.v3 else \ + Features( + { + "pixel_values": Array3D( + dtype="float32", shape=(3, self.cfg.img_size, self.cfg.img_size) + ), + "input_ids": Sequence(feature=Value(dtype="int64")), + "attention_mask": Sequence(Value(dtype="int64")), + "bbox": Array2D(dtype="int64", shape=(self.cfg.max_seq_length, 4)), + "labels": Sequence(ClassLabel(names=self.cfg.classes)), + } + ) + + logger.info("Feature format: {}".format(self.feature_format.keys())) + + + def _build_df(self, data_dir): + """Build dataframe from data directory + + Args: + data_dir (str): structure data folder + - data_dir + - img1.jpg + - img1.txt + - ... + """ + data_dir = Path(data_dir) + + # img_paths = glob.glob("*") + glob.glob("*/*") + + img_paths = [ + path for path in list(data_dir.rglob("*")) + + if ".txt" not in str(path) and path.with_suffix(".txt").exists() and path.suffix.lower() in IMG_EXTENSION + ] + + + label_paths = [str(path.with_suffix(".txt")) for path in img_paths] + + + img_paths = [str(path) for path in img_paths] + + + + assert len(label_paths) == len(img_paths) + # remove empty txt + ids = [id for id in range(len(label_paths)) if len(read_txt(label_paths[id])) > 0] + label_paths = [label_paths[id] for id in ids] + img_paths = [img_paths[id] for id in ids] + + dataframe = pd.DataFrame.from_dict( + {"image_path": img_paths, "label": label_paths} + ) + return dataframe + + def build_dataloader_from_dataset( + self, + dataset, + processor, + device, + batch_size, + shuffle=True, + num_workers=4, + cache_file="./cache.pkl", + use_sampling=False, + ): + + if not os.path.exists(cache_file): + self._build_cache( + dataset, + processor, + cache_file=cache_file, + max_seq_length=self.cfg.max_seq_length, + ) + cache = self._load_cache(cache_file) + dataset = dataset.map( + self._prepare_data, + fn_kwargs={"cache": cache, "sampling": use_sampling}, + remove_columns=dataset.column_names, + features=self.feature_format, + batched=False, + batch_size=self.cfg.batch_size, + ) + + dataset.set_format(type="torch", device=device) + dataloader = torch.utils.data.DataLoader( + dataset, batch_size=batch_size, shuffle=shuffle, num_workers=num_workers + ) + return dataloader + + def build_dataloader_from_dir( + self, + data_dir, + processor, + device, + batch_size, + shuffle=True, + num_workers=4, + cache_file="./cache.pkl", + use_sampling=False, + ): + + dataset = self._build_dataset(data_dir) + dataloader = self.build_dataloader_from_dataset( + dataset, + processor, + device, + batch_size, + shuffle, + num_workers, + cache_file, + use_sampling, + ) + return dataloader + + def _build_dataset(self, data_dir): + df = self._build_df(data_dir) + dataset = Dataset.from_pandas(df) + logger.info(f"Load example for {data_dir}") + dataset = dataset.map(lambda example: self._load_example_info(example)) + return dataset + + def _build_cache(self, dataset, processor, max_seq_length, cache_file=""): + logger.info(f"Caching {cache_file}...") + cache = {} + for examples in tqdm(dataset): + encoding_inputs = self._cache_feature(examples, processor, max_seq_length) + cache[examples["image_path"]] = encoding_inputs + + with open(cache_file, "wb") as f: + pickle.dump(cache, f) + + def _load_cache(self, cache_file): + with open(cache_file, "rb") as f: + cache = pickle.load(f) + return cache + + def _prepare_data(self, example, cache, sampling): + encoded_inputs_windows = cache[example["image_path"]] + if len(encoded_inputs_windows) == 0: + raise Exception("Empty encoded_inputs_windows") + if sampling: + if random.random() < 0.6: + encoded_inputs = encoded_inputs_windows[-1] + else: + encoded_inputs = random.choice(encoded_inputs_windows) + else: + encoded_inputs = encoded_inputs_windows[-1] + for k, v in encoded_inputs.items(): + if k in ["image", "pixel_values"]: + encoded_inputs[k] = encoded_inputs[k][0] + return encoded_inputs + + def _cache_feature(self, example, processor, max_seq_length=512): + """Sampling (optional) + apply LayoutLMProcessor + + Args: + examples (dict): dict {'image_path', 'words', 'bbox', 'word_labels'} + max_seq_length (int, optional): _description_. Defaults to 512. + + Returns: + list[dict]: list encoding inputs + """ + + image = Image.open(example["image_path"]).convert("RGB") + batch_words = example["words"] + batch_boxes = example["bbox"] + batch_labels = example["word_labels"] + + window_size = self.cfg.max_num_words + slice_interval = self.cfg.slice_interval + + word_windows = sliding_windows(batch_words, window_size, slice_interval) + box_windows = sliding_windows(batch_boxes, window_size, slice_interval) + label_windows = sliding_windows(batch_labels, window_size, slice_interval) + + encoded_inputs = [] + for words, boxes, labels in zip(word_windows, box_windows, label_windows): + # Process examples + encoded_input = processor( + image, + padding="max_length", + truncation=True, + text=words, + boxes=boxes, + word_labels=labels, + max_length=max_seq_length, + ) + + encoded_inputs.append(encoded_input) + + # full page + encoded_input = processor( + image, + padding="max_length", + truncation=True, + text=batch_words, + boxes=batch_boxes, + word_labels=batch_labels, + max_length=max_seq_length, + ) + encoded_inputs.append(encoded_input) + + return encoded_inputs + + def _load_example_info(self, example, aug_prob=0.0): + """_summary_ + + Args: + example (_type_): _description_ + aug_prob (float, optional): _description_. Defaults to 0.0. + """ + + image_path = example["image_path"] + label_path = example["label"] + assert os.path.exists(image_path) + assert os.path.exists(label_path) + # try: + image = cv2.imread(image_path) + h, w, _ = image.shape + with open(label_path) as f: + lines = [line.replace("\n", "").replace("\r", "") for line in f.readlines()] + + words, boxes, labels = [], [], [] + # print(label_path) + for i, line in enumerate(lines): + x1, y1, x2, y2, text, label = line.split("\t") + box = [int(x1), int(y1), int(x2), int(y2)] + if text != " ": + words.append(text) + boxes.append(box) + labels.append(label) + + if aug_prob > 0: + p_words = perturbate_character(words, aug_prob) + logging.info("{} - {}".format(len(p_words), len(words))) + + # custom for sort boxes + items = { + 'boxes': boxes, + 'texts': words, + 'labels': labels + } + # boxes, words, labels = sort_words(boxes, words, labels) + sorted_items = sort_words(items) + boxes, words, labels = sorted_items['boxes'], sorted_items['texts'], sorted_items['labels'] + + # print(image_path) + # print(image_path) + labels = [self.cfg.classes.index(label) for label in labels] + if self.cfg.debug: + visualize_kie( + img=image, + boxes=boxes, + pred_labels=labels, + outdir="wordirs/debug_{}".format( + "val" if "train" not in image_path else "train" + ), + image_name=os.path.basename(image_path), + ) + + boxes = [normalize_box(box, width=w, height=h) for box in boxes] + + example["words"] = words + example["bbox"] = boxes # TODO: Check this + example["word_labels"] = labels + # except Exception as err: + # logger.info(f"Exception: {err} at image path: {example['image_path']}") + # example["words"] = [] + # example["bbox"] = [] # TODO: Check this + # example["word_labels"] = [] + return example diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/engine/__init__.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/engine/__init__.py new file mode 100755 index 0000000..3e88504 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/engine/__init__.py @@ -0,0 +1 @@ +from .predictor import Predictor diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/engine/predictor.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/engine/predictor.py new file mode 100755 index 0000000..e7f5441 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/engine/predictor.py @@ -0,0 +1,457 @@ +import logging +import time + +import cv2 +import numpy as np +from sdsvkie.utils.word_formation import merge_boxes +import torch +from easydict import EasyDict +from PIL import Image + +from sdsvkie.cfg import load_cfg +# from sdsvkie.models.layoutlm import LayoutLM +from sdsvkie.models.layoutlmv2 import LayoutLMv2 +from sdsvkie.models.ocr import OCREngine +from sdsvkie.utils import invoice_postprocess # invoice +from sdsvkie.utils import receipt_postprocess # receipt +from sdsvkie.utils import POSTPROCESS_FUNC +from sdsvkie.utils import (Word, construct_word_groups_to_kie_label, + normalize_box, sliding_windows, sort_words, + unnormalize_box, words_to_lines, + pdf_to_image) + + +logging.basicConfig(level=logging.INFO) +logger = logging.getLogger(__name__) + + +class Predictor: + def __init__(self, cfg, **kwargs) -> None: + """ + + Args: + cfg (dict / str): config + **kwargs: device=..., weights=..., text_det=..., text_reg=... + """ + + if isinstance(cfg, str): + cfg = load_cfg(cfg, kwargs) + self.cfg = EasyDict(cfg) + print(self.cfg) + + self.model = None + self.processor = None + self.ocr_engine = None + self.classes = self.cfg["classes"] + + self.max_num_words = self.cfg.max_num_words + self.model = None + self.processor = None + self.ocr_engine = None + + def _init_predictor(self, model=None, proccessor=None, ocr_engine=None): + + if self.cfg.device != "cpu" and not torch.cuda.is_available(): + logger.info("Can not found cuda, training with CPU!!!") + self.cfg.device = "cpu" + + if self.cfg["inference_weights"] is None: + logger.info( + "Not yet set value for inference weights, use weights instead!!!" + ) + if model is None: + self.model = LayoutLMv2._load_model(self.cfg) + if proccessor is None: + self.processor = LayoutLMv2._load_processor(self.cfg) + + if ocr_engine is None: + self.ocr_engine = OCREngine( + text_det=self.cfg["text_det"], + text_recog=self.cfg["text_reg"], + device=self.cfg["device"], + ) + + + def __call__(self, input , ocr_output=None, return_raw=False): + """Inference KIE - + Pipeline: Img -> OCR -> box + text (word-level) -> sort by x, y-axis -> LayoutLM -> Word formation -> result + + Args: + input (np.ndarray / str / pdf path): BGR image (cv2) + + Returns: + (dict): { + 'kie_raw_output': + 'kie_post_output': + 'end2end_results': (dict) : {kie_label : value} + } + """ + if self.model is None: + self._init_predictor() + #check single or multi images + if isinstance(input, np.ndarray): + final_out= self.predict_single_image(input, ocr_output=ocr_output, return_raw=return_raw) + elif isinstance(input, list): + items = [self.predict_single_image(im, ocr_output=ocr_output, return_raw=return_raw) for im in input] + final_out = self.aggregate_outputs(items) + else: #pdf + import time + t1 = time.time() + imgs = pdf_to_image(input) + print("1. pdf2img: ", round(time.time() - t1, 4)) + t2 = time.time() + items = [self.predict_single_image(im, ocr_output=ocr_output, return_raw=return_raw) for im in imgs] + final_out = self.aggregate_outputs(items) + print("2. kie: ", round(time.time() - t2, 4)) + print(f"3. full pipeline for {len(imgs)} pages: {round(time.time() - t1, 4)}") + return final_out + + def predict_single_image(self, img, ocr_output=None, return_raw=False): + + if ocr_output is None: + ocr_output = self.ocr_engine(img, extend_ratio=[0.1, 0.3], ratio_thr=5) # solve long box + # ocr_output = self.ocr_engine(img) + kie_input = self.prepare_inputs(img, ocr_output) + kie_output = self.predict(kie_input) + kie_post_output = self.postprocessing(kie_output) + formated_output = self.format_output(kie_post_output) + output = { + "kie_raw_output": kie_output if return_raw else None, # raw output from layoutlm model + "kie_post_output": kie_post_output if return_raw else None, # wordgroup + "end2end_results": formated_output, # field_key + field_value + } + return output + + def predict(self, inputs: dict): + """predict + + Args: + inputs (dict): format + { + 'image": PIL RGB, + 'boxes': list[], + 'texts' + } + + Returns: + list[Word]: list of Word object + """ + window_size = self.cfg.max_num_words + slice_interval = self.cfg.slice_interval + + image, batch_boxes, batch_words = ( + inputs["img"], + inputs["boxes"], + inputs["texts"], + ) + results = [] + non_norm_boxes = inputs['non_norm_boxes'] + if len(batch_boxes) == 0: + logger.info("Not found any words in image!!! Continue...") + return results + + text_windows = sliding_windows(batch_words, window_size, slice_interval) + box_windows = sliding_windows(batch_boxes, window_size, slice_interval) + # print([len(t) for t in text_windows]) + + out_boxes_windows = [] + # out_labels_windows = [] + out_logits_windows = [] + + for i in range(len(text_windows)): + words = text_windows[i] # len: MAX_N_WORDS + boxes = box_windows[i] + + # Preprocess + dummy_word_labels = [0] * len(words) + encoding = self.processor( + image, + text=words, + boxes=boxes, + word_labels=dummy_word_labels, + return_tensors="pt", + padding="max_length", + truncation=True, + max_length=self.cfg.max_seq_length, + ) + + label_ = encoding.pop('labels') + # Run model + for k, v in encoding.items(): + encoding[k] = v.to(self.cfg.device) + with torch.no_grad(): + output = self.model(**encoding) + + + logits = output.logits.squeeze() # seq_len * classes + predictions = output.logits.argmax(-1).squeeze().tolist() + token_boxes = encoding.bbox.squeeze().tolist() + + # Postprocess + # is_subword = (encoding["labels"] == -100).detach().cpu()[0] + is_subword = (label_ == -100).detach().cpu()[0] + logit_predictions = logits[torch.logical_not(is_subword), :] + true_boxes = torch.Tensor( + [ + unnormalize_box(box, image.size[0], image.size[1]) + for idx, box in enumerate(token_boxes) + if not is_subword[idx] + ] + ) + + # print("logit shape: ", logit_predictions.shape) + # print("box shape: ", true_boxes.shape) + # true_boxes = torch.Tensor( + # [ + # unnormalize_box(box, image.size[0], image.size[1]) + # for idx, box in enumerate(boxes) + # ] + # ) + out_boxes_windows.append(true_boxes) + out_logits_windows.append(logit_predictions) + + # merge output by average logits between overlap window + merged_out_boxes = out_boxes_windows[0] + merged_out_logit = out_logits_windows[0] + overlap = window_size - slice_interval + for i in range(1, len(out_boxes_windows)): + if overlap != 0: + prev_overlap_logits = merged_out_logit[-overlap:, :] + curr_overlap_logits = out_logits_windows[i][:overlap, :] + avg_overlap_logits = ( + prev_overlap_logits + curr_overlap_logits + ) / 2 + curr_logits = torch.cat( + [avg_overlap_logits, out_logits_windows[i][overlap:, :]], dim=0 + ) + merged_out_logit = torch.cat( + [merged_out_logit[:-overlap, :], curr_logits], dim=0 + ) + else: + merged_out_logit = torch.cat( + [merged_out_logit, out_logits_windows[i]], dim=0 + ) + + merged_out_boxes = torch.cat( + [merged_out_boxes, out_boxes_windows[i][overlap:, :]], dim=0 + ) + + # print(f"merged_out_logit={len(merged_out_logit)} - merged_out_boxes={len(merged_out_boxes)}") + # from IPython import embed; embed() + assert len(merged_out_logit) == len( + merged_out_boxes + ), f"{len(merged_out_logit)} # {len(merged_out_boxes)}" + predictions = merged_out_logit.argmax(-1).squeeze().tolist() + if not isinstance(predictions, list): + predictions = [predictions] + + + assert len(predictions) == len(batch_words), f"{len(predictions)} # {len(batch_words)}" + # for word_index in range(len(batch_words)): + for word_index, word in enumerate(batch_words): + word = batch_words[word_index] + # bndbox = [int(coord) for coord in merged_out_boxes[word_index]] + bndbox = non_norm_boxes[word_index] + kie_label = self.cfg.classes[predictions[word_index]] + results.append( + Word( + text=word, + bndbox=bndbox, + kie_label=kie_label, + conf_cls=inputs["recog_confs"][word_index] + ) + ) + + return results + + def postprocessing(self, words): + """Post processing for output of kie + - Merge wordgroup list for each field + + Args: + items (dict): _description_ + """ + list_lines, _ = words_to_lines(words) + list_word_group = [] + for line in list_lines: + for word_group in line.list_word_groups: + word_group.update_kie_label() + word_group.update_conf() + list_word_group.append(word_group) + + kie_dict = construct_word_groups_to_kie_label(list_word_group) + #receipt postprocess + if 'postprocess_type' in self.cfg and self.cfg.postprocess_type == "receipt_postprocess": + kie_dict = receipt_postprocess(kie_dict, words) + else: #invoice_postprocess + # kie_dict = invoice_postprocess(kie_dict) + kie_dict = self._postprocess_kie_wordgroups(kie_dict, doc_type=self.cfg.postprocess_type) + return kie_dict + + def format_output(self, kie_dict): + """ + Args: + kie_dict (dict) : format + { + 'field_name': list[Wordgroup] + } + + Returns: + (dict): format + { + 'field_name': { + 'box': list, + 'value': str, + 'conf': float + } + } + """ + end2end_results = {} + filtered_dict = {k:v for k,v in kie_dict.items() if "key" not in k} + for field_name, wg_list in filtered_dict.items(): + wg_list = [wg_list] if not isinstance(wg_list, list) else wg_list + + if len(wg_list) == 0: + text, conf, box = "", 0.0, [] + else: + text = " ".join([wg.text for wg in wg_list]).strip().replace("✪", " ") + conf = sum(wg.conf for wg in wg_list) / len(wg_list) + box = merge_boxes([wg.boundingbox for wg in wg_list]) + + end2end_results[field_name] = { + "box": box, + "value": text, + "conf": conf + } + + # add empty values for missing fields + for class_name in self.classes: + if "key" not in class_name and class_name not in end2end_results and class_name.lower() not in ['other', 'others']: + end2end_results[class_name] = { + "box": [], + "value": "", + "conf": 0.0 + } + + end2end_results = self._postprocess_recognized_text(end2end_results, doc_type=self.cfg.postprocess_type) + # sort by keys + end2end_results = dict(sorted(end2end_results.items())) + return end2end_results + + + def _postprocess_kie_wordgroups(self, result, doc_type, metadata=None): + """post process for wordgroup outputs + + Args: + result (dict): {'field_name': list[Wordgroup]} + doc_type (str): invoice / receipt + metadata (_type_, optional): _description_. Defaults to None. + + Returns: + _type_: _description_ + """ + for field_name in result.keys(): + if field_name not in POSTPROCESS_FUNC[doc_type]: + continue + postprocess_func = POSTPROCESS_FUNC[doc_type][field_name].get("wordgroup", None) + if postprocess_func is None: + continue + result[field_name] = postprocess_func(result[field_name], metadata={"field_name": field_name, "wg_res": result}) + return result + + def _postprocess_recognized_text(self, result, doc_type, metadata=None): + for field_name in result.keys(): + if field_name not in POSTPROCESS_FUNC[doc_type]: + continue + postprocess_func = POSTPROCESS_FUNC[doc_type][field_name].get("text", None) + if postprocess_func is None: + continue + result[field_name]["value"] = postprocess_func(result[field_name]['value'], metadata) + return result + + def prepare_inputs(self, img, ocr_output): + """Prepare input for KIE model + + Args: + img (np.ndarray): BGR image + ocr_output (dict): format + { + "img_path": img_path, + "img": image, + "boxes": boxes, + "texts": words, + "kie_labels": word_labels + } + """ + assert "boxes" in ocr_output, "boxes not exists in ocr_output" + assert "texts" in ocr_output, "texts not exists in ocr_output" + + # cv2 to PIL (RGB) + img = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB)) + w, h = img.size + texts = ocr_output["texts"] + boxes = ocr_output["boxes"] + recog_confs = ocr_output['recog_confs'] + det_confs = ocr_output['det_confs'] + texts = [text.replace(" ", "✪") for text in texts] # layoutlm will throw an error if the input has space characters + word_items = { + 'boxes': boxes, + 'texts': texts, + 'det_confs': det_confs, + 'recog_confs': recog_confs + } + sorted_word_items = sort_words(word_items) + (boxes, texts, det_confs, recog_confs) = ( + sorted_word_items['boxes'], + sorted_word_items['texts'], + sorted_word_items['det_confs'], + sorted_word_items['recog_confs'] + ) + non_norm_boxes = sorted_word_items['boxes'] + boxes = [normalize_box(box, width=w, height=h) for box in boxes] + out_item = { + "img": img, + "boxes": np.array(boxes), + "texts": texts, + "det_confs": det_confs, + "recog_confs": recog_confs, + "non_norm_boxes": non_norm_boxes + } + return out_item + + + + def aggregate_outputs(self, outs): + f"""Postprocess the outputs of the muliple pages + + Args: + outs (_type_): _description_ + + Returns: + output: (dict): final output + + """ + combine_out = { + 'kie_raw_output': [], + 'kie_post_output': [], + 'end2end_result_each_page': [], + 'end2end_results': None + } + + for idx, out in enumerate(outs): + combine_out['kie_raw_output'].append(out['kie_raw_output']) + combine_out['kie_post_output'].append(out['kie_post_output']) + combine_out['end2end_result_each_page'].append(out['end2end_results']) + + #merge end2end result + end2end_results = combine_out['end2end_result_each_page'][0] + + for page_id, end2end_results_page in enumerate(combine_out['end2end_result_each_page'][1:]): + for field_key, field_value in end2end_results_page.items(): + if "value" in end2end_results[field_key] \ + and (end2end_results[field_key]['value'] == "" or end2end_results[field_key]['value'] == "0"): + end2end_results[field_key] = field_value + combine_out['end2end_results'] = end2end_results + + return combine_out + \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/engine/trainer.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/engine/trainer.py new file mode 100755 index 0000000..3a92c5d --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/engine/trainer.py @@ -0,0 +1,260 @@ +import logging +import os +import time + +import torch +import wandb +from easydict import EasyDict +from sklearn.metrics import precision_recall_fscore_support +from terminaltables import AsciiTable +from torch.optim import AdamW +from torch.optim.lr_scheduler import LinearLR +from tqdm import tqdm + +from sdsvkie.datasets.base_dataset import BaseDataset +from sdsvkie.models.layoutlmv2 import LayoutLMv2 +from sdsvkie.models.layoutlm import LayoutLM +from sdsvkie.utils import yaml_save, get_info_env, get_logger +from transformers import get_scheduler + +# logging = logging.getlogging(__name__) +# logging.basicConfig(level=logging.INFO) + + + +class Trainer: + def __init__(self, cfg: dict): + self.cfg = EasyDict(cfg) + self.model = None + self.processor = None + self._init_trainer() + + def _init_trainer(self): + + if self.cfg.v3: + os.environ["TOKENIZERS_PARALLELISM"] = "false" + + if not os.path.exists(self.cfg.save_dir): + os.makedirs(self.cfg.save_dir, exist_ok=True) + + timestamp = time.strftime('%Y%m%d_%H%M%S', time.localtime()) + log_file = "{}/{}.log".format(self.cfg.save_dir, str(timestamp)) + self.logger = get_logger(log_file=log_file, log_level='INFO') + self.logger.info(self.cfg) + # self.logger.info(get_info_env()) + + if not torch.cuda.is_available(): + self.logger.info("Can not found cuda, training with CPU!!!") + self.cfg.device = "cpu" + + + + self.model = LayoutLMv2._load_model(self.cfg) + self.processor = LayoutLMv2._load_processor(self.cfg) + + self.model.to(self.cfg.device) + + if self.cfg.wandb: + wandb.init( + project=self.cfg.wandb, + ) + + def _build_dataloader(self, data_dir, cache_file, use_sampling=False): + base_dataset = BaseDataset(self.cfg) + dataloader = base_dataset.build_dataloader_from_dir( + data_dir=data_dir, + processor=self.processor, + device="cpu", + batch_size=self.cfg.batch_size, + num_workers=self.cfg.num_workers, + shuffle=False, + cache_file=cache_file, + use_sampling=use_sampling, + ) + return dataloader + + def val(self, val_dir=None): + val_dir = val_dir if val_dir is not None else self.cfg.val_dir + val_cache_file = os.path.splitext(val_dir)[0] + ".pkl" + val_dataloader = self._build_dataloader( + val_dir if val_dir is not None else self.cfg.val_dir, + cache_file=val_cache_file + ) + acc = self.val_on_dataloader(val_dataloader) + return acc + + def train(self, train_dir=None, val_dir=None): + self.logger.info("Building train dataloader...") + base_dataset = BaseDataset(self.cfg) + train_dir = train_dir if train_dir is not None else self.cfg.train_dir + val_dir = val_dir if val_dir is not None else self.cfg.val_dir + train_cache_file = os.path.splitext(train_dir)[0] + ".pkl" + val_cache_file = os.path.splitext(val_dir)[0] + ".pkl" + if self.cfg.sampling: + train_dataset = base_dataset._build_dataset(data_dir=train_dir) + train_dataloader = base_dataset.build_dataloader_from_dataset( + train_dataset, + batch_size=self.cfg.batch_size, + processor=self.processor, + device="cpu", + shuffle=True, + num_workers=self.cfg.num_workers, + cache_file=train_cache_file, + use_sampling=True, + ) + else: + train_dataloader = self._build_dataloader( + train_dir if train_dir is not None else self.cfg.train_dir, + cache_file=train_cache_file, + use_sampling=False, + ) + + self.logger.info("Building valid dataloader...") + val_dataloader = self._build_dataloader( + val_dir if val_dir is not None else self.cfg.val_dir, + cache_file= val_cache_file, + use_sampling=False, + ) + + self.logger.info( + f"Info dataset: train = {len(train_dataloader)}, test = {len(val_dataloader)}" + ) + + optimizer = AdamW(self.model.parameters(), lr=self.cfg.lr) + if self.cfg.scheduler: + # scheduler = torch.optim.lr_scheduler.OneCycleLR( + # optimizer, + # max_lr=self.cfg.lr, + # steps_per_epoch=len(train_dataloader), + # epochs=self.cfg.epochs, + # anneal_strategy='cos', + # pct_start=0.1, + # div_factor=25, #init lr = max_lr / div_factor + # final_div_factor=1e4, # min lr = init_lr / final_dev_factor + # ) + num_training_steps = self.cfg.epochs * len(train_dataloader) + scheduler = get_scheduler( + name=self.cfg.scheduler, + optimizer=optimizer, + num_warmup_steps=0, + num_training_steps=num_training_steps, + + ) + + if self.cfg.wandb: + wandb.config = dict(self.cfg) + + best_acc = 0.0 + best_epoch = 0 + yaml_save(os.path.join(self.cfg.save_dir, "config.yaml"), dict(self.cfg)) + for epoch in range(self.cfg.epochs): + + # sampling slice window + if ( + self.cfg.sampling and epoch != 0 and epoch % self.cfg.sampling == 0 + ): # sampling each cfg.sampling epochs + train_dataloader = base_dataset.build_dataloader_from_dataset( + train_dataset, + batch_size=self.cfg.batch_size, + processor=self.processor, + device="cpu", + shuffle=True, + num_workers=self.cfg.num_workers, + cache_file=train_cache_file, + use_sampling=True, + ) + + self.model.train() + self.logger.info(f"Epoch: {epoch}:") + + running_loss = 0.0 + + for batch in tqdm(train_dataloader): + # forward pass + batch = self._to_device(batch, self.cfg.device) + + outputs = self.model(**batch) + loss = outputs.loss + running_loss += loss.item() + # backward pass to get the gradients + loss.backward() + + # update + optimizer.step() + if self.cfg.scheduler: + scheduler.step() + optimizer.zero_grad() + + loss_avg = running_loss / len(train_dataloader) + self.logger.info(f"Epoch[{epoch}/{self.cfg.epochs}] - lr: {round(scheduler.get_last_lr()[0], 9) if self.cfg.scheduler else self.cfg.lr} - loss: {loss_avg}") + if self.cfg.wandb: + wandb.log({"train_loss": loss_avg}) + + # valid + if epoch >= self.cfg.eval_delay: + acc = self.val_on_dataloader(val_dataloader) + + if acc > best_acc: + self.model.save_pretrained(os.path.join(self.cfg.save_dir, "best")) + self.logger.info(f"Update best acc, prev best acc = {best_acc}, current best acc = {acc}") + best_acc = acc + best_epoch = epoch + + if epoch % self.cfg.save_weight_interval == 0: + self.model.save_pretrained( + os.path.join(self.cfg.save_dir, "epoch_{}".format(epoch)) + ) + + self.model.save_pretrained(os.path.join(self.cfg.save_dir, "last")) + self.logger.info(f"Best accuracy = {best_acc} at epoch {best_epoch}") + + def _to_device(self, batch, device): + batch = {k: v.to(device) for k, v in batch.items()} + return batch + + def val_on_dataloader(self, dataloader): + self.model.eval() + total, correct = 0, 0 + preds, truths = [], [] + + running_loss = 0.0 + for batch in tqdm(dataloader): + with torch.no_grad(): + batch = self._to_device(batch, self.cfg.device) + outputs = self.model(**batch) + + loss = outputs.loss + running_loss += loss.item() + predictions = outputs.logits.argmax(dim=2) + valid_samples = batch["labels"] != -100 + predictions = predictions[valid_samples] + batch_labels = batch["labels"][valid_samples] + + preds.extend(predictions.detach().cpu().numpy().tolist()) + truths.extend(batch_labels.detach().cpu().numpy().tolist()) + correct += (predictions == batch_labels).float().sum() + total += predictions.numel() + + loss_avg = running_loss / len(dataloader) + + p, r, f1, support = precision_recall_fscore_support(truths, preds) + # self.logger.info("shapeeee", p.shape) + table_data = [["Class", "P", "R", "F1", "#samples"]] + for c in range(len(self.cfg.classes)): + if c < p.shape[0]: + table_data.append([self.cfg.classes[c], p[c], r[c], f1[c], support[c]]) + continue + + f1_avg = sum(f1) / len(f1) + table = AsciiTable(table_data) + self.logger.info(table.table) + self.logger.info( + "Validation F1: {} - #samples: {} - #corrects: {}".format( + f1_avg, total, correct + ) + ) + + if self.cfg.wandb: + wandb.log({"val_loss": loss_avg, "f1": f1_avg}) + + return f1_avg diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/__init__.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/__init__.py new file mode 100755 index 0000000..e69de29 diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/cvat.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/cvat.py new file mode 100755 index 0000000..7d93788 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/cvat.py @@ -0,0 +1,671 @@ + + + + + + +import argparse +import glob +import json +import os +import xml.etree.ElementTree as ET + +import numpy as np +import tqdm +from sdsvkie.utils.word_formation import Box, check_iou +from pathlib import Path + +def read_txt(txt): + with open(txt, 'r', encoding='utf8') as f: + data = [line.strip() for line in f] + return data + +def write_txt(txt, data): + with open(txt, 'w', encoding='utf8') as f: + for line in data: + f.write(line + "\n") + + + +""" + +general json format: + + +python cvat.py --task pseudo --xml sample_cvat/annotations.xml --xml_out sample_cvat/annotations_out.xml --pseudo_path sample_cvat/pseudo.json + +""" + + + + + +""" + + +config for fwd +{ + "id": "OCR005_2", + "name": "Số Hợp đồng", + "type": "text", + "value": "33252663", + "page_num": 0, + "box": [192, 168, 220, 250] + +}, + +""" +# CONFIG = { +# "label": "field", + +# #edit here +# "attribute_names": ["type", "value", "id", "name"] # name of attribute in cvat label: text / checkbox +# } + + +CONFIG = { + "label": "word", + # "attribute_names": ["text", "kie_label"] # name of attribute in cvat label: text / checkbox + "attribute_names": [] +} + + + +class CVAT: + def __init__(self): + pass + + def create_xml_from_json(self, json_path, xml_in, xml_out): + """ + json data format: + { + "img_1.jpg": [ + { + "box": [x1, y1, x2, y2] + "label": str # (not required) + "attrib1": str, + "attrib2": str, + }, + { + "box": [x1, y1, x2, y2] + "label": str # (not required) + "attrib1": str, + "attrib2": str, + } + ... + ], + "img_2.jpg": [...] + } + """ + + data = self.read_json(json_path) + + + + tree = ET.parse(xml_in) + root = tree.getroot() + for img_item in root.iter("image"): + img_path = img_item.attrib['name'] + + img_data = data[img_path] + + for item in img_data: + et = ET.Element('box') + #default values + et.attrib['occluded']="0" + et.attrib['source']="manual" + et.attrib['z_order'] = "0" + + #overwrite values + if 'label' in item: + et.attrib['label'] = item['label'] + else: + et.attrib['label'] = CONFIG['label'] + + xmin, ymin, xmax, ymax = item['box'] + ( + et.attrib['xtl'], et.attrib['ytl'], + et.attrib['xbr'], et.attrib['ybr'] + ) = ( + str(xmin), str(ymin), + str(xmax), str(ymax) + ) + + for att_name in CONFIG['attribute_names']: + if att_name not in item: + continue + + att_et = ET.Element('atrribute') + att_et.attrib['name'] = att_name + att_et.text = item[att_name] + et.append(att_et) + + + img_item.append(et) + + tree.write(xml_out, encoding='utf8') + + + + def get_data_from_txt_dir(self, txt_dir, resever_parent_dir=False): + if resever_parent_dir: + txt_paths = glob.glob(txt_dir + "/*/*.txt") + else: + txt_paths = glob.glob(txt_dir + "/*.txt") + data = {} + for txt_path in txt_paths: + if resever_parent_dir: + txt_name = "/".join(txt_path.split("/")[-2:]) + else: + txt_name = os.path.basename(txt_path) + + + txt_data = read_txt(txt_path) + format_data = [] + for line in txt_data: + items = line.split("\t") + # assert len(items) == 6, "error get len = {} - {}".format(len(items), items) + + box = [int(float(x)) for x in items[:4]] + text = items[4] + + if len(items) == 6: + kie_label = items[5] + else: + kie_label = "word" + format_data.append( + { + 'box': box, + 'text': text, + 'label': kie_label + } + ) + data[txt_name] = format_data + + return data + + def get_data_from_txt_path(self, txt_path): + + txt_data = read_txt(txt_path) + format_data = [] + for line in txt_data: + items = line.split("\t") + assert len(items) == 6, "error get len = {} - {}".format(len(items), items) + box = [int(float(x)) for x in items[:4]] + text = items[4] + kie_label = items[5] + format_data.append( + { + 'box': box, + 'text': text, + 'label': kie_label + } + ) + return format_data + + def format_data_invoice(self, data): + + new_data = {} + for txt_name, value in data.items(): + items = [] + for item in value: + text = item['text'] + if "____kie_wordgroup" in text: + new_item = { + 'box': item['box'], + 'label': item['label'] + } + else: + + new_item = { + "box": item['box'], + 'text': "xxxxxx", + 'kie_label': item['label'], + 'label': "word" + } + + items.append(new_item) + new_data[txt_name] = items + return new_data + + + + + def create_xml_from_txt(self, txt_dir, xml_in, xml_out, skip_labels=[], resever_parent_dir=False): + """ + + """ + data = self.get_data_from_txt_dir(txt_dir, resever_parent_dir) + print(list(data.keys())) + + # for invoice + if len(skip_labels) > 0 and "word" in skip_labels: + data = self.format_data_invoice(data) + tree = ET.parse(xml_in) + root = tree.getroot() + count = 0 + for img_item in tqdm.tqdm(root.iter("image")): + count += 1 + img_path = img_item.attrib['name'] + + + txt_name = os.path.splitext(img_path)[0] + ".txt" + + img_data = data.get(txt_name, []) + # from IPython import embed; embed() + # break + if len(img_data) > 0: + # img_item.clear() + for child in img_item: + img_item.remove(child) + + for item in img_data: + et = ET.Element('box') + #default values + et.attrib['occluded']="0" + et.attrib['source']="manual" + et.attrib['z_order'] = "0" + + #overwrite values + + if 'label' in item: + if item['label'] in skip_labels: + continue + et.attrib['label'] = item['label'] + else: + et.attrib['label'] = CONFIG['label'] + + xmin, ymin, xmax, ymax = item['box'] + ( + et.attrib['xtl'], et.attrib['ytl'], + et.attrib['xbr'], et.attrib['ybr'] + ) = ( + str(xmin), str(ymin), + str(xmax), str(ymax) + ) + + for att_name in CONFIG['attribute_names']: + if att_name not in item: + continue + + att_et = ET.Element('atrribute') + att_et.attrib['name'] = att_name + att_et.text = item[att_name] + et.append(att_et) + + + img_item.append(et) + print("Num imgs: ", count) + tree.write(xml_out, encoding='utf8') + + def get_data_from_xml(self, xml, skip_labels=[]): + """ parse xml to dict + + + Args: + xml (str): cvat anno xml path + + Returns: + (dict): { + 'img_1.jpg': [ + 'kie_label': [xyxy] + ... + ], + 'img_2.jpg': ... + } + """ + anno_data = open(xml, encoding='utf8') + tree = ET.parse(anno_data) + root = tree.getroot() + data = {} + + for obj in tqdm.tqdm(root.iter("image")): + img_path = obj.attrib['name'] + img_data = [] + for box in obj.iter("box"): + box_label = box.attrib['label'] + if box_label in skip_labels: + continue + + #get coordinate + xmin, ymin, xmax, ymax = box.attrib['xtl'], box.attrib['ytl'], box.attrib['xbr'], box.attrib['ybr'] + xmin, ymin, xmax, ymax = int(float(xmin)), int(float(ymin)), int(float(xmax)), int(float(ymax)) + + item = { + box_label: [xmin, ymin, xmax, ymax] + } + img_data.append(item) + + data[img_path] = img_data + + return data + @staticmethod + def write_json(json_path, data): + with open(json_path, 'w', encoding='utf8') as f: + json.dump(data, f, ensure_ascii=False) + + + def read_json(self, json_path): + with open(json_path, 'r', encoding='utf8') as f: + data = json.load(f) + + return data + + def update_label_kie(self, txt_dir, json_path, out_dir): + if not os.path.exists(out_dir): + os.makedirs(out_dir, exist_ok=True) + data = self.read_json(json_path) + txt_paths = glob.glob(txt_dir + "/*.txt") + for txt_path in tqdm.tqdm(txt_paths): + ori_data = read_txt(txt_path) + + boxes = [] + + img_name = os.path.splitext(os.path.basename(txt_path))[0] + img_name = "_".join(img_name.split("_")[:-1]) + "_1" + ".jpg" + # img_name = os.path.splitext(os.path.basename(txt_path))[0] + ".jpg" + new_img_data = data[img_name] + for line in ori_data: + xmin, ymin, xmax, ymax, text, kie_label = line.strip().split("\t") + if "____kie_wordgroup" in text: + continue + xmin, ymin, xmax, ymax = int(xmin), int(ymin), int(xmax), int(ymax) + # box_word = [xmin, ymin, xmax, ymax] + new_kie_label = "other" + for label_info in new_img_data: + for label, box_wordgroup in label_info.items(): + # print(label, box_wordgroup) + box_word = Box( + xmin, ymin, xmax, ymax + ) + box_wordgroup = Box( + box_wordgroup[0], box_wordgroup[1], box_wordgroup[2],box_wordgroup[3] + ) + if check_iou(box1=box_word, box2=box_wordgroup, threshold=0.85): + new_kie_label = label + break + + if new_kie_label != "other": + break + + + new_box = Box( + xmin=xmin, + ymin=ymin, + xmax=xmax, + ymax=ymax, + label=text, + kie_label=new_kie_label + + ) + boxes.append(new_box) + + boxes = sorted(boxes, key=lambda box: [box.ymin, xmin]) + new_data = [ + "\t".join([str(box.xmin), str(box.ymin), str(box.xmax), str(box.ymax), box.label, box.kie_label]) + for box in boxes + ] + + + write_txt(os.path.join(out_dir, os.path.basename(txt_path)), new_data) + def _check_iou(self, box1, box2, threshold=0.9): + """_summary_ + + Args: + box1 (_type_): word box + box2 (_type_): line box + threshold (float, optional): _description_. Defaults to 0.9. + + Returns: + _type_: _description_ + """ + area1 = (box1[2] - box1[0]) * (box1[3] - box1[1]) + area2 = (box2[2] - box2[0]) * (box2[3] - box2[1]) + xmin_intersect = max(box1[0], box2[0]) + ymin_intersect = max(box1[1], box2[1]) + xmax_intersect = min(box1[2], box2[2]) + ymax_intersect = min(box1[3], box2[3]) + + + if xmax_intersect < xmin_intersect or ymax_intersect < ymin_intersect: + area_intersect = 0 + else: + area_intersect = (xmax_intersect - xmin_intersect) * ( + ymax_intersect - ymin_intersect + ) + # union = area1 + area2 - area_intersect + iou = area_intersect / area1 + return iou + # if iou > threshold: + # return True + # return False + + def _update_label_for_word(self, box, line_items, threshold=0.75, other_class='others'): + have_label = False + max_iou = -1 + for line_item in line_items: + # 465 901 664 940 + + curr_iou = self._check_iou(box, line_item['box'], threshold=threshold) + if curr_iou > threshold and curr_iou > max_iou: + + max_iou = curr_iou + kie_label = line_item['label'] + have_label = True + + # if box[0] == 465 and box[-1] == 940: + # print(box, curr_iou, kie_label, line_item) + # break + + if not have_label: + kie_label = other_class + return kie_label + + def update_label_kie_from_xml(self, txt_dir, xml, out_dir, skip_labels = [], line_to_word=False, other_class="others", resever_parent_dir=False): + if not os.path.exists(out_dir): + os.makedirs(out_dir, exist_ok=True) + + #read xml + xml_data = {} + anno_data = open(xml, encoding='utf8') + tree = ET.parse(anno_data) + root = tree.getroot() + # data = {} + + for obj in tqdm.tqdm(root.iter("image")): + img_path = obj.attrib['name'] + # img_data = [] + if not line_to_word: + img_data = {} + for box in obj.iter("box"): + box_label = box.attrib['label'] + if box_label in skip_labels: + continue + + #get coordinate + xmin, ymin, xmax, ymax = box.attrib['xtl'], box.attrib['ytl'], box.attrib['xbr'], box.attrib['ybr'] + box_int = int(float(xmin)), int(float(ymin)), int(float(xmax)), int(float(ymax)) + box_key = ",".join([str(x) for x in box_int]) + img_data[box_key] = box_label + + else: + img_data = [] + for box in obj.iter("box"): + box_label = box.attrib['label'] + if box_label in skip_labels: + continue + + #get coordinate + xmin, ymin, xmax, ymax = box.attrib['xtl'], box.attrib['ytl'], box.attrib['xbr'], box.attrib['ybr'] + box_int = int(float(xmin)), int(float(ymin)), int(float(xmax)), int(float(ymax)) + box_key = ",".join([str(x) for x in box_int]) + img_data.append( + { + 'box': box_int, + 'label': box_label + } + ) + xml_data[os.path.splitext(img_path)[0]] = img_data + + # print(xml_data) + if resever_parent_dir: + txt_paths = glob.glob(txt_dir + "/*/*.txt") + else: + txt_paths = glob.glob(txt_dir + "/*.txt") + updated_imgs = [] + for txt_path in tqdm.tqdm(txt_paths): + is_update = False + # print(txt_path) + ori_data = read_txt(txt_path) + # print(ori_data) + img_new_data = [] + if resever_parent_dir: + img_key = str(Path(txt_path).with_suffix('').relative_to(Path(txt_path).parent.parent)) # a/xyz + else: + img_key = os.path.splitext(os.path.basename(txt_path))[0] # xyz + if img_key not in xml_data: + print(txt_path) + continue + img_annoted_data = xml_data[img_key] + # print(img_key, img_annoted_data) + if not line_to_word: + + for line in ori_data: + xmin, ymin, xmax, ymax, text, kie_label = line.strip().split("\t") + if "____kie_wordgroup" in text: + continue + box_int = int(xmin), int(ymin), int(xmax), int(ymax) + box_key = ",".join([str(x) for x in box_int]) + + if box_key in img_annoted_data: + if kie_label != img_annoted_data[box_key]: + is_update.append(txt_path) + # print(kie_label, img_annoted_data[box_key]) + kie_label = img_annoted_data[box_key] + else: + kie_label = other_class + img_new_data.append("\t".join([xmin, ymin, xmax, ymax, text, kie_label])) + else: + + # print("ori_data: ", ori_data) + for line in ori_data: + # print(line) + items = line.strip().split("\t") + if len(items) == 5: + xmin, ymin, xmax, ymax, text = items + else: + xmin, ymin, xmax, ymax, text, label = items + + box_int = int(xmin), int(ymin), int(xmax), int(ymax) + kie_label = self._update_label_for_word(box_int, img_annoted_data, threshold=0.75, other_class=other_class) + + if label != kie_label: + print(kie_label, label) + is_update = True + img_new_data.append("\t".join([xmin, ymin, xmax, ymax, text, kie_label])) + if resever_parent_dir: + out_sub_dir = Path(out_dir) / Path(img_key).parts[-2] + if not out_sub_dir.exists(): + out_sub_dir.mkdir(parents=True) + # else: + # out_sub_dir = out_dir + # out_sub_dir = str(out_sub_dir) + write_txt(os.path.join(out_dir, img_key + ".txt"), img_new_data) + + if is_update: + updated_imgs.append(txt_path) + else: + print("No update: ", txt_path) + print("updated_imgs: ", list(set(updated_imgs))) + print("num updated_imgs: ", len(list(set(updated_imgs)))) + + + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument("--xml", type=str, default='annotations.xml') + parser.add_argument("--pseudo_path", type=str, default="pseudolabel.json") + parser.add_argument("--xml_out", type=str, default="annotations_out.xml") + parser.add_argument("--task", type=str, default='pseudo', help='pseudo / parse_data / update_txt / update_txt_from_xml') + parser.add_argument("--txt_in", type=str, default='txt_dir_in') + parser.add_argument("--txt_out", type=str, default='txt_dir_out') + parser.add_argument("--line_to_word", action='store_true') + parser.add_argument("--other_class", type=str, default='other') + parser.add_argument("--resever_parent_dir", action="store_true") + + args = parser.parse_args() + cvat = CVAT() + + if args.task == 'parse_data': + data = cvat.get_data_from_xml( + xml=args.xml + ) + CVAT.write_json(args.xml_out, data) + + elif args.task == 'pseudo_from_json': + + cvat.create_xml_from_json( + xml_in=args.xml, + xml_out=args.xml_out, + json_path=args.pseudo_path + ) + + elif args.task == 'pseudo_from_txt': + + cvat.create_xml_from_txt( + xml_in=args.xml, + xml_out=args.xml_out, + txt_dir=args.pseudo_path, + # skip_labels=['word'] + # skip_labels=[args.other_class], + resever_parent_dir=args.resever_parent_dir + ) + elif args.task == 'update_txt': + cvat.update_label_kie( + txt_dir=args.txt_in, + json_path=args.pseudo_path, + out_dir=args.txt_out + ) + + elif args.task == 'update_txt_from_xml': + cvat.update_label_kie_from_xml( + txt_dir=args.txt_in, + xml=args.xml, + out_dir=args.txt_out, + skip_labels = ['word'], + line_to_word=args.line_to_word, + other_class=args.other_class, + resever_parent_dir=args.resever_parent_dir + ) + else: + raise NotImplementedError(f"{args.task} not yet implemented") + + + + + +""" +python tools/cvat.py --task update_txt --txt_in /mnt/ssd1T/hoanglv/Projects/KIE/craw_data/output/synth_vnpt_r20/one_line_filtered --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/craw_data/output/synth_vnpt_r20/one_line_filtered --pseudo_path ../workdirs/data/vnpt_oneline/annotations.json + +python tools/cvat.py --task pseudo_from_txt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/visualize/xml/vnpt_r2/annotations.xml \ + --xml_out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/visualize/xml/vnpt_r2/annotations_out.xml \ + --pseudo_path /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/visualize/vnpt_r2_txt + +python tools/cvat.py --task pseudo_from_txt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/re_labeling/wild_batch_1_raw.xml \ + --xml_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/re_labeling/wild_batch_1_pseudo.xml \ + --pseudo_path /mnt/ssd1T/hoanglv/Projects/KIE/DATA/WildReceipt/re_labeling/batches/batch_1 + + +python tools/cvat.py --task update_txt_from_xml \ + --txt_in /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/visualize/vnpt_r2_txt \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/visualize/vnpt_r2.xml \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/visualize/vnpt_r2_done_txt + +python tools/cvat.py --task update_txt_from_xml \ + --txt_in /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/labeling/Pseudo/batch_2/Good/Food \ + --xml /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/labeling/Pseudo/batch_2/batch_2_food_done.xml \ + --txt_out /mnt/ssd1T/hoanglv/Projects/KIE/DATA/SDSAP_Invoice/processed/batch_2/Good/Food \ + --other_class Others +""" \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/gen_cvat_text_det.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/gen_cvat_text_det.py new file mode 100755 index 0000000..56cd3f1 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/gen_cvat_text_det.py @@ -0,0 +1,137 @@ +import cv2 +import glob +import os +import fitz +import json +import numpy as np +import pandas as pd +from time import time +import yaml +from tqdm.auto import tqdm +import xml.etree.ElementTree as ET +from sklearn.model_selection import StratifiedKFold + +# from textdetection.src.serve_model import Predictor as TextDetector + +FOLDER = "/mnt/ssd1T/tuanlv/06.KVUCombineStage/preprocess/data/invoices-receipts/SBT/nttmai_renamed/" +TXT_DIR = "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/pseudo_ocr/invoice_receipt_sbt" +OUT_FOLDER = "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/pseudo_ocr/sbt_batches" +ANN_OUT = "processed_textdet_batch%d.json" +N_BATCHES = 3 + +os.makedirs(OUT_FOLDER, exist_ok=True) + + +if __name__ == "__main__": + all_files = [] + doc_types = [] + for file_name in tqdm(sorted(os.listdir(FOLDER))): + try: + file_name_no_ext = file_name.split('.')[0] + all_files.append(file_name) + doc_type = "1" + doc_types.append(doc_type) + file_path = os.path.join(FOLDER, file_name) + + except Exception as ex: + print('image:', file_name, '. Error:', ex) + + df = pd.DataFrame({'file_name': all_files, 'doc_type': doc_types}) + + df = df[df.doc_type.isin(['1'])].reset_index(drop=True) + + kfold = StratifiedKFold(n_splits=N_BATCHES) + fold_num = 0 + for train_inds, val_inds in kfold.split(df, df['doc_type']): + df.loc[val_inds, 'fold'] = fold_num + fold_num+=1 + + df.to_csv(f'{OUT_FOLDER}/tmp.csv', index=False) + + text_detector = TextDetector(setting['text_detection']['setting'], "textdetection") + + for batch in range(N_BATCHES): + print(f"================== Batch {batch} ================") + fold_df = df.loc[df.fold == batch] + # tree = ET.parse(XML_IN) + # root = tree.getroot() + + # for image in root.findall('image'): + # root.remove(image) + with open('/home/sds/namnt/FWD_Data/coco_template.json', 'r') as f: + coco_annotations = json.load(f) + + count = 2 + img_id = 1 + ann_id = 1 + + all_images = [] + all_annotations = [] + + for row_num, row in tqdm(fold_df.iterrows(), total=len(fold_df)): + # try: + file_name = row['file_name'] + file_name_no_ext = file_name.split('.')[0] + doc_type = row['doc_type'] + file_path = os.path.join(FOLDER, file_name) + images = pdf2np_fitz(file_path, _type='fname') + + images, batch_boxes = text_detector(images) + for page_num, (img, boxes) in enumerate(zip(images, batch_boxes)): + os.makedirs(os.path.join(OUT_FOLDER, f"batch{batch}"), exist_ok=True) + out_img_path = os.path.join(OUT_FOLDER, f"batch{batch}", f"batch{batch}_{img_id:04d}_{file_name_no_ext}_{page_num}.jpg") + cv2.imwrite(out_img_path, img[:,:,::-1]) + H, W = img.shape[:2] + c_img = { + "id": int(img_id), + "width": W, + "height": H, + "file_name": os.path.join(f"batch{batch}", f"batch{batch}_{img_id:04d}_{file_name_no_ext}_{page_num}.jpg"), + "license": 0, + "flickr_url": "", + "coco_url": "", + "date_captured": 0 + } + all_images.append(c_img) + + for box in boxes: + x1,y1,x2,y2 = box + w, h = x2-x1, y2-y1 + c_ann = { + "id": int(ann_id), + "image_id": int(img_id), + "category_id": 1, + "segmentation": [], + "area": w*h, + "bbox": [x1,y1,w,h], + "iscrowd": 0, + "attributes": { + "occluded": False, + "rotation": 0.0 + } + } + all_annotations.append(c_ann) + ann_id += 1 + + img_id += 1 + # if count == 1: + # break + # else: + # count -= 1 + # except Exception as ex: + # print('image:', file_name, '. Error:', ex) + + coco_annotations['categories'] = [{ + "id": 1, + "name": "text", + "supercategory": "" + }] + coco_annotations['images'] = all_images + coco_annotations['annotations'] = all_annotations + with open(os.path.join(OUT_FOLDER, ANN_OUT%(batch)), 'w') as f: + json.dump(coco_annotations, f) + + # break + + + \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/infer.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/infer.py new file mode 100755 index 0000000..8141139 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/infer.py @@ -0,0 +1,144 @@ +""" +Use for eval, debug +""" +import argparse +import os +from copy import copy +from glob import glob +from pathlib import Path + +import cv2 +import tqdm + +from sdsvkie.cfg import load_cfg +from sdsvkie.engine import Predictor +from sdsvkie.utils import visualize_kie +from sdsvkie.utils.io_file import load_ocr_output, write_json, write_txt + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument("--cfg", type=str, default="sdsvkie/cfg/default.yaml") + parser.add_argument( + "--img", type=str, default="img.jpg", help="image path or directory" + ) + + # optional + parser.add_argument("--weights", type=str, default=None, required=False) + + parser.add_argument("--device", type=str, default=None, required=False) + + parser.add_argument( + "--text_det", type=str, default=None, required=False, help="image path or directory" + ) + parser.add_argument( + "--text_reg", type=str, default=None, required=False, help="image path or directory" + ) + parser.add_argument( + "--vis_out", type=str, default=None, required=False, help="visualize output directory" + ) + parser.add_argument("--txt_out", type=str, required=False, default=None) + parser.add_argument("--kie_wordgroup_out", required=False, action="store_true") + parser.add_argument("--e2e", type=str, required=False, default=None) + parser.add_argument("--not_use_ocr", required=False, action="store_true") + parser.add_argument("--parse_e2e", action='store_true', help="Parse end2end result from word label") + + args = parser.parse_args() + + + # print(cfg) + + predictor = Predictor(**vars(args)) + + + # cfg = load_cfg(args.cfg, vars(args)) + # predictor = Predictor(cfg) + + if args.txt_out: + if not os.path.exists(args.txt_out): + os.makedirs(args.txt_out, exist_ok=True) + + if args.e2e: + outdir_e2e = os.path.dirname(args.e2e) + if not os.path.exists(outdir_e2e): + os.makedirs(outdir_e2e, exist_ok=True) + + if os.path.isdir(args.img): + img_paths = glob(args.img + "/*") + print("Infence image dir, total imgs: {}".format(len(img_paths))) + else: + img_paths = [args.img] + + out_dict = {} + for img_path in tqdm.tqdm(img_paths): + + img = cv2.imread(img_path) + if img is None: + print("img is None: ", img_path) + continue + if args.not_use_ocr: + txt_path = str(Path(img_path).with_suffix(".txt")) + ocr_output = load_ocr_output(txt_path) + # print(len(ocr_output["boxes"])) + out = predictor(img, ocr_output=ocr_output, return_raw=True) + else: + out = predictor(img, return_raw=True) + + # visualize + if args.vis_out: + # from IPython import embed; embed() + out_kie = out["kie_raw_output"] + visualize_kie( + img, + boxes=[word.boundingbox for word in out_kie], + pred_labels=[word.kie_label for word in out_kie], + image_name=os.path.basename(img_path), + outdir=args.vis_out, + skip_classes=["other---"] + ) + + if args.txt_out: + txt_out_path = os.path.join( + args.txt_out, os.path.splitext(os.path.basename(img_path))[0] + ".txt" + ) + + out_kie = out["kie_raw_output"] + boxes = [word.boundingbox for word in out_kie] + pred_labels = [word.kie_label for word in out_kie] + texts = [word.text for word in out_kie] + + data = [] + + + if args.kie_wordgroup_out: + output = out["kie_post_output"] + # print(output) + # from IPython import embed; embed() + wordgroup_all_list = [] + for kie_label, wordgroup_list in output.items(): + if isinstance(wordgroup_list, list): + wordgroup_all_list.extend(wordgroup_list) + else: + wordgroup_all_list.append(wordgroup_list) + boxes = [word.boundingbox for word in wordgroup_all_list] + pred_labels = [word.kie_label for word in wordgroup_all_list] + texts = [word.text + "____kie_wordgroup" for word in wordgroup_all_list] + + for box, text, kie_label in zip(boxes, texts, pred_labels): + item = "\t".join([str(int(x)) for x in box]) + item = "\t".join([item, text, kie_label]) + data.append(item) + else: + for box, text, kie_label in zip(boxes, texts, pred_labels): + item = "\t".join([str(int(x)) for x in box]) + item = "\t".join([item, text, kie_label]) + data.append(item) + + write_txt(txt_out_path, data) + + if args.e2e: + + img_id = os.path.splitext(os.path.basename(img_path))[0] + out_dict[img_id] = out['end2end_results'] + + if args.e2e: + write_json(os.path.join(args.e2e), out_dict) diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/infer_e2e.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/infer_e2e.py new file mode 100755 index 0000000..507dc69 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/infer_e2e.py @@ -0,0 +1,122 @@ +""" +Use for deploy +""" +import argparse +import os +from glob import glob +from pathlib import Path + +import cv2 +import tqdm + +from sdsvkie.cfg import load_cfg +from sdsvkie.engine.predictor import Predictor +from sdsvkie.utils.io_file import write_json +from sdsvkie.utils import visualize_kie, IMG_EXT, PDF_EXT +import random +""" +python sdsvkie/tools/infer_e2e.py \ + --cfg /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/config.yaml \ + --weights /mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/invoice/06062023/best \ + --device "cuda:0" \ + --img /mnt/hdd2T/AICR/Projects/2023/Vietinbank_POC/Invoice_JPG/ \ + --e2e /mnt/hdd2T/AICR/Projects/2023/Vietinbank_POC/Invoice_KIE_Results/result.json + + +""" + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument("--cfg", type=str, default="sdsvkie/cfg/default.yaml") + parser.add_argument("--img", type=str, default="img.jpg", help="image path or directory") + parser.add_argument("--weights", type=str, default=None) + parser.add_argument("--text_det", type=str, default=None) + parser.add_argument("--device", type=str, default=None) + parser.add_argument("--e2e", type=str, default=None) + parser.add_argument("--vis", type=str, default=None) + + + args = parser.parse_args() + + # predictor = Predictor(cfg=cfg) + predictor = Predictor(**vars(args)) + + if args.e2e: + outdir_e2e = os.path.dirname(args.e2e) + if not os.path.exists(outdir_e2e): + os.makedirs(outdir_e2e, exist_ok=True) + + if os.path.isdir(args.img): + img_paths = sorted(glob(args.img + "/*")) + print("Infence image dir, total imgs: {}".format(len(img_paths))) + else: + img_paths = [args.img] + + out_dict = {} + + if "Others" in predictor.classes: + colors = { + "Store_name_value": (30,97,235), + "id": (28,175,6), + "Date_value": (241,26,242), + "Total_value": (255,0,0), + } + else: + colors = [ + ( + random.randint(0, 255), + random.randint(0, 255), + random.randint(0, 255), + ) + for _ in range(len(predictor.classes)) + ] + + + import time + + for img_path in tqdm.tqdm(img_paths): + print(img_path) + if Path(img_path).suffix.lower() in IMG_EXT: + img = cv2.imread(img_path) + if img is None: + print("img is None: ", img_path) + continue + elif Path(img_path).suffix.lower() in PDF_EXT: + img = img_path #pdf + else: + continue + # try: + out = predictor(img) + # except Exception as err: + # print(err, img_path) + # continue + + out_api = out['end2end_results'] + + if not args.e2e: + print(out_api) + else: + + img_id = os.path.splitext(os.path.basename(img_path))[0] + out_dict[img_id] = { + field_name: field_item['value'] for field_name, field_item in out_api.items() + } + + if args.vis: + + visualize_kie( + img, + boxes=[field_item['box'] for field_name, field_item in out_api.items() if len(field_item['box']) > 0], + pred_labels=[field_name for field_name, field_item in out_api.items() if len(field_item['box']) > 0], + image_name=os.path.basename(img_path), + outdir=args.vis, + colors=colors, + texts = [field_item['value'] for field_name, field_item in out_api.items() if len(field_item['box']) > 0] + ) + + if args.e2e: + write_json(os.path.join(args.e2e), out_dict) + + + + \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/parse_e2e.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/parse_e2e.py new file mode 100755 index 0000000..d8263cd --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/parse_e2e.py @@ -0,0 +1,72 @@ +""" +Use for eval, debug +""" +import argparse +import os +from glob import glob +from pathlib import Path + +from sdsvkie.utils.word_formation import Word +import tqdm + +from sdsvkie.engine import Predictor +from sdsvkie.utils.io_file import load_ocr_output, write_txt + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument("--cfg", type=str, default="sdsvkie/cfg/default.yaml") + parser.add_argument( + "--src", type=str, default="img.jpg / img_dir", help="image path or directory" + ) + parser.add_argument("--tgt", type=str, required=True, default=None) + + args = parser.parse_args() + + predictor = Predictor(args.cfg) + + + if not os.path.exists(args.tgt): + os.makedirs(args.tgt, exist_ok=True) + + txt_paths = glob(args.src + "/*.txt") + print("Total txt: {}".format(len(txt_paths))) + + + for txt_path in tqdm.tqdm(txt_paths): + ocr_output = load_ocr_output(txt_path) + + boxes, texts, labels = ocr_output['boxes'], ocr_output['texts'], ocr_output['labels'] + words = [] + for box, text, label in zip(boxes, texts, labels): + words.append( + Word( + text=text, + bndbox=box, + kie_label=label, + conf_cls=0.0 + ) + ) + + kie_output = predictor.postprocessing(words) + + + txt_out_path = str(Path(args.tgt) / Path(txt_path).name) + + + data = [] + + # print(output) + wordgroup_all_list = [] + for kie_label, wordgroup_list in kie_output.items(): + wordgroup_all_list.extend(wordgroup_list) + boxes = [word.boundingbox for word in wordgroup_all_list] + pred_labels = [word.kie_label for word in wordgroup_all_list] + texts = [word.text + "____kie_wordgroup" for word in wordgroup_all_list] + + for box, text, kie_label in zip(boxes, texts, pred_labels): + item = "\t".join([str(int(x)) for x in box]) + item = "\t".join([item, text, kie_label]) + data.append(item) + + + write_txt(txt_out_path, data) \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/postprocess_e2e_label.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/postprocess_e2e_label.py new file mode 100755 index 0000000..6593bb3 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/postprocess_e2e_label.py @@ -0,0 +1,72 @@ +import argparse +from sdsvkie.utils import read_json, yaml_load, write_json +from sdsvkie.utils.post_processing.invoice_post_processing import * +from sdsvkie.utils.post_processing.common_post_processing import normalize_number + + + +def postprocess_invoice(invoice_data): + if 'date' in invoice_data: + invoice_data['date'] = post_processing_datetime(invoice_data['date']) + + #### normalize number + number_fields = ['total_value', 'VAT_amount_value'] + for number_field in number_fields: + if number_field not in invoice_data: + continue + invoice_data[number_field] = normalize_number(invoice_data[number_field]) + if 'buyer_tax_code_value' in invoice_data: + invoice_data['buyer_tax_code_value'] = normalize_number(invoice_data['buyer_tax_code_value'], rerserve_minus=True) + if 'seller_tax_code_value' in invoice_data: + invoice_data['seller_tax_code_value'] = normalize_number(invoice_data['seller_tax_code_value'], rerserve_minus=True) + if "seller_mobile_value" in invoice_data: + invoice_data['seller_mobile_value'] = normalize_number(invoice_data['seller_mobile_value'], rerserve_minus=False, reserve_plus=True) + + + for field_name in invoice_data.keys(): + field_value = invoice_data[field_name] + field_value = field_value.replace("✪", " ") + field_value = field_value.replace("\t", " ") + field_value = re.sub(r"\s+", " ", field_value) + invoice_data[field_name] = field_value + + return invoice_data + + + + +def format_e2e_data(input_json, output_json, cfg): + cfg = yaml_load(cfg) + classes = cfg['classes'] + value_classes = [cls_name for cls_name in classes if "_key" not in cls_name and "other" not in cls_name] + print(value_classes) + in_data = read_json(input_json) + + out_data = {} + for img_id, img_data in in_data.items(): + + new_img_data = postprocess_invoice(img_data) + + + + for cls_value in value_classes: + if cls_value not in new_img_data: + new_img_data[cls_value] = "" + + + out_data[img_id] = new_img_data + + + write_json(data=out_data, json_path=output_json) + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument("--cfg", type=str) + parser.add_argument("--input", type=str, help="e2e label file path") + parser.add_argument("--out", type=str, help='postprocess e2e label') + + args = parser.parse_args() + + format_e2e_data(args.input, args.out, args.cfg) + + diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/run_ocr.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/run_ocr.py new file mode 100755 index 0000000..63e5435 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/run_ocr.py @@ -0,0 +1,84 @@ +import argparse +import glob +from pathlib import Path + +import cv2 +from tqdm import tqdm + +from sdsvkie.models.ocr import OCREngine +from sdsvkie.utils.visualize import visualize_ocr +from sdsvkie.utils.io_file import write_txt +from sdsvkie.utils.word_formation import sort_words + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + + parser.add_argument("--img", type=str) + parser.add_argument("--out_dir", type=str, default=None) + parser.add_argument("--device", type=str, default='cpu') + parser.add_argument("--reserve_parent_dir", action='store_true') + parser.add_argument("--only_text", action='store_true') + parser.add_argument("--out_txt", type=str, default=None) + parser.add_argument("--text_det", default="yolox-s-general-text-pretrain-20221226") + parser.add_argument("--text_recog", default="satrn-lite-general-pretrain-20230106") + + args = parser.parse_args() + ocr_engine = OCREngine(text_det=args.text_det, text_recog=args.text_recog, device=args.device) + + + if args.reserve_parent_dir: + paths = glob.glob(args.img + "/*/*") + else: + paths = glob.glob(args.img + "/*") + for path in tqdm(paths): + img = cv2.imread(path) + if img is None: + print(path) + continue + ocr_output = ocr_engine(img, extend_ratio=[0.1, 0.3], ratio_thr=5) + + if args.out_dir: + if args.reserve_parent_dir: + out_dir_img = Path(args.out_dir) / Path(path).parent.name + else: + out_dir_img = Path(args.out_dir) + if not out_dir_img.exists(): + out_dir_img.mkdir(parents=True) + + + visualize_ocr( + img = img, + boxes=ocr_output['boxes'], + texts=ocr_output['texts'], + image_name=str(Path(path).name), + outdir=str(out_dir_img) + ) + + if args.out_txt: + + + if args.reserve_parent_dir: + out_dir_txt = Path(args.out_txt) / Path(path).parent.name + else: + out_dir_txt = Path(args.out_txt) + if not out_dir_txt.exists(): + out_dir_txt.mkdir(parents=True) + + out_txt_path = out_dir_txt / Path(path).with_suffix(".txt").name + data = [] + if args.only_text: + out = sort_words(ocr_output) + text = " ".join(out['texts']) + data.append(text) + else: + + for box, text in zip(ocr_output['boxes'], ocr_output['texts']): + item = "\t".join([str(int(x)) for x in box]) + item = "\t".join([item, text]) + data.append(item) + write_txt(str(out_txt_path), data) + + + + + diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/train.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/train.py new file mode 100755 index 0000000..58b588d --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/train.py @@ -0,0 +1,27 @@ + +import argparse + +from sdsvkie.cfg import load_cfg +from sdsvkie.engine.trainer import Trainer + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument("--cfg", type=str, default="sdsvkie/cfg/default.yaml") + parser.add_argument("--device", type=str, default="cuda") + parser.add_argument("--save_dir", type=str, default="./workdirs/exp") + parser.add_argument("--wandb", action="store_true") + + + args = parser.parse_args() + # cfg = cfg2dict(args.cfg) + # cfg['device'] = args.device + # cfg['save_dir'] = args.save_dir + cfg = load_cfg(args.cfg, vars(args)) + print(cfg) + + if args.wandb: + cfg['wandb'] = "invoice" + + trainer = Trainer(cfg) + trainer.train() + diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/val.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/val.py new file mode 100755 index 0000000..2d83e5b --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/tools/val.py @@ -0,0 +1,20 @@ + +import argparse + +from sdsvkie.cfg import load_cfg +from sdsvkie.engine.trainer import Trainer + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument("--cfg", type=str, default="sdsvkie/cfg/default.yaml") + parser.add_argument("--device", type=str, default="cuda") + parser.add_argument("--weights", type=str, default=None) + + + args = parser.parse_args() + cfg = load_cfg(args.cfg, vars(args)) + + trainer = Trainer(cfg) + metric = trainer.val() + print(metric) + diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/__init__.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/__init__.py new file mode 100755 index 0000000..5bfd774 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/__init__.py @@ -0,0 +1,17 @@ +from .transform import normalize_box, unnormalize_box +from .augmentation import perturbate_character, sampling_data +from .io_file import yaml_load, yaml_save, read_json,write_json +from .visualize import visualize_kie, visualize_ocr +from .word_formation import ( + sliding_windows, Word_group, words_to_lines, + sort_words, Word, merge_boxes, merge_wordgroups, + distance_of_boxes, y_distance +) +from .post_processing import * +from .logger import get_logger +from .common import get_info_env +from .convert_pdf2image import pdf_to_image + + +IMG_EXT = ['.jpg', ".png", ".jpeg"] +PDF_EXT = [".pdf"] \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/augmentation.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/augmentation.py new file mode 100755 index 0000000..042b27d --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/augmentation.py @@ -0,0 +1,112 @@ +import math +import random + +VN_list_char = "aAàÀảẢãÃáÁạẠăĂằẰẳẲẵẴắẮặẶâÂầẦẩẨẫẪấẤậẬbBcCdDđĐeEèÈẻẺẽẼéÉẹẸêÊềỀểỂễỄếẾệỆfFgGhHiIìÌỉỈĩĨíÍịỊjJkKlLmMnNoOòÒỏỎõÕóÓọỌôÔồỒổỔỗỖốỐộỘơƠờỜởỞỡỠớỚợỢpPqQrRsStTuUùÙủỦũŨúÚụỤưƯừỪửỬữỮứỨựỰvVwWxXyYỳỲỷỶỹỸýÝỵỴzZ0123456789!#$%&()*+,-./:;<=>?@[\]^_`{|}~" + + +def perturbate_character(words: list, ratio=0.01): + # Algorithm + # Step 1: couting number of characters is words and sample the postion we want to perturbation + # ( words = ["abc", "lkdhf", "lfhdlsa", "akdjhf"] =>> total_char = 21, pertubation_position = [15,13,7]), these are the positions of perturbating chars in the concatenating string of words "abclkdhflfhdlsaakdjhf" + # start_pos = 0, ending_pos = 0 + # Step 2: with each word in words, calculate the start_position and ending_pos of word in the concatenating string + # if ending pos > pertubation_position[-1] => conduct perturbation and plus 1 to perturbation index, else => continue + # Loop 1: words[0], start_pos = 0 ,ending_pos= 3 <= pertubation_position[-1] =7 => continue + # Loop 2: + + total_char = sum(len(i) for i in words) + pertubation_positions = sorted( + random.sample(range(total_char), int(ratio * total_char)) + ) + # logging.info(pertubation_positions) + pos = 0 + start_pos = 0 + j = 0 + for i, word in enumerate(words): + if j == len(pertubation_positions): + break + start_pos = pos + pos += len(word) + # logging.info(start_pos,pos) + while pos > pertubation_positions[j]: + x = random.randint(0, 3) + fixing_pos = pertubation_positions[j] - start_pos + if x == 0: # append random char to the left + word = ( + word[:fixing_pos] + + VN_list_char[random.randint(0, len(VN_list_char) - 1)] + + word[fixing_pos:] + ) + + if x == 1: # append random char to the right + word = ( + word[: fixing_pos + 1] + + VN_list_char[random.randint(0, len(VN_list_char) - 1)] + + word[fixing_pos + 1 :] + ) + + if x == 2: # adjust to another random char at current position + word = ( + word[:fixing_pos] + + VN_list_char[random.randint(0, len(VN_list_char) - 1)] + + word[fixing_pos + 1 :] + ) + + if x == 3 and len(word) > 1: # delete char at current position + + word = word[:fixing_pos] + word[fixing_pos + 1 :] + + j += 1 + # logging.info(words[i], word) + words[i] = word + if j == len(pertubation_positions): + break + + return words + + +def sampling_data(words, boxes, labels, max_num_words=150, slice_interval=50): + # num_boxes = len(words) + # if num_boxes > max_num_words: + # slide = max_num_words // 2 + # num_batches = math.ceil(num_boxes / slide) + + # idx_batches = [i for i in range(num_batches)] + # idx_batch = random.choice(idx_batches) + # start_idx = slide * idx_batch + # words = words[start_idx:] + # normalized_word_boxes = normalized_word_boxes[start_idx:] + # word_labels = normalized_word_boxes[start_idx:] + + total_word = len(words) + window_size = max_num_words + text_windows = [ + words[i : i + window_size] for i in range(0, total_word, slice_interval) + ] + box_windows = [ + boxes[i : i + window_size] for i in range(0, total_word, slice_interval) + ] + label_windown = [ + labels[i : i + window_size] for i in range(0, total_word, slice_interval) + ] + + # assert all( + # [ + # len(_words) == len(boxes) + # for _words, boxes in zip(words, normalized_word_boxes) + # ] + # ) + # assert all( + # [ + # len(_words) == len(_word_labels) + # for _words, _word_labels in zip(words, word_labels) + # ] + # ) + sampling_idx = random.choice([i for i in range(len(text_windows))]) + sampling_words, sampling_boxes, sampling_labels = ( + text_windows[sampling_idx], + box_windows[sampling_idx], + label_windown[sampling_idx], + ) + + return sampling_idx, sampling_words, sampling_boxes, sampling_labels diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/common.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/common.py new file mode 100755 index 0000000..265b634 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/common.py @@ -0,0 +1,8 @@ +from torch.utils import collect_env + + +def get_info_env(): + return collect_env.get_pretty_env_info() + +def count_parameters(model): + return sum(p.numel() for p in model.parameters() if p.requires_grad) \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/convert_pdf2image.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/convert_pdf2image.py new file mode 100755 index 0000000..2ced06f --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/convert_pdf2image.py @@ -0,0 +1,166 @@ +import argparse +import glob +import os +import shutil +from pathlib import Path + +import fitz # PyMuPDF, imported as fitz for backward compatibility reasons +import numpy as np +from tqdm import tqdm +import cv2 +from pdf2image import convert_from_path + + +def convert_pdf2image(filename, out_dir, dpi=300, reserve_parent_dir=False, is_get_first_page=False): + """Convert and save to disk + + Args: + filename (_type_): _description_ + out_dir (_type_): _description_ + dpi (int, optional): _description_. Defaults to 300. + reserve_parent_dir (bool, optional): _description_. Defaults to False. + """ + out_dir = Path(out_dir) + filename = Path(filename) + filename_str = str(filename) + + if reserve_parent_dir: + parent_dir = filename.parent.name + out_dir = out_dir / parent_dir + + if not out_dir.exists(): + out_dir.mkdir(parents=True) + if ".txt" in str(filename).lower(): + return + if ".pdf" not in str(filename).lower(): + shutil.copy(filename, out_dir) + return + + + # doc = fitz.open(filename_str) # open document + # # zoom = 2 # zoom factor, standard: 72 dpi + + # # dpi = 300 + # zoom = dpi // 72 + # magnify = fitz.Matrix(zoom, zoom) + # for idx, page in enumerate(doc): + # pix = page.get_pixmap(matrix=magnify) # render page to an image + + # outpath = out_dir / Path(os.path.splitext(os.path.basename(filename))[0] + "_" + str(idx+1) + ".jpg") + # pix.pil_save(outpath) + try: + imgs = pdf_to_image(pdf=filename_str, is_get_first_page=is_get_first_page, dpi=dpi) + except: + print("Use v2: ", filename_str) + imgs = pdf_to_image_v2(pdf=filename_str, is_get_first_page=is_get_first_page, dpi=dpi) + print("Len img: ", len(imgs)) + for idx, img in enumerate(imgs): + outpath = str(out_dir / Path(os.path.splitext(os.path.basename(filename))[0] + "_" + str(idx+1) + ".jpg")) + + cv2.imwrite(img=img, filename=outpath) + + +def pdf_to_image_v2(pdf, dpi=300, is_get_first_page=False, max_page=1000): + """_summary_ + + Args: + pdf (_type_): _description_ + dpi (int, optional): _description_. Defaults to 300. + is_get_first_page (bool, optional): _description_. Defaults to False. + max_page (int, optional): _description_. Defaults to 1000. + + Raises: + NotImplementedError: _description_ + + Returns: + _type_: _description_ + """ + if isinstance(pdf, str): + if not os.path.exists(pdf): + print(f"Not found pdf path at {pdf}") + return [] + imgs = convert_from_path(pdf, dpi=dpi) # PILLOW + else: + raise NotImplementedError(f"Not yet implement for {type(pdf)} type !!!") + + + # zoom = dpi // 72 + # magnify = fitz.Matrix(zoom, zoom) + cv_imgs = [] + + for idx, img in enumerate(imgs): + img = img.convert("RGB") + cv_img = np.array(img) + cv_img = cv_img[:, :, ::-1].copy() + cv_imgs.append(cv_img) + if is_get_first_page or idx >= max_page: + break + return cv_imgs + + +def pdf_to_image(pdf, dpi=300, is_get_first_page=False, max_page=1000): + """_summary_ + + Args: + pdf (_type_): _description_ + dpi (int, optional): _description_. Defaults to 300. + is_get_first_page (bool, optional): _description_. Defaults to False. + max_page (int, optional): _description_. Defaults to 1000. + + Raises: + NotImplementedError: _description_ + + Returns: + _type_: _description_ + """ + if isinstance(pdf, str): + if not os.path.exists(pdf): + print(f"Not found pdf path at {pdf}") + return [] + doc = fitz.open(pdf) # open document + elif isinstance(pdf, bytes): + doc = fitz.open(stream=pdf, filetype='pdf') + else: + raise NotImplementedError(f"Not yet implement for {type(pdf)} type !!!") + + + zoom = dpi // 72 + magnify = fitz.Matrix(zoom, zoom) + imgs = [] + + for idx, page in enumerate(doc): + pix = page.get_pixmap(matrix=magnify) # render page to an image + + im = np.frombuffer(pix.samples, dtype=np.uint8).reshape(pix.h, pix.w, pix.n) + im = np.ascontiguousarray(im[..., [2, 1, 0]]) # rgb to bgr + imgs.append(im) + if is_get_first_page or idx >= max_page: + break + return imgs + + +if __name__ == "__main__": + + parser = argparse.ArgumentParser() + parser.add_argument("--pdf_dir", type=str) + parser.add_argument("--out_dir", type=str) + parser.add_argument("--reserve_parent_dir", action='store_true') + args = parser.parse_args() + + paths = glob.glob(args.pdf_dir + "/*") \ + + glob.glob(args.pdf_dir + "/*/*") \ + + glob.glob(args.pdf_dir + "/*/*/*") + # + glob.glob(args.pdf_dir + "/*") + print(f"Total pdf paths in {args.pdf_dir}: {len(paths)} ") + + error_pdfs = [] + for path in tqdm(paths): + path = str(path) + try: + convert_pdf2image(path, args.out_dir, reserve_parent_dir=args.reserve_parent_dir) + except Exception as err: + print(err, path) + error_pdfs.append(path) + continue + print("Total error pdfs: ", len(error_pdfs)) + print(error_pdfs) \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/data_preprocessing/cvat_utils.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/data_preprocessing/cvat_utils.py new file mode 100755 index 0000000..222700c --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/data_preprocessing/cvat_utils.py @@ -0,0 +1,90 @@ +from typing import List +import random + +def gen_random_color(): + red = random.randint(0, 255) + green = random.randint(0, 255) + blue = random.randint(0, 255) + + # combine the values into a hexadecimal color code + color_code = "#{:02x}{:02x}{:02x}".format(red, green, blue) + return color_code + +def gen_raw_label(labels: List[str]): + """gen raw label for cvat tool + + { + "name": "no_key", + "color": "#33ddff", + "type": "any", + "attributes": [] + }, + + Args: + labels (List[str]): _description_ + """ + raw_label = [] + for label in labels: + item = { + "name": label, + "color": gen_random_color(), + "type": "any", + "attributes": [] + } + raw_label.append(item) + + return raw_label + + + +if __name__ == "__main__": + labels = [ + # id invoice + 'no_key', # số hóa đơn + 'no_value', + 'form_key', # mẫu số hóa đơn + 'form_value', + 'serial_key', # số kí hiệu hoá đơn + 'serial_value', + 'date', + + # seller info + 'seller_company_name_key', + 'seller_company_name_value', + 'seller_tax_code_key', + 'seller_tax_code_value', + 'seller_address_value', + 'seller_address_key', + 'seller_mobile_key', + 'seller_mobile_value', + + # Not yet support seller_bank_no, seller_bank_name + # 'seller_name_key', + # 'seller_name_value', + # 'seller_company_name_value', -> seller_name_value + + # buyer info + 'buyer_name_key', + 'buyer_name_value', + 'buyer_company_name_value', + 'buyer_company_name_key', + 'buyer_tax_code_key', + 'buyer_tax_code_value', + 'buyer_address_key', + 'buyer_address_value', + 'buyer_mobile_key', + 'buyer_mobile_value', + + # money info + 'VAT_amount_key', + 'VAT_amount_value', + 'total_key', + 'total_value', + 'total_in_words_key', + 'total_in_words_value', + + 'other', + ] + + raw_label = gen_raw_label(labels) + print(raw_label) \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/data_preprocessing/invoice_data.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/data_preprocessing/invoice_data.py new file mode 100755 index 0000000..1081e18 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/data_preprocessing/invoice_data.py @@ -0,0 +1,87 @@ + +import os +import glob +import json +import os +import shutil + +def read_txt(txt): + with open(txt, 'r', encoding='utf8') as f: + data = [line.strip() for line in f] + return data + +def write_txt(txt, data): + with open(txt, 'w', encoding='utf8') as f: + for line in data: + f.write(line + "\n") + +def write_json(json_path, data): + with open(json_path, 'w', encoding='utf8') as f: + json.dump(data, f, ensure_ascii=False) + + +def read_json(json_path): + with open(json_path, 'r', encoding='utf8') as f: + data = json.load(f) + + return data + +def create_template_info(data_dir, json_out): + outputs ={} + txt_paths = sorted(glob.glob(data_dir + "/*.txt")) + + for txt_path in txt_paths: + txt_name = os.path.basename(txt_path) + txt_data = read_txt(txt_path) + wordgroups = [item for item in txt_data if "____kie_wordgroup seller_company_name_value" in item] + num_line_company = len(wordgroups) + outputs[txt_name] = num_line_company + write_json(json_out, outputs) + + +def filter_data(template_file, data_file, img_dir, txt_dir, output): + template_data = read_json(template_file) + data = read_json(data_file) + + new_data = [] + for txt_name, num_wordgroup_line in template_data.items(): + id = txt_name.split("_type99_")[0] + for txt_name_target, num_wordgroup_target_line in data.items(): + id_target = txt_name_target.split("_type99_")[0] + # print(id, id_target, id_target != id) + if id_target != id: + # print(id_target, id) + continue + if num_wordgroup_line != num_wordgroup_target_line: + continue + + new_data.append(txt_name_target) + + new_data = sorted(list(set(new_data))) + print(new_data[:5]) + # return new_data + + if not os.path.exists(output): + os.makedirs(output, exist_ok=True) + + for txt_name in new_data: + img_path = os.path.join(img_dir, txt_name.replace(".txt", ".jpg")) + shutil.copy(img_path, output) + shutil.copy(os.path.join(txt_dir, txt_name), output) + + + + +if __name__ == "__main__": + target_dir = "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/visualize/vnpt_one_line_r20_txt" + template_dir = "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/visualize/vnpt_one_line_txt" + output_dir = "/mnt/ssd1T/hoanglv/Projects/KIE/craw_data/output/synth_vnpt_r20/one_line_filtered" + img_target_dir = "/mnt/ssd1T/hoanglv/Projects/KIE/craw_data/output/synth_vnpt_r20/one_line" + out_template_json = "vnpt_template.json" + out_target_json = "vnpt_r20.json" + create_template_info(template_dir, out_template_json) + create_template_info(target_dir, out_target_json) + + new_data = filter_data(out_template_json, out_target_json,img_target_dir, target_dir, output_dir) + print("Total after filter: ", len(new_data)) + diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/data_preprocessing/vnpt_r20.json b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/data_preprocessing/vnpt_r20.json new file mode 100755 index 0000000..f0fb391 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/data_preprocessing/vnpt_r20.json @@ -0,0 +1 @@ +{"invoice_vnpt_id10_type99_1.txt": 1, "invoice_vnpt_id10_type99_10.txt": 1, "invoice_vnpt_id10_type99_11.txt": 1, "invoice_vnpt_id10_type99_12.txt": 1, "invoice_vnpt_id10_type99_13.txt": 1, "invoice_vnpt_id10_type99_14.txt": 1, "invoice_vnpt_id10_type99_15.txt": 1, "invoice_vnpt_id10_type99_16.txt": 1, "invoice_vnpt_id10_type99_17.txt": 1, "invoice_vnpt_id10_type99_18.txt": 1, "invoice_vnpt_id10_type99_19.txt": 2, "invoice_vnpt_id10_type99_2.txt": 1, "invoice_vnpt_id10_type99_20.txt": 1, "invoice_vnpt_id10_type99_3.txt": 2, "invoice_vnpt_id10_type99_4.txt": 1, "invoice_vnpt_id10_type99_5.txt": 1, "invoice_vnpt_id10_type99_6.txt": 1, "invoice_vnpt_id10_type99_7.txt": 1, "invoice_vnpt_id10_type99_8.txt": 1, "invoice_vnpt_id10_type99_9.txt": 1, "invoice_vnpt_id11_type99_1.txt": 1, "invoice_vnpt_id11_type99_10.txt": 1, 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+ "name": "word", + "color": "#83e070", + "type": "any", + "attributes": [ + { + "name": "text", + "input_type": "text", + "mutable": false, + "values": ["x"] + }, + { + "name": "kie_label", + "input_type": "text", + "mutable": false, + "values": ["x"] + } + ] + }, + { + "name": "no_key", + "color": "#cf04f1", + "type": "any", + "attributes": [] + }, + { + "name": "no_value", + "color": "#0a01ce", + "type": "any", + "attributes": [] + }, + { + "name": "form_key", + "color": "#bfe920", + "type": "any", + "attributes": [] + }, + { + "name": "form_value", + "color": "#ac3436", + "type": "any", + "attributes": [] + }, + { + "name": "serial_key", + "color": "#706724", + "type": "any", + "attributes": [] + }, + { + "name": "serial_value", + "color": "#7a9b4b", + "type": "any", + "attributes": [] + }, + { + "name": "date", + "color": "#23f0e9", + "type": "any", + "attributes": [] + }, + { + "name": "seller_company_name_key", + "color": "#f47ccc", + "type": "any", + "attributes": [] + }, + { + "name": "seller_company_name_value", + "color": "#9c9c73", + "type": "any", + "attributes": [] + }, + { + "name": "seller_tax_code_key", + "color": "#afa0fa", + "type": "any", + "attributes": [] + }, + { + "name": "seller_tax_code_value", + "color": "#6e7352", + "type": "any", + "attributes": [] + }, + { + "name": "seller_address_value", + "color": "#121512", + "type": "any", + "attributes": [] + }, + { + "name": "seller_address_key", + "color": "#188735", + "type": "any", + "attributes": [] + }, + { + "name": "seller_mobile_key", + "color": "#7387fd", + "type": "any", + "attributes": [] + }, + { + "name": "seller_mobile_value", + "color": "#325bf1", + "type": "any", + "attributes": [] + }, + { + "name": "buyer_name_key", + "color": "#a5b431", + "type": "any", + "attributes": [] + }, + { + "name": "buyer_name_value", + "color": "#e63dcc", + "type": "any", + "attributes": [] + }, + { + "name": "buyer_company_name_value", + "color": "#e9bf0b", + "type": "any", + "attributes": [] + }, + { + "name": "buyer_company_name_key", + "color": "#a8d921", + "type": "any", + "attributes": [] + }, + { + "name": "buyer_tax_code_key", + "color": "#1d8f4f", + "type": "any", + "attributes": [] + }, + { + "name": "buyer_tax_code_value", + "color": "#e638c6", + "type": "any", + "attributes": [] + }, + { + "name": "buyer_address_key", + "color": "#74afe5", + "type": "any", + "attributes": [] + }, + { + "name": "buyer_address_value", + "color": "#1518dc", + "type": "any", + "attributes": [] + }, + { + "name": "buyer_mobile_key", + "color": "#13b1cd", + "type": "any", + "attributes": [] + }, + { + "name": "buyer_mobile_value", + "color": "#c49d59", + "type": "any", + "attributes": [] + }, + { + "name": "VAT_amount_key", + "color": "#69c945", + "type": "any", + "attributes": [] + }, + { + "name": "VAT_amount_value", + "color": "#77c3be", + "type": "any", + "attributes": [] + }, + { + "name": "total_key", + "color": "#d1353a", + "type": "any", + "attributes": [] + }, + { + "name": "total_value", + "color": "#246976", + "type": "any", + "attributes": [] + }, + { + "name": "total_in_words_key", + "color": "#45a8b5", + "type": "any", + "attributes": [] + }, + { + "name": "total_in_words_value", + "color": "#d800df", + "type": "any", + "attributes": [] + }, + { + "name": "other", + "color": "#ba0fbd", + "type": "any", + "attributes": [] + } +] \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/eval_kie.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/eval_kie.py new file mode 100755 index 0000000..65e806a --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/eval_kie.py @@ -0,0 +1,479 @@ +import argparse +import re +from difflib import SequenceMatcher + +from rapidfuzz.distance import Levenshtein +from terminaltables import AsciiTable + +from sdsvkie.cfg import load_cfg +from sdsvkie.utils.io_file import read_json, write_json +from pathlib import Path + + +def is_type_list(x, type): + + if not isinstance(x, list): + return False + + return all(isinstance(item, type) for item in x) + + +def cal_true_positive_char(pred, gt): + """Calculate correct character number in prediction. + Args: + pred (str): Prediction text. + gt (str): Ground truth text. + Returns: + true_positive_char_num (int): The true positive number. + """ + + all_opt = SequenceMatcher(None, pred, gt) + true_positive_char_num = 0 + for opt, _, _, s2, e2 in all_opt.get_opcodes(): + if opt == "equal": + true_positive_char_num += e2 - s2 + else: + pass + return true_positive_char_num + + +def post_processing(text, lowercase=False): + """ + - Remove special characters and extra spaces + """ + + text = re.sub( + r"[^aAàÀảẢãÃáÁạẠăĂằẰẳẲẵẴắẮặẶâÂầẦẩẨẫẪấẤậẬbBcCdDđĐeEèÈẻẺẽẼéÉẹẸêÊềỀểỂễỄếẾệỆfFgGhHiIìÌỉỈĩĨíÍịỊjJkKlLmMnNoOòÒỏỎõÕóÓọỌôÔồỒổỔỗỖốỐộỘơƠờỜởỞỡỠớỚợỢpPqQrRsStTuUùÙủỦũŨúÚụỤưƯừỪửỬữỮứỨựỰvVwWxXyYỳỲỷỶỹỸýÝỵỴzZ0123456789 ]", + " ", + text, + ) + text = re.sub(r"\s\s+", " ", text) + text = text.strip() + + if lowercase: + text = text.lower() + + return text + + +def count_matches(pred_texts, gt_texts, use_ignore=True): + """Count the various match number for metric calculation. + Args: + pred_texts (list[str]): Predicted text string. + gt_texts (list[str]): Ground truth text string. + Returns: + match_res: (dict[str: int]): Match number used for + metric calculation. + """ + match_res = { + "gt_char_num": 0, + "pred_char_num": 0, + "true_positive_char_num": 0, + "gt_word_num": 0, + "match_word_num": 0, + "match_word_ignore_case": 0, + "match_word_ignore_case_symbol": 0, + "match_kie": 0, + "match_kie_ignore_case": 0, + } + # comp = re.compile('[^A-Z^a-z^0-9^\u4e00-\u9fa5]') + # comp = re.compile('[]') + norm_ed_sum = 0.0 + + gt_texts_for_ned_word = [] + pred_texts_for_ned_word = [] + for pred_text, gt_text in zip(pred_texts, gt_texts): + if gt_text == pred_text: + match_res["match_word_num"] += 1 + match_res["match_kie"] += 1 + gt_text_lower = gt_text.lower() + pred_text_lower = pred_text.lower() + if gt_text_lower == pred_text_lower: + match_res["match_word_ignore_case"] += 1 + + # gt_text_lower_ignore = comp.sub('', gt_text_lower) + # pred_text_lower_ignore = comp.sub('', pred_text_lower) + if use_ignore: + gt_text_lower_ignore = post_processing(gt_text_lower) + pred_text_lower_ignore = post_processing(pred_text_lower) + else: + gt_text_lower_ignore = gt_text_lower + pred_text_lower_ignore = pred_text_lower + + if gt_text_lower_ignore == pred_text_lower_ignore: + match_res["match_kie_ignore_case"] += 1 + + gt_texts_for_ned_word.append(gt_text_lower_ignore.split(" ")) + pred_texts_for_ned_word.append(pred_text_lower_ignore.split(" ")) + + match_res["gt_word_num"] += 1 + + norm_ed = Levenshtein.normalized_distance( + pred_text_lower_ignore, gt_text_lower_ignore + ) + # if norm_ed > 0.1: + # print(gt_text_lower_ignore, pred_text_lower_ignore, sep='\n') + # print("-"*20) + norm_ed_sum += norm_ed + + # number to calculate char level recall & precision + match_res["gt_char_num"] += len(gt_text_lower_ignore) + match_res["pred_char_num"] += len(pred_text_lower_ignore) + true_positive_char_num = cal_true_positive_char( + pred_text_lower_ignore, gt_text_lower_ignore + ) + match_res["true_positive_char_num"] += true_positive_char_num + + normalized_edit_distance = norm_ed_sum / max(1, len(gt_texts)) + match_res["ned"] = normalized_edit_distance + + # NED for word-level + norm_ed_word_sum = 0.0 + # print(pred_texts_for_ned_word[0]) + unique_words = list( + set( + [x for line in pred_texts_for_ned_word for x in line] + + [x for line in gt_texts_for_ned_word for x in line] + ) + ) + preds = [ + [unique_words.index(w) for w in pred_text_for_ned_word] + for pred_text_for_ned_word in pred_texts_for_ned_word + ] + truths = [ + [unique_words.index(w) for w in gt_text_for_ned_word] + for gt_text_for_ned_word in gt_texts_for_ned_word + ] + for pred_text, gt_text in zip(preds, truths): + norm_ed_word = Levenshtein.normalized_distance(pred_text, gt_text) + # if norm_ed_word < 0.2: + # print(pred_text, gt_text) + norm_ed_word_sum += norm_ed_word + + normalized_edit_distance_word = norm_ed_word_sum / max(1, len(gt_texts)) + match_res["ned_word"] = normalized_edit_distance_word + + return match_res + + +def eval_ocr_metric(pred_texts, gt_texts, metric="acc"): + """Evaluate the text recognition performance with metric: word accuracy and + 1-N.E.D. See https://rrc.cvc.uab.es/?ch=14&com=tasks for details. + Args: + pred_texts (list[str]): Text strings of prediction. + gt_texts (list[str]): Text strings of ground truth. + metric (str | list[str]): Metric(s) to be evaluated. Options are: + - 'word_acc': Accuracy at word level. + - 'word_acc_ignore_case': Accuracy at word level, ignoring letter + case. + - 'word_acc_ignore_case_symbol': Accuracy at word level, ignoring + letter case and symbol. (Default metric for academic evaluation) + - 'char_recall': Recall at character level, ignoring + letter case and symbol. + - 'char_precision': Precision at character level, ignoring + letter case and symbol. + - 'one_minus_ned': 1 - normalized_edit_distance + In particular, if ``metric == 'acc'``, results on all metrics above + will be reported. + Returns: + dict{str: float}: Result dict for text recognition, keys could be some + of the following: ['word_acc', 'word_acc_ignore_case', + 'word_acc_ignore_case_symbol', 'char_recall', 'char_precision', + '1-N.E.D']. + """ + assert isinstance(pred_texts, list) + assert isinstance(gt_texts, list) + assert len(pred_texts) == len(gt_texts) + + assert isinstance(metric, str) or is_type_list(metric, str) + if metric == "acc" or metric == ["acc"]: + metric = [ + "word_acc", + "word_acc_ignore_case", + "word_acc_ignore_case_symbol", + "char_recall", + "char_precision", + "one_minus_ned", + ] + metric = set([metric]) if isinstance(metric, str) else set(metric) + + # supported_metrics = set([ + # 'word_acc', 'word_acc_ignore_case', 'word_acc_ignore_case_symbol', + # 'char_recall', 'char_precision', 'one_minus_ned', 'one_minust_ned_word' + # ]) + # assert metric.issubset(supported_metrics) + + match_res = count_matches(pred_texts, gt_texts) + eps = 1e-8 + eval_res = {} + + if "char_recall" in metric: + char_recall = ( + 1.0 * match_res["true_positive_char_num"] / (eps + match_res["gt_char_num"]) + ) + eval_res["char_recall"] = char_recall + + if "char_precision" in metric: + char_precision = ( + 1.0 + * match_res["true_positive_char_num"] + / (eps + match_res["pred_char_num"]) + ) + eval_res["char_precision"] = char_precision + + if "word_acc" in metric: + word_acc = 1.0 * match_res["match_word_num"] / (eps + match_res["gt_word_num"]) + eval_res["word_acc"] = word_acc + + if "word_acc_ignore_case" in metric: + word_acc_ignore_case = ( + 1.0 * match_res["match_word_ignore_case"] / (eps + match_res["gt_word_num"]) + ) + eval_res["word_acc_ignore_case"] = word_acc_ignore_case + + if "word_acc_ignore_case_symbol" in metric: + word_acc_ignore_case_symbol = ( + 1.0 + * match_res["match_word_ignore_case_symbol"] + / (eps + match_res["gt_word_num"]) + ) + eval_res["word_acc_ignore_case_symbol"] = word_acc_ignore_case_symbol + + if "one_minus_ned" in metric: + + eval_res["1-N.E.D"] = 1.0 - match_res["ned"] + + if "one_minus_ned_word" in metric: + + eval_res["1-N.E.D_word"] = 1.0 - match_res["ned_word"] + + if "line_acc_ignore_case_symbol" in metric: + line_acc_ignore_case_symbol = ( + 1.0 * match_res["match_kie_ignore_case"] / (eps + match_res["gt_word_num"]) + ) + eval_res["line_acc_ignore_case_symbol"] = line_acc_ignore_case_symbol + + if "line_acc" in metric: + word_acc_ignore_case_symbol = ( + 1.0 * match_res["match_kie"] / (eps + match_res["gt_word_num"]) + ) + eval_res["line_acc"] = word_acc_ignore_case_symbol + + for key, value in eval_res.items(): + eval_res[key] = float("{:.4f}".format(value)) + + return eval_res + + +def eval_kie(pred_e2e_path, gt_e2e_path, kie_labels=[], skip_labels=[], log_failure_case=None, norm_failcase=False): + # assert ".json" in pred_e2e_path and ".json" in gt_e2e_path, "only support json type" + + f = None + if log_failure_case: + log_failure_case = Path(log_failure_case) + log_failure_case_dir = log_failure_case.parent + if not log_failure_case_dir.exists(): + log_failure_case_dir.mkdir(parents=True) + + if isinstance(gt_e2e_path, str): + gt_e2e = read_json(gt_e2e_path) + else: + gt_e2e = gt_e2e_path + if isinstance(pred_e2e_path, str): + preds_e2e = read_json(pred_e2e_path) + else: + preds_e2e = pred_e2e_path + + KIE_LABELS_WITH_ONLY_VALUES = [ + class_name + for class_name in kie_labels + if "_key" not in class_name + and "other" not in class_name + and class_name not in skip_labels + ] + + pred_texts_dict = {label: [] for label in KIE_LABELS_WITH_ONLY_VALUES} + gt_texts_dict = {label: [] for label in KIE_LABELS_WITH_ONLY_VALUES} + + results = {label: 1 for label in KIE_LABELS_WITH_ONLY_VALUES} + # print(KIE_LABELS_WITH_ONLY_VALUES) + + fail_cases = {} + for img_id in preds_e2e.keys(): + fail_cases[img_id] = {} + pred_items = preds_e2e[img_id] + gt_items = gt_e2e[img_id] + + if not pred_items: + pred_items = { + class_name: "" for class_name in KIE_LABELS_WITH_ONLY_VALUES + } + + + for class_name, text_gt in gt_items.items(): + if class_name in skip_labels: + continue + # if class_name == 'seller_name_value': + # print(gt_items) + if class_name not in pred_items: + text_pred = "" + else: + text_pred = pred_items[class_name] + + if norm_failcase: + _text_pred = post_processing(text_pred, lowercase=True) + _text_gt = post_processing(text_gt, lowercase=True) + + else: + _text_pred = text_pred + _text_gt = text_gt + + if _text_pred != _text_gt: + fail_cases[img_id][class_name] = { + 'pred': _text_pred, + 'gt': _text_gt + } + + + pred_texts_dict[class_name].append(text_pred) + gt_texts_dict[class_name].append(text_gt) + + if log_failure_case: + with open(log_failure_case, 'w', encoding='utf8') as f: + write_json(log_failure_case, fail_cases) + + for class_name in KIE_LABELS_WITH_ONLY_VALUES: + pred_texts = pred_texts_dict[class_name] + gt_texts = gt_texts_dict[class_name] + result = eval_ocr_metric( + pred_texts, + gt_texts, + metric=[ + "one_minus_ned", + "line_acc_ignore_case_symbol", + "line_acc", + "one_minus_ned_word", + ], + ) + results[class_name] = { + "1-ned": result["1-N.E.D"], + "1-ned-word": result["1-N.E.D_word"], + "line_acc": result["line_acc"], + "line_acc_ignore_case_symbol": result["line_acc_ignore_case_symbol"], + "samples": len(pred_texts), + } + + # avg reusults + sum_1_ned = sum( + [ + results[class_name]["1-ned"] * results[class_name]["samples"] + for class_name in KIE_LABELS_WITH_ONLY_VALUES + ] + ) + sum_1_ned_word = sum( + [ + results[class_name]["1-ned-word"] * results[class_name]["samples"] + for class_name in KIE_LABELS_WITH_ONLY_VALUES + ] + ) + + sum_line_acc = sum( + [ + results[class_name]["line_acc"] * results[class_name]["samples"] + for class_name in KIE_LABELS_WITH_ONLY_VALUES + ] + ) + sum_line_acc_ignore_case_symbol = sum( + [ + results[class_name]["line_acc_ignore_case_symbol"] + * results[class_name]["samples"] + for class_name in KIE_LABELS_WITH_ONLY_VALUES + ] + ) + + total_samples = sum( + [results[class_name]["samples"] for class_name in KIE_LABELS_WITH_ONLY_VALUES] + ) + results["avg_all"] = { + "1-ned": round(sum_1_ned / total_samples, 4), + "1-ned-word": round(sum_1_ned_word / total_samples, 4), + "line_acc": round(sum_line_acc / total_samples, 4), + "line_acc_ignore_case_symbol": round( + sum_line_acc_ignore_case_symbol / total_samples, 4 + ), + "samples": total_samples, + } + + table_data = [ + [ + "class_name", + "1-NED", + "1-N.E.D_word", + "line-acc", + "line_acc_ignore_case_symbol", + "#samples", + ] + ] + for class_name in results.keys(): + # if c < p.shape[0]: + table_data.append( + [ + class_name, + results[class_name]["1-ned"], + results[class_name]["1-ned-word"], + results[class_name]["line_acc"], + results[class_name]["line_acc_ignore_case_symbol"], + results[class_name]["samples"], + ] + ) + + table = AsciiTable(table_data) + print(table.table) + return results + + +if __name__ == "__main__": + + # gt_e2e = "/mnt/ssd1T/hoanglv/Projects/KIE/DATA/test_end2end/test_e2e.json" + + # # pred_e2e = "/mnt/ssd1T/hoanglv/Projects/KIE/TokenClassification_invoice/workdirs/runs/pred_e2e.json" + # # pred_e2e = "/mnt/ssd1T/hoanglv/Projects/KIE/TokenClassification_invoice/workdirs/runs/infer/layoutxlm-base-31-03-2023-maxwords150_samplingv2/pred_e2e.json" + # # pred_e2e = "/mnt/ssd1T/hoanglv/Projects/KIE/TokenClassification_invoice/workdirs/runs/infer/kie_e2e_pred_17-10-2022-maxwords150_samplingv2_rm_dup_boxes/pred_e2e.json" + # # pred_e2e = "/mnt/ssd1T/hoanglv/Projects/KIE/TokenClassification_invoice/workdirs/runs/infer/kie_e2e_pred_17-10-2022-maxwords150_samplingv2/pred_e2e.json" + + # # pred_e2e = "/home/sds/hoanglv/Projects/TokenClassification_invoice/runs/infer/kie_e2e_pred_14-10-2022_2/pred_e2e.json" + # pred_e2e = "/mnt/ssd1T/hoanglv/Projects/KIE/sdsvkie/workdirs/e2e/test_17_10_2022_last_use_ocr_merge_use_label.json" + + parser = argparse.ArgumentParser() + parser.add_argument("--cfg", type=str) + parser.add_argument("--pred", type=str, help="predict json file path") + parser.add_argument("--gt", type=str, help="ground truth json file path") + parser.add_argument("--log_failure_case", type=str, default=None, help="log_failure_case path") + parser.add_argument("--norm_failcase", action='store_true') + args = parser.parse_args() + + cfg = load_cfg(args.cfg) + kie_labels = cfg['classes'] + + # res = eval_kie(pred_e2e, gt_e2e, skip_labels=["buyer_mobile_value"]) + # print(res) + result = eval_kie( + pred_e2e_path=args.pred, + gt_e2e_path=args.gt, + kie_labels=kie_labels, + skip_labels=["Others", "other"], + log_failure_case=args.log_failure_case, + norm_failcase=args.norm_failcase + ) + + print("Path of validation dataset: /mnt/ssd1T/hoanglv/Projects/KIE/DATA/dev_model/Invoice/processed/test/PV2/invoice_kie_validation") + print("Number of validation dataset: ", result[list(result.keys())[0]]['samples']) + print("Evaluation metric: NLD") + print("Target level: ") + print("Archieved level: ") + print("Verification result: PASS") + +"""" + + +""" \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/io_file.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/io_file.py new file mode 100755 index 0000000..6e7727c --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/io_file.py @@ -0,0 +1,102 @@ +import json +import re +from pathlib import Path + +import yaml + + +def yaml_load(file="data.yaml", append_filename=False): + """ + Load YAML data from a file. + Args: + file (str, optional): File name. Default is 'data.yaml'. + append_filename (bool): Add the YAML filename to the YAML dictionary. Default is False. + Returns: + dict: YAML data and file name. + """ + with open(file, errors="ignore", encoding="utf-8") as f: + s = f.read() # string + + # Remove special characters + if not s.isprintable(): + s = re.sub( + r"[^\x09\x0A\x0D\x20-\x7E\x85\xA0-\uD7FF\uE000-\uFFFD\U00010000-\U0010ffff]+", + "", + s, + ) + + # Add YAML filename to dict and return + return ( + {**yaml.safe_load(s), "yaml_file": str(file)} + if append_filename + else yaml.safe_load(s) + ) + + +def yaml_save(file="data.yaml", data=None): + """ + Save YAML data to a file. + Args: + file (str, optional): File name. Default is 'data.yaml'. + data (dict, optional): Data to save in YAML format. Default is None. + Returns: + None: Data is saved to the specified file. + """ + file = Path(file) + if not file.parent.exists(): + # Create parent directories if they don't exist + file.parent.mkdir(parents=True, exist_ok=True) + + with open(file, "w") as f: + # Dump data to file in YAML format, converting Path objects to strings + yaml.safe_dump( + {k: str(v) if isinstance(v, Path) else v for k, v in data.items()}, + f, + sort_keys=False, + allow_unicode=True, + ) + + +def write_txt(txt, data, mode="w"): + with open(txt, mode, encoding="utf8") as f: + for line in data: + f.write(line + "\n") + + +def read_txt(txt): + with open(txt, "r", encoding="utf8") as f: + data = [line.strip() for line in f] + return data + + +def write_json(json_path, data, sort_keys=True): + with open(json_path, "w", encoding="utf8") as f: + json.dump(data, f, ensure_ascii=False, sort_keys=sort_keys) + + +def read_json(json_path): + with open(json_path, "r", encoding="utf8") as f: + data = json.load(f) + return data + + + +def load_ocr_output(txt_path): + with open(txt_path) as f: + lines = [line.replace("\n", "").replace("\r", "") for line in f.readlines()] + words, boxes, labels = [], [], [] + for i, line in enumerate(lines): + if len(line.split("\t")) == 6: + x1, y1, x2, y2, text, label = line.split("\t") + else: + x1, y1, x2, y2, text = line.split("\t") + label = None + + x1, y1, x2, y2 = int(x1), int(y1), int(x2), int(y2) + box = [x1, y1, x2, y2] + if text != " ": + words.append(text) + boxes.append(box) + labels.append(label) + + return {"boxes": boxes, "texts": words, 'labels': labels} diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/logger.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/logger.py new file mode 100755 index 0000000..642ba90 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/logger.py @@ -0,0 +1,48 @@ +import os +import sys +import logging +import functools + +logger_initialized = {} + +@functools.lru_cache() +def get_logger(name='root', log_file=None, log_level=logging.DEBUG): + """Initialize and get a logger by name. + If the logger has not been initialized, this method will initialize the + logger by adding one or two handlers, otherwise the initialized logger will + be directly returned. During initialization, a StreamHandler will always be + added. If `log_file` is specified a FileHandler will also be added. + Args: + name (str): Logger name. + log_file (str | None): The log filename. If specified, a FileHandler + will be added to the logger. + log_level (int): The logger level. Note that only the process of + rank 0 is affected, and other processes will set the level to + "Error" thus be silent most of the time. + Returns: + logging.Logger: The expected logger. + """ + logger = logging.getLogger(name) + if name in logger_initialized: + return logger + for logger_name in logger_initialized: + if name.startswith(logger_name): + return logger + + formatter = logging.Formatter( + '[%(asctime)s] %(name)s %(levelname)s: %(message)s', + datefmt="%Y/%m/%d %H:%M:%S") + + stream_handler = logging.StreamHandler(stream=sys.stdout) + stream_handler.setFormatter(formatter) + logger.addHandler(stream_handler) + if log_file is not None: + log_file_folder = os.path.split(log_file)[0] + os.makedirs(log_file_folder, exist_ok=True) + file_handler = logging.FileHandler(log_file, 'a', encoding='utf8') + file_handler.setFormatter(formatter) + logger.addHandler(file_handler) + + logger.setLevel(log_level) + logger_initialized[name] = True + return logger \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/post_processing/__init__.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/post_processing/__init__.py new file mode 100755 index 0000000..7a6df84 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/post_processing/__init__.py @@ -0,0 +1,4 @@ +from .common_post_processing import * +from .invoice_post_processing import * +from .receipt_post_processing import * +from .hardcoded_postprocess_funcs import * \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/post_processing/common_post_processing.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/post_processing/common_post_processing.py new file mode 100755 index 0000000..f5f4017 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/post_processing/common_post_processing.py @@ -0,0 +1,129 @@ + +import re +from datetime import datetime +from sdsvkie.utils import Word_group + + +YEAR_START = 2000 +def construct_word_groups_to_kie_label(list_word_groups: list): + kie_dict = dict() + + for wg in list_word_groups: + if wg.kie_label.lower() in ['other', 'others']: + continue + if wg.kie_label not in kie_dict: + kie_dict[wg.kie_label] = [wg] + else: + kie_dict[wg.kie_label].append(wg) + + return kie_dict + + +def near(word_group1: Word_group, word_group2: Word_group): + min_height = min( + word_group1.boundingbox[3] - word_group1.boundingbox[1], + word_group2.boundingbox[3] - word_group2.boundingbox[1], + ) + overlap = min(word_group1.boundingbox[3], word_group2.boundingbox[3]) - max( + word_group1.boundingbox[1], word_group2.boundingbox[1] + ) + + if overlap > 0: + return True + if abs(overlap / min_height) < 1.5: + print("near enough", abs(overlap / min_height), overlap, min_height) + return True + return False + + +def normalize_number(text_str: str, reserve_dot=False, reserve_plus=False, reserve_minus=False): + """ + Normalize a string of numbers by removing non-numeric characters + + """ + assert isinstance(text_str, str), "input must be str" + reserver_chars = "" + if reserve_dot: + reserver_chars += ".," + if reserve_plus: + reserver_chars += "+" + if reserve_minus: + reserver_chars += "-" + regex_fomula = "[^0-9{}]".format(reserver_chars) + normalized_text_str = re.sub(r"{}".format(regex_fomula), "", text_str) + return normalized_text_str + + +def normalize_number_wordgroup(word_group, reserve_dot=False, reserve_plus=False, reserve_minus=False): + word_group.text = normalize_number(word_group.text, reserve_dot=reserve_dot, reserve_plus=reserve_plus, reserve_minus=reserve_minus) + return word_group + +def tax_code_processing(tax_code_raw: str): + """ + + """ + if len(tax_code_raw.replace(' ', '')) != 13 or (len(tax_code_raw.replace(' ', '')) != 14 and "-" not in tax_code_raw): # to remove the first/last number dupicated + tax_code_raw = tax_code_raw.split(' ') + tax_code_raw = sorted(tax_code_raw, key=lambda x: len(x), reverse=True)[0] + return tax_code_raw.replace(' ', '') + +def normalize_tax_wordgroup(word_group, reserve_dot=False, reserve_plus=False, reserve_minus=False): + print("before: ", word_group.text) + word_group.text = tax_code_processing(word_group.text) + print("after: ", word_group.text) + word_group.text = normalize_number(word_group.text, reserve_dot=reserve_dot, reserve_plus=reserve_plus, reserve_minus=reserve_minus) + return word_group + + +def _date_format(date_string): + """Format date string according format dd/MM/yyyy""" + date_string = ( + date_string.replace("ngay ", "") + .replace(" thang ", "/") + .replace(" nam ", "/") + ) + day, month, year = date_string.split("/") + day = day.rjust(2, "0") + month = month.rjust(2, "0") + year = f"20{year}" if len(year) == 2 else year + + # Check valid year + try: + _ = datetime(year=int(year), month=int(month), day=int(day)) + if int(year) > YEAR_START: + return "/".join([day, month, year]) + except: + print("Date is invalid", date_string) + + return None + +def get_date(list_date): + """Regex get date""" + + list_date = [ + _date_format(date.group(0)) + for date in list_date + # if _date_format(date.group(0)) is not None + ] + list_date = [ + date for date in list_date if date is not None + ] + return list_date + + +def merge_multi_page_results(result_pages): + """Merge the result of the multiple pages + + Args: + results (list[dict]): list of result dict of each page + """ + if len(result_pages) == 0: + return {} + + result = result_pages[0] + for result_page in result_pages[1:]: + for field_name, field_value in result_page.items(): + if field_name not in result: + result[field_name] = field_value + + return result diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/post_processing/hardcoded_postprocess_funcs.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/post_processing/hardcoded_postprocess_funcs.py new file mode 100755 index 0000000..f559f46 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/post_processing/hardcoded_postprocess_funcs.py @@ -0,0 +1,280 @@ +import re +import numpy as np + +from sdsvkie.utils.post_processing import near +from sdsvkie.utils.post_processing.common_post_processing import normalize_number_wordgroup, tax_code_processing +from sdsvkie.utils.post_processing.post_processing_datetime import post_processing_datetime +from sdsvkie.utils import merge_boxes, Word_group, merge_wordgroups, distance_of_boxes, y_distance +from sdsvkie.utils.post_processing.receipt_post_processing import is_wg_same_line + + +__all__ = ["POSTPROCESS_FUNC"] + + +class CommonPostprocessing: + r"""Functions to postprocess fields + + Notes: + * I/O formats for text postprocessing functions must be the same + * I/O formats for box postprocessing functions must be the same + """ + re_number_pattern = '[0-9]' + re_not_number_pattern = '[^0-9]' + re_not_staff_code = '[^a-zA-Z0-9]' + re_char_pattern = '[a-zA-Z]' + re_not_char_pattern = '[^a-zA-Z]' + re_not_phone_pattern = '[^0-9+]' + re_not_tax_pattern = '[^0-9-]' + re_remove_extra_space = '\s+' + + + def remove_numbers(text, metadata): + result = re.sub(CommonPostprocessing.re_not_name_pattern, "", text) + + return result + + def remove_nan(text, metadata): + r"""Get number characters only""" + result = re.sub(CommonPostprocessing.re_not_number_pattern, "", text) + + return result + + + def remove_not_phone(text, metadata): + r"""Get phone number characters only""" + result = re.sub(CommonPostprocessing.re_not_phone_pattern, "", text) + + return result + + def remove_not_tax(text, metadata): + r"""Get tax number characters only""" + # print("before: ", text) + # text = tax_code_processing(text) + # print("after: ", text) + res = re.sub('[^0-9- ]', "", text) + res = res.strip() + num_spaces = res.count(" ") + + # duplicate with 14 chars tax + print(text) + if "-" in res and len(res) - num_spaces > 14: + tmp_res = res + for idx in range(len(res)): + if res[idx] == " ": + if res[idx-1] == res[idx+1]: + tmp_res = res[:idx] + res[idx+2:] + if len(re.sub('[^0-9-]', "", tmp_res)) == 14: + break + res = tmp_res + elif len(res) - num_spaces > 10: + tmp_res = res + for idx in range(len(res)): + if res[idx] == " ": + if res[idx-1] == res[idx+1]: + tmp_res = res[:idx] + res[idx+2:] + if len(re.sub('[^0-9-]', "", tmp_res)) == 10: + break + res = tmp_res + + result = re.sub(CommonPostprocessing.re_not_tax_pattern, "", res) + + print("--> ", text) + return result + + def remove_duplicate_space(text, metadata): + result = re.sub(CommonPostprocessing.re_remove_extra_space, " ", text) + return result + + +class InvoicePostprocessing: + """Function to postprocess VAT invoice + """ + @staticmethod + def process_tax_amount(text, metadata=None): + print("tax before: ", text) + text = CommonPostprocessing.remove_nan(text, metadata) + text = "0" if len(text) == 0 else text + print("tax after: ", text) + return text + + @staticmethod + def process_no_wordgroup(items, metadata=None): + if len(items) <= 1: + return items + if metadata is not None: + wg_res = metadata.get("wg_res", None) + no_key_wg = wg_res.get("no_key", None) + + if no_key_wg and len(no_key_wg) > 0: + no_key_box = no_key_wg[0].boundingbox + height_no_key = no_key_box[3] - no_key_box[1] if len(no_key_box) == 4 else 10000 + items = [no_wg for no_wg in items if y_distance(no_wg.boundingbox, no_key_box) <= 3*height_no_key] + + return items + + @staticmethod + def process_serial_wordgroup(items, metadata=None): + if len(items) <= 1: + return items + if metadata is not None: + wg_res = metadata.get("wg_res", None) + serial_key_wg = wg_res.get("serial_key", None) + + if serial_key_wg and len(serial_key_wg) > 0: + serial_key_box = serial_key_wg[0].boundingbox + + + height_serial_key = serial_key_box[3] - serial_key_box[1] if len(serial_key_box) == 4 else 10000 + items = [serial_wg for serial_wg in items if y_distance(serial_wg.boundingbox, serial_key_box) <= 2*height_serial_key] + + return items + + + @staticmethod + def process_date_wordgroup(items, metadata=None): + + def _not_too_far_from_wg(curr_wg: Word_group, next_wg: Word_group, thresh=3): + height_curr_wg = curr_wg.boundingbox[3] - curr_wg.boundingbox[1] + _distance = y_distance(curr_wg.boundingbox, next_wg.boundingbox) + return True if _distance <= height_curr_wg * thresh else False + + + + # sort by y-axis + date_wordgroups = sorted(items, key=lambda date_wg: date_wg.boundingbox[1]) + line = [date_wordgroups[0]] + for idx, wg in enumerate(date_wordgroups[1:]): + if is_wg_same_line(line[-1], wg) or _not_too_far_from_wg(curr_wg=line[-1], next_wg=wg): + line.append(wg) + + + # sort by x-axis + date_line = sorted(line, key=lambda wg: wg.boundingbox[0]) + + date_wg = merge_wordgroups(date_line) + return date_wg + + @staticmethod + def process_tax_wordgroup(items, metadata=None): + """ + params: + items: + metadata (dict): ['anchor_box'] + """ + + # case 1: multiple taxes + if metadata is not None: + field_name = metadata.get("field_name", None) + wg_res = metadata.get("wg_res", None) + + # sort by y-axis + tax_wordgroups = sorted(items, key=lambda tax_wg: tax_wg.boundingbox[1]) + if len(tax_wordgroups) > 1: + anchor = None + # get coordinate of buyer/seller name + if field_name is not None and wg_res is not None: + if field_name == "seller_tax_code_value": + name_wg_list = wg_res.get("seller_company_name_value", None) + elif field_name == "buyer_tax_code_value": + name_wg_list = wg_res.get("buyer_company_name_value", None) + if name_wg_list is not None and len(name_wg_list) > 0: + name_wg = name_wg_list[0] + anchor = name_wg.boundingbox + if anchor: + tax_wordgroups = [wg for wg in tax_wordgroups if wg.boundingbox[1] >= anchor[1]] + + line = [tax_wordgroups[0]] + for idx, wg in enumerate(tax_wordgroups[1:]): + if is_wg_same_line(line[-1], wg): + line.append(wg) + # sort by x-axis + tax_line = sorted(line, key=lambda wg: wg.boundingbox[0]) + + + tax_wg = merge_wordgroups(tax_line) + return tax_wg + + @staticmethod + def process_date(item, metadata=None): + """ + + Args: + item (str): date string + metadata (dict, optional): metadata dict. Defaults to None. + """ + item = post_processing_datetime(item) + return item + @staticmethod + def process_total_value_in_word(item, metadata=None): + re_remove_special_char_pattern = '[^aAàÀảẢãÃáÁạẠăĂằẰẳẲẵẴắẮặẶâÂầẦẩẨẫẪấẤậẬbBcCdDđĐeEèÈẻẺẽẼéÉẹẸêÊềỀểỂễỄếẾệỆfFgGhHiIìÌỉỈĩĨíÍịỊjJkKlLmMnNoOòÒỏỎõÕóÓọỌôÔồỒổỔỗỖốỐộỘơƠờỜởỞỡỠớỚợỢpPqQrRsStTuUùÙủỦũŨúÚụỤưƯừỪửỬữỮứỨựỰvVwWxXyYỳỲỷỶỹỸýÝỵỴzZ0123456789, ]' + item = re.sub(re_remove_special_char_pattern, " ", item) + item = CommonPostprocessing.remove_duplicate_space(item, metadata) + return item + + @staticmethod + def process_address(item, metadata=None): + item = CommonPostprocessing.remove_duplicate_space(item, metadata) + return item + @staticmethod + def process_company_name(item, metadata=None): + item = CommonPostprocessing.remove_duplicate_space(item, metadata) + return item + + +POSTPROCESS_FUNC = { + "invoice_postprocess": { + "no_value": { + "wordgroup": InvoicePostprocessing.process_no_wordgroup + }, + # "form_value": { + # "text": CommonPostprocessing.remove_numbers + # }, + "serial_value": { + "wordgroup": InvoicePostprocessing.process_serial_wordgroup + }, + "date_value": { + "wordgroup": InvoicePostprocessing.process_date_wordgroup, + "text": InvoicePostprocessing.process_date, + }, + "buyer_tax_code_value": { + "wordgroup": InvoicePostprocessing.process_tax_wordgroup, + "text": CommonPostprocessing.remove_not_tax + }, + "buyer_tel_value": { + "text": CommonPostprocessing.remove_not_phone + }, + "buyer_company_name_value": { + "text": InvoicePostprocessing.process_company_name + }, + "buyer_address_value": { + "text": InvoicePostprocessing.process_address + }, + + "seller_tax_code_value": { + "wordgroup": InvoicePostprocessing.process_tax_wordgroup, + "text": CommonPostprocessing.remove_not_tax + }, + "seller_tel_value": { + "text": CommonPostprocessing.remove_not_phone + }, + "seller_company_name_value": { + "text": InvoicePostprocessing.process_company_name + }, + "seller_address_value": { + "text": InvoicePostprocessing.process_address + }, + "tax_amount_value": { + "text": InvoicePostprocessing.process_tax_amount + }, + "total_value": { + "text": CommonPostprocessing.remove_nan + }, + "total_in_words_value": { + "text": InvoicePostprocessing.process_total_value_in_word + }, + + }, + "receipt_postprocess": { + } + +} \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/post_processing/invoice_post_processing.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/post_processing/invoice_post_processing.py new file mode 100755 index 0000000..4fceaa6 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/post_processing/invoice_post_processing.py @@ -0,0 +1,235 @@ +import re + +import numpy as np + +from sdsvkie.utils.post_processing import near +from sdsvkie.utils.post_processing.common_post_processing import normalize_number_wordgroup, normalize_tax_wordgroup +from sdsvkie.utils.post_processing.post_processing_datetime import post_processing_datetime +from sdsvkie.utils import merge_boxes, Word_group +from sdsvkie.utils.post_processing.receipt_post_processing import is_wg_same_line + +# def construct_word_groups_to_kie_label(list_word_groups: list): +# kie_dict = dict() +# for wg in list_word_groups: +# if wg.kie_label == "other": +# continue +# if wg.kie_label not in kie_dict: +# kie_dict[wg.kie_label] = [wg] +# else: +# kie_dict[wg.kie_label].append(wg) + +# new_dict = dict() +# for key, value in kie_dict.items(): +# if len(value) == 1: +# new_dict[key] = value +# continue + +# value.sort(key=lambda x: x.boundingbox[1]) +# new_dict[key] = value +# return new_dict + + +# def postprocess_total_value(kie_dict): +# if "total_in_words_value" not in kie_dict: +# return kie_dict + +# for k, value in kie_dict.items(): +# if k == "total_in_words_value": +# continue +# l = [] +# for v in value: +# if v.boundingbox[3] <= kie_dict["total_in_words_value"][0].boundingbox[3]: +# l.append(v) + +# if len(l) != 0: +# kie_dict[k] = l + +# return kie_dict + + +# def postprocess_tax_code_value(kie_dict): +# if "buyer_tax_code_value" in kie_dict or "seller_tax_code_value" not in kie_dict: +# return kie_dict + +# kie_dict["buyer_tax_code_value"] = [] +# for v in kie_dict["seller_tax_code_value"]: +# if "buyer_name_key" in kie_dict and ( +# v.boundingbox[3] > kie_dict["buyer_name_key"][0].boundingbox[3] +# or near(v, kie_dict["buyer_name_key"][0]) +# ): +# kie_dict["buyer_tax_code_value"].append(v) +# continue + +# if "buyer_name_value" in kie_dict and ( +# v.boundingbox[3] > kie_dict["buyer_name_value"][0].boundingbox[3] +# or near(v, kie_dict["buyer_name_value"][0]) +# ): +# kie_dict["buyer_tax_code_value"].append(v) +# continue + +# if "buyer_address_value" in kie_dict and near( +# kie_dict["buyer_address_value"][0], v +# ): +# kie_dict["buyer_tax_code_value"].append(v) +# return kie_dict + + +# def postprocess_tax_code_key(kie_dict): +# if "buyer_tax_code_key" in kie_dict or "seller_tax_code_key" not in kie_dict: +# return kie_dict +# kie_dict["buyer_tax_code_key"] = [] +# for v in kie_dict["seller_tax_code_key"]: +# if "buyer_name_key" in kie_dict and ( +# v.boundingbox[3] > kie_dict["buyer_name_key"][0].boundingbox[3] +# or near(v, kie_dict["buyer_name_key"][0]) +# ): +# kie_dict["buyer_tax_code_key"].append(v) +# continue + +# if "buyer_name_value" in kie_dict and ( +# v.boundingbox[3] > kie_dict["buyer_name_value"][0].boundingbox[3] +# or near(v, kie_dict["buyer_name_value"][0]) +# ): +# kie_dict["buyer_tax_code_key"].append(v) +# continue + +# if "buyer_address_value" in kie_dict and near( +# kie_dict["buyer_address_value"][0], v +# ): +# kie_dict["buyer_tax_code_key"].append(v) + +# return kie_dict + + +def format_output(kie_dict): + """ + { + 'field_key': { + 'value': str, + 'confidence': float, + 'box': list[int] + }, + or 'field_key': { + 'value': "", + 'confidence': None, + 'box': [] + }, + } + + Args: + kie_dict (_type_): _description_ + + Returns: + _type_: _description_ + """ + end2end_results = {} + for field_name, wg_list in kie_dict.items(): + if "key" in field_name: + continue + + if not isinstance(wg_list, list): + wg_list = [wg_list] + + if len(wg_list) == 0: + text = "" + conf = 0.0 + box = [] + else: + + text = " ".join([wg.text for wg in wg_list]) + text = text.strip() + text = text.replace("✪", " ") + conf_list = [wg.conf for wg in wg_list] + conf = sum(conf_list) / len(conf_list) + box_list = [wg.boundingbox for wg in wg_list] + box = merge_boxes(box_list) + + end2end_results[field_name] = { + "box": box, + "value": text, + "conf": conf + } + + # sort by keys + field_keys = list(end2end_results.keys()) + field_keys.sort() + end2end_results = { + field_key: end2end_results[field_key] for field_key in field_keys + } + return end2end_results + + +def postprocess_date(date_wordgroups): + date_wordgroups = sorted(date_wordgroups, key=lambda date_wg: date_wg.boundingbox[1]) + + # merge total value if have multi boxes in one line + line = [date_wordgroups[0]] + for idx, wg in enumerate(date_wordgroups[1:]): + if is_wg_same_line(line[-1], wg): + line.append(wg) + + date_line = sorted(line, key=lambda wg: wg.boundingbox[0]) # sort wg by x-axis in a line + if len(date_line) == 1: + date_wg = date_line[0] + date_wg.text = post_processing_datetime(date_wg.text) + return [date_wg] + + #text + date_text = " ".join([wg.text for wg in date_line if wg.text.strip() != ""]) + date_text = post_processing_datetime(date_text) + #box + date_box = merge_boxes([wg.boundingbox for wg in date_line]) + #label + date_label = date_line[0].kie_label + #conf + conf_list = [wg.conf for wg in date_line] + date_conf = sum(conf_list) / len(conf_list) + + # new value wg + date_wg = Word_group() + date_wg._set_values( + boundingbox=date_box, + text=date_text, + kie_label=date_label, + conf=date_conf + ) + + + return [date_wg] + +# def postprocess_total_in_words(total_words_wgs): +# total_words_wgs = [normalize_total_words(total_words_wg) for total_words_wg in total_words_wgs] +# return total_words_wgs + + + +def invoice_postprocess(kie_dict: dict): + + # date + if 'date' in kie_dict: + kie_dict['date'] = postprocess_date(kie_dict['date']) + + #### normalize number + number_fields = ['total_value', 'VAT_amount_value'] + for number_field in number_fields: + if number_field not in kie_dict: + continue + kie_dict[number_field] = [normalize_number_wordgroup(word_group) for word_group in kie_dict[number_field]] + + #tax code value + tax_code_fields = ['buyer_tax_code_value', 'seller_tax_code_value'] + for tax_code_field in tax_code_fields: + if tax_code_field in kie_dict: + + kie_dict[tax_code_field] = [normalize_tax_wordgroup(word_group, reserve_minus=True) for word_group in kie_dict[tax_code_field]] + + # mobile + if "seller_mobile_value" in kie_dict: + kie_dict['seller_mobile_value'] = [normalize_number_wordgroup(word_group, reserve_plus=True) for word_group in kie_dict['seller_mobile_value']] + + # if 'total_in_words_value' in kie_dict: + # kie_dict['total_in_words_value'] = postprocess_total_in_words(kie_dict['total_in_words_value']) + + + + return kie_dict \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/post_processing/post_processing_datetime.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/post_processing/post_processing_datetime.py new file mode 100755 index 0000000..349aa1b --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/post_processing/post_processing_datetime.py @@ -0,0 +1,87 @@ +import re +from datetime import datetime +from underthesea import word_tokenize + + +def verify_and_convert_date(date_str): + # Try to parse the date string using the datetime module + try: + date = datetime.strptime(date_str, "%d/%m/%Y") # TODO: fix this + except ValueError: + # If the date string is not in a valTid format, return False + return "" + + # If the date string is in the correct format, check if it is already in the "dd/mm/yyyy" format + if date_str[:2] == "dd" and date_str[3:5] == "mm" and date_str[6:] == "yyyy": + # If the date string is already in the correct format, return it as is + return date_str + else: + # If the date string is not in the correct format, use the strftime method to convert it + return date.strftime("%d/%m/%Y") + + +def get_date_from_date_string_by_prefix(date_string_, prefix_): + prefix = prefix_.lower() + date_string = date_string_.lower() + if prefix in date_string: + try: + if prefix == "năm": + match = re.split( + r"năm[^\d]*(\d{4}|\d{1}\s*\d{3}|\d{3}\s*\d{1}|\d{2}\s*\d{2})\s*\b", + date_string, + ) + elif prefix == "ngày": + match = re.split( + r"ngày[^\d]*(\d{2}|\d{1}\s*\d{1}|\d{1})\s*\b", date_string + ) + else: + match = re.split( + r"tháng[^\d]*(\d{2}|\d{1}\s*\d{1}|\d{1})\s*\b", date_string + ) + num = match[1] + remain_string = match[2] if prefix != "năm" else match[0] + return num, remain_string + except Exception as e: + print(e) + return "", date_string_ + else: + return "", date_string_ + + +def get_date_by_pattern(date_string): + match = re.findall(r"([^\d\s]+)?\s*(\d{1}\s*\d?\s+|\d{2}\s+|\d+\s*\b)", date_string) + if not match: + return "" + if len(match) > 3: + day = match[0][-1].replace(" ", "") + year = match[-1][-1].replace(" ", "") + # since in the VIETNAMESE DRIVER LICENSE, the tháng/month is behind the stamp and can be recognized as any thing => mistạken number may be in range (1->-3) => choose month to be -2 + month = match[-2][-1].replace(" ", "") + return "/".join([day, month, year]) + else: + return "/".join([m[-1].replace(" ", "") for m in match]) + + +def extract_date_from_string(date_string): + remain_str = date_string + ldate = [] + for d in ["năm", "ngày", "tháng"]: + date, remain_str = get_date_from_date_string_by_prefix(remain_str, d) + if not date: + return get_date_by_pattern(date_string) + ldate.append(date.strip().replace(" ", "")) + return "/".join([ldate[1], ldate[2], ldate[0]]) + + +def post_processing_datetime(date_string): + # Extract the day, month, and year from the string using regular expressions + date_string = date_string.lower().replace("✪", " ") + date_string = " ".join(word_tokenize(date_string)) + parsed_date_string_ = verify_and_convert_date( + date_string + ) # if already in datetime format + if parsed_date_string_: + return parsed_date_string_ + extracted_date = extract_date_from_string(date_string) + parsed_date_string_ = verify_and_convert_date(extracted_date) + return parsed_date_string_ if parsed_date_string_ else date_string diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/post_processing/receipt_post_processing.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/post_processing/receipt_post_processing.py new file mode 100755 index 0000000..3be02b5 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/post_processing/receipt_post_processing.py @@ -0,0 +1,355 @@ +from sdsvkie.utils.post_processing import normalize_number_wordgroup +from sdsvkie.utils import Word_group +from dateutil import parser +from rapidfuzz.distance import Levenshtein +from sdsvkie.utils.post_processing.common_post_processing import normalize_number +import re +import math +from sdsvkie.utils.word_formation import merge_boxes + +RATIO_VALID_DISTANCE = 3 +SIMILAR_SCORE_THR = 0.7 +GOJEK_KEYWORD = "gojek" + + +def cal_score_similar(str1, str2): + return Levenshtein.normalized_similarity(str1, str2) + +def is_grab_seller(seller_wordgroups, words=False, thr=0.7): + SELLER_GRAB_NAMES = [ + "justgrab", + "grabcar", + "grabcar premium", + "standard taxi" + ] + for seller_wg in seller_wordgroups: + for keyword_grab in SELLER_GRAB_NAMES: + # print(f"{seller_wg.text.lower()} - {keyword_grab} - {cal_score_similar(seller_wg.text.lower(), keyword_grab)}") + if cal_score_similar(seller_wg.text.lower().strip(), keyword_grab) > thr \ + or "grab" in seller_wg.text.lower().strip(): + return True + return False + + + +def is_wg_same_line(pre_wg, curr_wg, thresh=0.7): + def _cal_ratio(top1, bottom1, top2, bottom2): + sorted_vals = sorted([top1, bottom1, top2, bottom2]) + intersection = sorted_vals[2] - sorted_vals[1] + min_height = min(bottom1 - top1, bottom2 - top2) + if min_height == 0: + return -1 + ratio = intersection / min_height + return ratio + + def _cal_ratio_height(top1, bottom1, top2, bottom2): + + height1, height2 = top1 - bottom1, top2 - bottom2 + ratio_height = float(max(height1, height2)) / float(min(height1, height2)) + return ratio_height + # calculate iou in vertical direction + _, top1, _, bottom1 = pre_wg.boundingbox + _, top2, _, bottom2 = curr_wg.boundingbox + + ratio = _cal_ratio(top1, bottom1, top2, bottom2) + ratio_height = _cal_ratio_height(top1, bottom1, top2, bottom2) + + if ( + (top1 in range(top2, bottom2) or top2 in range(top1, bottom1)) + and ratio >= thresh + and (ratio_height < 2) + ): + return True + return False + + +def is_gojek_seller(words=None, thr=0.7): + + texts = [word.text for word in words] + texts_str = " ".join(texts) + if GOJEK_KEYWORD in texts_str: + return True + else: + return False + + +def strip_wordgroup(wg): + wg.text = wg.text.strip() + return wg + +def postprocess_seller(seller_wordgroups, words): + """Seller: maybe have multiple lines + - if two wordgroup have too far distance, get highest y-axis wordgroup + + Args: + seller_wordgroups (_type_): _description_ + """ + # if len(seller_wordgroups) == 1: + # return seller_wordgroups + + # remove seller wg that have too far distance from top seller + valid_seller_wg = [] + seller_wordgroups = sorted(seller_wordgroups, key=lambda wg: wg.boundingbox[1]) + top_seller_wg = seller_wordgroups[0] + valid_seller_wg.append(top_seller_wg) + height_top_seller_wg = abs(top_seller_wg.boundingbox[3] - top_seller_wg.boundingbox[1]) + for seller_wg in seller_wordgroups[1:]: + if y_distance(seller_wg.boundingbox, valid_seller_wg[-1].boundingbox) <= height_top_seller_wg * RATIO_VALID_DISTANCE: + valid_seller_wg.append(seller_wg) + # print(f"height_top_seller_wg: {height_top_seller_wg}, height_top_seller_wg * RATIO_VALID_DISTANCE = {height_top_seller_wg * RATIO_VALID_DISTANCE}") + + if is_grab_seller(seller_wordgroups, thr=SIMILAR_SCORE_THR): + valid_seller_wg[0].text = "Grab" + return [valid_seller_wg[0]] + elif is_gojek_seller(seller_wordgroups, words): + valid_seller_wg[0].text = "Gojek" + return [valid_seller_wg[0]] + elif len(valid_seller_wg) > 1: + + # Sort seller wordgroups + valid_seller_wg = sorted(valid_seller_wg, key=lambda wg: wg.boundingbox[1]) # sort by y-axis + wg_lines = [] + line = [valid_seller_wg[0]] + for idx, wg in enumerate(valid_seller_wg[1:]): + if is_wg_same_line(line[-1], wg): + line.append(wg) + else: + line = sorted(line, key=lambda wg: wg.boundingbox[0]) # sort wg by x-axis in a line + wg_lines.append(line) + + line = [wg] + if idx == len(valid_seller_wg[1:]) - 1: + line = sorted(line, key=lambda wg: wg.boundingbox[0]) + wg_lines.append(line) + valid_seller_wg = [wg for line in wg_lines for wg in line] + #strip text + valid_seller_wg = [strip_wordgroup(wg) for wg in valid_seller_wg] + + return valid_seller_wg + + +def normalize_id(id_text): + id_text = id_text.upper() + + split_chars = ["#:", ":"] + for split_char in split_chars: + if split_char in id_text: + id_text = id_text.split(split_char)[-1] + + keywords = ["NO.","NO:", "NO#", "BILL", "RCDT", "RCPT", "#", "."] + for keyword in keywords: + id_text = id_text.replace(keyword, "") + + id_text = re.sub(r"[^0-9A-Z-]", "", id_text) + return id_text + +def postprocess_id(id_wordgroups): + """Only one wordgroup + + Args: + id_wordgroups (list[Wordgrou[]]): list of id wordgroups + """ + id_wordgroups = id_wordgroups[:1] # only get the first id + id_wordgroups[0].text = normalize_id(id_wordgroups[0].text) + + return id_wordgroups + + +def parse_date(date_str): + # remove space + date_str = re.sub(r"/\s+", "/", date_str) + date_str = re.sub(r"-\s+", "-", date_str) + is_parser_error = False + try: + date_obj = parser.parse(date_str, fuzzy=True) + year_str = str(date_obj.year) + day_str = str(date_obj.day) + date_formated = date_obj.strftime("%d/%m/%Y") + except Exception as err: + + print(f"Error parse date: err = {err}, date = {date_str}") + # from IPython import embed; embed() + date_formated = date_str + is_parser_error = True + return date_formated, is_parser_error + + if len(normalize_number(date_str)) == 6: + year_str = year_str[-2:] + try: + year_index = date_str.index(str(year_str)) + day_index = date_str.index(str(day_str)) + if year_index > day_index: + date_obj = parser.parse(date_str, fuzzy=True, dayfirst=True) + + date_formated = date_obj.strftime("%d/%m/%Y") + except Exception as err: + print(f"Error check dayfirst: err = {err}, date = {date_str}") + + return date_formated, is_parser_error + +def postprocess_date(date_wordgroups, total_value_wordgroup=None): + """ + --> parse all date wordgroups to standard format + - 1 date -> ok + - >= 2 date + + if the same date -> get highest y-axis + + if different date: + - get highest y-axis + """ + + date_wordgroups = sorted(date_wordgroups, key=lambda wg: wg.boundingbox[1]) + date_str, status = parse_date(date_wordgroups[0].text) + date_wordgroups[0].text = date_str + return date_wordgroups[:1] + + +# total money utils +def check_same_value(total_wordgroups): + is_same = True + prev_value = total_wordgroups[0] + for total_wg in total_wordgroups[1:]: + if total_wg.text != prev_value: + is_same = False + + return is_same + + +def find_best_total_key(total_key_wordgroups): + """_summary_ + + Args: + total_key_wordgroups (_type_): _description_ + """ + if len(total_key_wordgroups) == 1: + return total_key_wordgroups[0] + else: + #priority: + ## 1. 'total' keyword in key + ## 2. 'amount paid' in key + ## 3. highest y-axis + for total_key_wg in total_key_wordgroups: + if 'sub total' in total_key_wg.text.lower(): + continue + if 'total' in total_key_wg.text.lower() and 'sub total' not in total_key_wg.text.lower(): + return total_key_wg + if 'amount paid' in total_key_wg.text.lower(): + return total_key_wg + + total_key_wordgroups = sorted(total_key_wordgroups, key=lambda wg: wg.boundingbox[1]) + best_total_key = total_key_wordgroups[0] + + return best_total_key + +def y_distance(box_1, box_2): + return abs((box_1[1] + box_1[3]) / 2 - (box_2[1] + box_2[3])/ 2) + + + + +def get_best_total_value_wordgroup(total_value_wordgroups, total_key_wg): + total_value_wordgroups = sorted(total_value_wordgroups, key=lambda total_value_wg: y_distance(total_value_wg.boundingbox, total_key_wg.boundingbox)) + + # merge total value if have multi boxes in one line + line = [total_value_wordgroups[0]] + for idx, wg in enumerate(total_value_wordgroups[1:]): + if is_wg_same_line(line[-1], wg): + line.append(wg) + + total_value_line = sorted(line, key=lambda wg: wg.boundingbox[0]) # sort wg by x-axis in a line + if len(total_value_line) == 1: + return total_value_line[0] + + #text + total_value_text = ".".join([wg.text for wg in total_value_line if wg.text.strip() != ""]) + total_value_text = total_value_text.replace("..", ".") + #box + total_value_box = merge_boxes([wg.boundingbox for wg in total_value_line]) + #label + total_value_label = total_value_line[0].kie_label + #conf + conf_list = [wg.conf for wg in total_value_line] + total_value_conf = sum(conf_list) / len(conf_list) + + # new value wg + total_value_wg = Word_group() + total_value_wg._set_values( + boundingbox=total_value_box, + text=total_value_text, + kie_label=total_value_label, + conf=total_value_conf + ) + + + return total_value_wg + + +def postprocess_total(total_key_wordgroups, total_value_wordgroups, reserve_dot=False): + """ + Case 1: 1 total value + Case 2: >1 total value + - the same value -> get highest y-axis box + - different value -> get total_key's box that have highest y-axis -> get total_value have the same line + + """ + total_value_wordgroups = [normalize_number_wordgroup(wg, reserve_dot=reserve_dot) for wg in total_value_wordgroups] + if len(total_value_wordgroups) == 1: + return total_value_wordgroups + elif len(total_value_wordgroups) > 1: + if check_same_value(total_value_wordgroups) or len(total_key_wordgroups) == 0: + total_value_wordgroups = sorted(total_value_wordgroups, key=lambda wg : wg.boundingbox[1]) + best_total_value_wordgroup = total_value_wordgroups[0] + + else: + # use total_key + total_key_wg = find_best_total_key(total_key_wordgroups) + best_total_value_wordgroup = get_best_total_value_wordgroup(total_value_wordgroups, total_key_wg) + return [best_total_value_wordgroup] + +def remove_special_token(wg): + wg.text = wg.text.replace("✪", " ") + return wg + +def process_remove_special_token(kie_dict): + new_kie_dict = {} + for field_key, list_wg in kie_dict.items(): + new_list_wg = [remove_special_token(wg) for wg in list_wg] + new_kie_dict[field_key] = new_list_wg + + return new_kie_dict + +def receipt_postprocess(kie_dict: dict, words=None, return_currency=False): + + ### Remove special token + kie_dict = process_remove_special_token(kie_dict) + + # ID + if 'no_value' in kie_dict: + kie_dict['no_value'] = postprocess_id(kie_dict['no_value']) + else: + kie_dict['no_value'] = [] + # Store name + if 'seller_company_name_value' in kie_dict: + kie_dict['seller_company_name_value'] = postprocess_seller(kie_dict['seller_company_name_value'], words) + else: + kie_dict['seller_company_name_value'] = [] + # Date + if 'date_value' in kie_dict: + kie_dict['date_value'] = postprocess_date(kie_dict['date_value']) + else: + kie_dict['date_value'] = [] + # Total + if 'total_value' in kie_dict: + + total_key_wordgroups = [] if 'total_key' not in kie_dict else kie_dict['total_key'] + kie_dict['total_value'] = postprocess_total( + total_key_wordgroups=total_key_wordgroups, + total_value_wordgroups=kie_dict['total_value'], + reserve_dot=True) + # print(kie_dict['Total_value'][0].text) + else: + kie_dict['total_value'] = [] + + # mapping + + + return kie_dict \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/results.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/results.py new file mode 100755 index 0000000..c9c1be4 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/results.py @@ -0,0 +1,9 @@ + + + +class Results: + def __ini__(self): + self.list_word_groups = None # list of wordgroups + self.word_group = None # field's wordgroup + + diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/split_data.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/split_data.py new file mode 100755 index 0000000..28d26ed --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/split_data.py @@ -0,0 +1,45 @@ +import os +import glob +import shutil +import argparse +import random +from pathlib import Path + +random.seed(1000) + +def copy_data(src_paths, tgt_dir): + for p in src_paths: + txt_path = str(Path(p).with_suffix(".txt")) + shutil.copy(txt_path, tgt_dir) + shutil.copy(p, tgt_dir) + + +if __name__ == "__main__": + parser = argparse.ArgumentParser() + parser.add_argument("--path", type=str, required=True) + parser.add_argument("--out", type=str, required=True) + parser.add_argument("--test_ratio", type=float, default=0.1) + args = parser.parse_args() + img_paths = [p for p in sorted(glob.glob(args.path + "/*")) if ".txt" not in p] + random.shuffle(img_paths) + total_imgs = len(img_paths) + num_test = int(args.test_ratio * total_imgs) + if num_test == 0: + test_paths = [] + train_paths = img_paths + else: + train_paths = img_paths[:-num_test] + test_paths = img_paths[-num_test:] + + out_dir = Path(args.out) + out_train = out_dir / 'train' + out_test = out_dir / 'test' + if not out_train.exists(): + out_train.mkdir(parents=True) + out_test.mkdir(parents=True) + + copy_data(train_paths, out_train) + copy_data(test_paths, out_test) + + + diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/transform.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/transform.py new file mode 100755 index 0000000..c83f587 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/transform.py @@ -0,0 +1,16 @@ +def unnormalize_box(bbox, width, height): + return [ + width * (bbox[0] / 1000), + height * (bbox[1] / 1000), + width * (bbox[2] / 1000), + height * (bbox[3] / 1000), + ] + + +def normalize_box(box, width, height): + return [ + int(1000 * (box[0] / width)), + int(1000 * (box[1] / height)), + int(1000 * (box[2] / width)), + int(1000 * (box[3] / height)), + ] diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/version.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/version.py new file mode 100755 index 0000000..6c4c011 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/version.py @@ -0,0 +1 @@ +__version__ = '1.0.1' \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/visualize.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/visualize.py new file mode 100755 index 0000000..e3857e0 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/visualize.py @@ -0,0 +1,108 @@ +import os +import random + +import cv2 +import numpy as np +from PIL import Image, ImageDraw, ImageFont + + +def visualize_kie( + img, + boxes, + pred_labels, + skip_classes=["other"], + image_name="out_kie.jpg", + outdir="workdirs/visualize", + colors=None, + texts=None, +): + """Visualize kie output + + Args: + image (PIL.Image): _description_ + boxes (list[xyxy]): list of xyxy boxes + kie_preds (list[str]): _description_ + skip_classes (list[str], optional): list of skip labels. Defaults to ['other']. + image_path (str, optional): _description_. Defaults to None. + outdir (_type_, optional): _description_. Defaults to None. + """ + if not os.path.exists(outdir): + os.makedirs(outdir, exist_ok=True) + + image = img.copy() + if isinstance(image, np.ndarray): + image = Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB)) + + set_labels = sorted(list(set(pred_labels))) + if colors is None: + colors = [ + ( + random.randint(0, 255), + random.randint(0, 255), + random.randint(0, 255), + ) + for _ in range(len(set_labels)) + ] + text_color = (255,0,0) + text_checkin = [0] * len(set_labels) + + + + + + draw = ImageDraw.Draw(image) + # font = ImageFont.load_default() + font = ImageFont.truetype("/usr/share/fonts/truetype/msttcorefonts/Arial.ttf", 16) + for i, pred_label in enumerate(pred_labels): + if pred_label in skip_classes: + continue + pred_label_idx = set_labels.index(pred_label) + box = boxes[i] + color = colors[pred_label_idx] if isinstance(colors, list) else colors[pred_label] + draw.rectangle(box, fill=None, outline=color) + + # skip visualize text label for other boxes + if texts is not None and text_checkin[set_labels.index(pred_label)] == 0: + draw.text( + (int(box[0]) + 10, int(box[1]) - 10), + fill=text_color if isinstance(colors, list) else colors[pred_label], + # text=str(pred_label) + " - " + str(texts[i]), + text=str(texts[i]), + font=font, + ) + text_checkin[pred_label_idx] = 1 + image.save(os.path.join(outdir, image_name)) + + +def visualize_ocr( + img, boxes, texts, image_name="out_ocr.jpg", outdir="workdirs/visualize" +): + """Visualize kie output + + Args: + image (PIL.Image): _description_ + boxes (list[xyxy]): list of xyxy boxes + kie_preds (list[str]): _description_ + skip_classes (list[str], optional): list of skip labels. Defaults to ['other']. + image_path (str, optional): _description_. Defaults to None. + outdir (_type_, optional): _description_. Defaults to None. + """ + if not os.path.exists(outdir): + os.makedirs(outdir, exist_ok=True) + + image = img.copy() + if isinstance(image, np.ndarray): + image = Image.fromarray(cv2.cvtColor(image, cv2.COLOR_BGR2RGB)) + color = ( + random.randint(0, 255), + random.randint(0, 255), + random.randint(0, 255), + ) + + draw = ImageDraw.Draw(image) + font = ImageFont.load_default() + for i, text in enumerate(texts): + box = boxes[i] + draw.rectangle(box, fill=None, outline=color) + # draw.text((int(box[0])+10, int(box[1])-10),fill=color, text=text, font = font) + image.save(os.path.join(outdir, image_name)) diff --git a/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/word_formation.py b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/word_formation.py new file mode 100755 index 0000000..b202dd0 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/sdsvkie/utils/word_formation.py @@ -0,0 +1,608 @@ +import re +from builtins import dict, type +import numpy as np +import math + +MIN_IOU_HEIGHT = 0.7 +MIN_WIDTH_LINE_RATIO = 0.05 +MIN_IOU_BETWEEN_WORD_AND_WORDGROUP = 0.7 + +class Word: + def __init__( + self, + text="", + image=None, + conf_detect=0.0, + conf_cls=0.0, + bndbox=None, + kie_label="", + ): + self.type = "word" + self.text = text + self.image = image + self.conf_detect = conf_detect + self.conf_cls = conf_cls + self.boundingbox = ( + bndbox if bndbox is not None else [-1, -1, -1, -1] + ) # [left, top,right,bot] coordinate of top-left and bottom-right point + self.word_id = 0 # id of word + self.word_group_id = 0 # id of word_group which instance belongs to + self.line_id = 0 # id of line which instance belongs to + self.paragraph_id = 0 # id of line which instance belongs to + self.kie_label = kie_label + + def invalid_size(self): + return (self.boundingbox[2] - self.boundingbox[0]) * ( + self.boundingbox[3] - self.boundingbox[1] + ) > 0 + + def is_special_word(self): + left, top, right, bottom = self.boundingbox + width, height = right - left, bottom - top + text = self.text + + if text is None: + return True + + if len(text) >= 7: + no_digits = sum(c.isdigit() for c in text) + return no_digits / len(text) >= 0.3 + + return False + + +class Word_group: + def __init__(self): + self.type = "word_group" + self.list_words = [] # dict of word instances + self.word_group_id = 0 # word group id + self.line_id = 0 # id of line which instance belongs to + self.paragraph_id = 0 # id of paragraph which instance belongs to + self.text = "" + self.boundingbox = [-1, -1, -1, -1] + self.kie_label = "" + self.conf = 0.0 + + def _set_values(self, boundingbox, text, kie_label, conf): + self.boundingbox = boundingbox + self.text = text + self.kie_label = kie_label + self.conf = conf + + def add_word(self, word: Word): # add a word instance to the word_group + if word.text != "✪": + for w in self.list_words: + if word.word_id == w.word_id: + print("Word id collision") + return False + word.word_group_id = self.word_group_id # + word.line_id = self.line_id + word.paragraph_id = self.paragraph_id + + # sort wordgroup: + if len(self.list_words) >= 1 and word.boundingbox[0] < self.list_words[-1].boundingbox[0]: + self.list_words.append(word) + self.list_words = sorted(self.list_words, key=lambda wg: wg.boundingbox[0]) + self.update_text() + else: + self.list_words.append(word) + self.text += " " + word.text + + if self.boundingbox == [-1, -1, -1, -1]: + self.boundingbox = word.boundingbox + else: + self.boundingbox = [ + min(self.boundingbox[0], word.boundingbox[0]), + min(self.boundingbox[1], word.boundingbox[1]), + max(self.boundingbox[2], word.boundingbox[2]), + max(self.boundingbox[3], word.boundingbox[3]), + ] + return True + else: + return False + + def update_word_group_id(self, new_word_group_id): + self.word_group_id = new_word_group_id + for i in range(len(self.list_words)): + self.list_words[i].word_group_id = new_word_group_id + + def update_kie_label(self): + list_kie_label = [word.kie_label for word in self.list_words] + dict_kie = dict() + for label in list_kie_label: + if label not in dict_kie: + dict_kie[label] = 1 + else: + dict_kie[label] += 1 + total = len(list(dict_kie.values())) + max_value = max(list(dict_kie.values())) + list_keys = list(dict_kie.keys()) + list_values = list(dict_kie.values()) + self.kie_label = list_keys[list_values.index(max_value)] + + def update_text(self): # update text after changing positions of words in list word + text = "" + for word in self.list_words: + text += " " + word.text + self.text = text + + def update_conf(self): + conf_list = [word.conf_cls for word in self.list_words] + conf = sum(conf_list) / len(conf_list) if len(conf_list) > 0 else 0.0 + self.conf = conf + + +class Line: + def __init__(self): + self.type = "line" + self.list_word_groups = [] # list of Word_group instances in the line + self.line_id = 0 # id of line in the paragraph + self.paragraph_id = 0 # id of paragraph which instance belongs to + self.text = "" + self.boundingbox = [-1, -1, -1, -1] + + def add_group(self, word_group: Word_group): # add a word_group instance + if word_group.list_words is not None: + for wg in self.list_word_groups: + if word_group.word_group_id == wg.word_group_id: + print("Word_group id collision") + return False + + self.list_word_groups.append(word_group) + self.text += word_group.text + word_group.paragraph_id = self.paragraph_id + word_group.line_id = self.line_id + + for i in range(len(word_group.list_words)): + word_group.list_words[ + i + ].paragraph_id = self.paragraph_id # set paragraph_id for word + word_group.list_words[i].line_id = self.line_id # set line_id for word + return True + return False + + def update_line_id(self, new_line_id): + self.line_id = new_line_id + for i in range(len(self.list_word_groups)): + self.list_word_groups[i].line_id = new_line_id + for j in range(len(self.list_word_groups[i].list_words)): + self.list_word_groups[i].list_words[j].line_id = new_line_id + + def merge_word(self, word): # word can be a Word instance or a Word_group instance + if word.text != "✪": + if self.boundingbox == [-1, -1, -1, -1]: + self.boundingbox = word.boundingbox + else: + self.boundingbox = [ + min(self.boundingbox[0], word.boundingbox[0]), + min(self.boundingbox[1], word.boundingbox[1]), + max(self.boundingbox[2], word.boundingbox[2]), + max(self.boundingbox[3], word.boundingbox[3]), + ] + self.list_word_groups.append(word) + self.text += " " + word.text + return True + return False + + def __cal_ratio(self, top1, bottom1, top2, bottom2): + sorted_vals = sorted([top1, bottom1, top2, bottom2]) + intersection = sorted_vals[2] - sorted_vals[1] + min_height = min(bottom1 - top1, bottom2 - top2) + if min_height == 0: + return -1 + ratio = intersection / min_height + return ratio + + def __cal_ratio_height(self, top1, bottom1, top2, bottom2): + + height1, height2 = top1 - bottom1, top2 - bottom2 + ratio_height = float(max(height1, height2)) / float(min(height1, height2)) + return ratio_height + + def in_same_line(self, input_line, thresh=0.7): + # calculate iou in vertical direction + _, top1, _, bottom1 = self.boundingbox + _, top2, _, bottom2 = input_line.boundingbox + + ratio = self.__cal_ratio(top1, bottom1, top2, bottom2) + ratio_height = self.__cal_ratio_height(top1, bottom1, top2, bottom2) + + if ( + (top1 in range(top2, bottom2) or top2 in range(top1, bottom1)) + and ratio >= thresh + and (ratio_height < 2) + ): + return True + return False + + +class Paragraph: + def __init__(self, id=0, lines=None): + self.list_lines = ( + lines if lines is not None else [] + ) # list of all lines in the paragraph + self.paragraph_id = id # index of paragraph in the ist of paragraph + self.text = "" + self.boundingbox = [-1, -1, -1, -1] + + def add_line(self, line: Line): # add a line instance + if line.list_word_groups is not None: + for l in self.list_lines: + if line.line_id == l.line_id: + print("Line id collision") + return False + for i in range(len(line.list_word_groups)): + line.list_word_groups[ + i + ].paragraph_id = ( + self.paragraph_id + ) # set paragraph id for every word group in line + for j in range(len(line.list_word_groups[i].list_words)): + line.list_word_groups[i].list_words[ + j + ].paragraph_id = ( + self.paragraph_id + ) # set paragraph id for every word in word groups + line.paragraph_id = self.paragraph_id # set paragraph id for line + self.list_lines.append(line) # add line to paragraph + self.text += " " + line.text + return True + else: + return False + + def update_paragraph_id( + self, new_paragraph_id + ): # update new paragraph_id for all lines, word_groups, words inside paragraph + self.paragraph_id = new_paragraph_id + for i in range(len(self.list_lines)): + self.list_lines[ + i + ].paragraph_id = new_paragraph_id # set new paragraph_id for line + for j in range(len(self.list_lines[i].list_word_groups)): + self.list_lines[i].list_word_groups[ + j + ].paragraph_id = new_paragraph_id # set new paragraph_id for word_group + for k in range(len(self.list_lines[i].list_word_groups[j].list_words)): + self.list_lines[i].list_word_groups[j].list_words[ + k + ].paragraph_id = new_paragraph_id # set new paragraph id for word + return True + + +# def resize_to_original( +# boundingbox, scale +# ): # resize coordinates to match size of original image +# left, top, right, bottom = boundingbox +# left *= scale[1] +# right *= scale[1] +# top *= scale[0] +# bottom *= scale[0] +# return [left, top, right, bottom] + + +def check_iomin(word: Word, word_group: Word_group): + min_height = min( + word.boundingbox[3] - word.boundingbox[1], + word_group.boundingbox[3] - word_group.boundingbox[1], + ) + intersect = min(word.boundingbox[3], word_group.boundingbox[3]) - max( + word.boundingbox[1], word_group.boundingbox[1] + ) + if intersect / min_height > MIN_IOU_BETWEEN_WORD_AND_WORDGROUP: + return True + return False + + +def prepare_line(words): + lines = [] + visited = [False] * len(words) + for id_word, word in enumerate(words): + if word.invalid_size() == 0: + continue + new_line = True + for i in range(len(lines)): + if ( + lines[i].in_same_line(word) and not visited[id_word] + ): # check if word is in the same line with lines[i] + lines[i].merge_word(word) + new_line = False + visited[id_word] = True + + if new_line == True: + new_line = Line() + new_line.merge_word(word) + lines.append(new_line) + + # sort line from top to bottom according top coordinate + lines.sort(key=lambda x: x.boundingbox[1]) + return lines + + +def __create_word_group(word, word_group_id): + new_word_group = Word_group() + new_word_group.word_group_id = word_group_id + new_word_group.add_word(word) + + return new_word_group + + +def __sort_line(line): + line.list_word_groups.sort( + key=lambda x: x.boundingbox[0] + ) # sort word in lines from left to right + + return line + + +def __merge_text_for_line(line): + line.text = "" + for word in line.list_word_groups: + line.text += " " + word.text + + return line + + +def __update_list_word_groups(line, word_group_id, word_id, line_width): + + old_list_word_group = line.list_word_groups + list_word_groups = [] + + inital_word_group = __create_word_group(old_list_word_group[0], word_group_id) + old_list_word_group[0].word_id = word_id + list_word_groups.append(inital_word_group) + word_group_id += 1 + word_id += 1 + + for word in old_list_word_group[1:]: + check_word_group = True + word.word_id = word_id + word_id += 1 + + if ( + (not list_word_groups[-1].text.endswith(":")) + and ( + (word.boundingbox[0] - list_word_groups[-1].boundingbox[2]) / line_width + < MIN_WIDTH_LINE_RATIO + ) + and check_iomin(word, list_word_groups[-1]) + and (len(list_word_groups[-1].list_words) > 0 and word.kie_label == list_word_groups[-1].list_words[-1].kie_label) + ): + list_word_groups[-1].add_word(word) + check_word_group = False + + if check_word_group: + new_word_group = __create_word_group(word, word_group_id) + list_word_groups.append(new_word_group) + word_group_id += 1 + line.list_word_groups = list_word_groups + return line, word_group_id, word_id + + +def construct_word_groups_in_each_line(lines): + line_id = 0 + word_group_id = 0 + word_id = 0 + for i in range(len(lines)): + if len(lines[i].list_word_groups) == 0: + continue + + # left, top ,right, bottom + line_width = lines[i].boundingbox[2] - lines[i].boundingbox[0] # right - left + + lines[i] = __sort_line(lines[i]) + + # update text for lines after sorting + lines[i] = __merge_text_for_line(lines[i]) + + lines[i], word_group_id, word_id = __update_list_word_groups( + lines[i], word_group_id, word_id, line_width + ) + lines[i].update_line_id(line_id) + line_id += 1 + return lines + + +def words_to_lines(words, check_special_lines=True): # words is list of Word instance + # sort word by top + words.sort(key=lambda x: (x.boundingbox[1], x.boundingbox[0])) + number_of_word = len(words) + # sort list words to list lines, which have not contained word_group yet + lines = prepare_line(words) + + # construct word_groups in each line + lines = construct_word_groups_in_each_line(lines) + return lines, number_of_word + + +# def sort_words(boxes, texts, det_confs=None, recog_confs=None, labels=None): +def sort_words(word_items): + """Sort words by line + + Args: + word_items (dict): format { + "boxes": list[list[int]], #xyxy format + "texts": list[str] + } + + Returns: + (dict): format: + sorted_word_items = { + 'boxes': [word.boundingbox for word in new_words], + 'texts': [word.text for word in new_words], + 'labels': [word.kie_label for word in new_words], + 'det_confs': [word.conf_detect for word in new_words], + 'recog_confs': [word.conf_cls for word in new_words], + } + """ + assert 'boxes' in word_items, "boxes key not exists in word items" + assert 'texts' in word_items, "texts key not exists in word items" + + boxes = word_items['boxes'] + texts = word_items['texts'] + + + labels = word_items.pop("labels", ["dummy_label"] * len(boxes)) + det_confs = word_items.pop("det_confs", [0.0] * len(boxes)) + recog_confs = word_items.pop("recog_confs", [0.0] * len(boxes)) + + + words = [] + for idx, (box, text) in enumerate(zip(boxes, texts)): + word = Word( + text=text, + bndbox=box, + kie_label=labels[idx], + conf_detect=det_confs[idx], + conf_cls=recog_confs[idx] + ) + words.append(word) + lines, _ = words_to_lines(words) + + new_words = [] + for line in lines: + list_word_groups = line.list_word_groups + for word_group in list_word_groups: + for word in word_group.list_words: + new_words.append(word) + + sorted_word_items = { + 'boxes': [word.boundingbox for word in new_words], + 'texts': [word.text for word in new_words], + 'labels': [word.kie_label for word in new_words], + 'det_confs': [word.conf_detect for word in new_words], + 'recog_confs': [word.conf_cls for word in new_words], + } + + return sorted_word_items + + + + +def sliding_windows(elements, window_size, slice_inverval): + element_windows = [] + + stop = False + for i in range(0, len(elements), slice_inverval): + if stop: + break + element_windows.append(elements[i : i + window_size]) + if i + window_size > len(elements): + stop = True + + return element_windows + +def merge_boxes(box_list): + boxes = np.array(box_list) + xmin = np.min(boxes[:, 0]) + ymin = np.min(boxes[:, 1]) + xmax = np.max(boxes[:, 2]) + ymax = np.max(boxes[:, 3]) + return [int(xmin), int(ymin), int(xmax), int(ymax)] + + +def merge_wordgroups(wordgroups): + if len(wordgroups) == 1: + return wordgroups[0] + wg_text = " ".join([wg.text for wg in wordgroups if wg.text.strip() != ""]) + wg_box = merge_boxes([wg.boundingbox for wg in wordgroups]) + wg_label = wordgroups[0].kie_label + wg_conf = sum([wg.conf for wg in wordgroups]) / len(wordgroups) + + # new value wg + wordgroup = Word_group() + wordgroup._set_values( + boundingbox=wg_box, + text=wg_text, + kie_label=wg_label, + conf=wg_conf + ) + return wordgroup + + +# def calculate_iou_and_near(wg1: Word_group, wg2: Word_group): +# min_height = min( +# wg1.boundingbox[3] - wg1.boundingbox[1], wg2.boundingbox[3] - wg2.boundingbox[1] +# ) +# overlap = min(wg1.boundingbox[3], wg2.boundingbox[3]) - max( +# wg1.boundingbox[1], wg2.boundingbox[1] +# ) +# iou = overlap / min_height +# distance = min( +# abs(wg1.boundingbox[0] - wg2.boundingbox[2]), +# abs(wg1.boundingbox[2] - wg2.boundingbox[0]), +# ) +# if iou > 0.7 and distance < 0.5 * (wg1.boundingboxp[2] - wg1.boundingbox[0]): +# return True +# return False + + + + + +# def throw_overlapping_words(list_words): +# new_list = [list_words[0]] +# for word in list_words: +# overlap = False +# area = (word.boundingbox[2] - word.boundingbox[0]) * ( +# word.boundingbox[3] - word.boundingbox[1] +# ) +# for word2 in new_list: +# area2 = (word2.boundingbox[2] - word2.boundingbox[0]) * ( +# word2.boundingbox[3] - word2.boundingbox[1] +# ) +# xmin_intersect = max(word.boundingbox[0], word2.boundingbox[0]) +# xmax_intersect = min(word.boundingbox[2], word2.boundingbox[2]) +# ymin_intersect = max(word.boundingbox[1], word2.boundingbox[1]) +# ymax_intersect = min(word.boundingbox[3], word2.boundingbox[3]) +# if xmax_intersect < xmin_intersect or ymax_intersect < ymin_intersect: +# continue + +# area_intersect = (xmax_intersect - xmin_intersect) * ( +# ymax_intersect - ymin_intersect +# ) +# if area_intersect / area > 0.7 or area_intersect / area2 > 0.7: +# overlap = True +# if overlap == False: +# new_list.append(word) +# return new_list + + +class Box: + def __init__(self, xmin=0, ymin=0, xmax=0, ymax=0, label="", kie_label=""): + self.xmax = xmax + self.ymax = ymax + self.xmin = xmin + self.ymin = ymin + self.label = label + self.kie_label = kie_label + + + +def check_iou(box1: Box, box2: Box, threshold=0.9): + area1 = (box1.xmax - box1.xmin) * (box1.ymax - box1.ymin) + area2 = (box2.xmax - box2.xmin) * (box2.ymax - box2.ymin) + xmin_intersect = max(box1.xmin, box2.xmin) + ymin_intersect = max(box1.ymin, box2.ymin) + xmax_intersect = min(box1.xmax, box2.xmax) + ymax_intersect = min(box1.ymax, box2.ymax) + if xmax_intersect < xmin_intersect or ymax_intersect < ymin_intersect: + area_intersect = 0 + else: + area_intersect = (xmax_intersect - xmin_intersect) * ( + ymax_intersect * ymin_intersect + ) + union = area1 + area2 - area_intersect + iou = area_intersect / area1 + if iou > threshold: + return True + return False + + +def distance_of_boxes(box1, box2): + x1, y1 = (box1[0] + box1[2]) / 2, (box1[1] + box1[3]) / 2 + x2, y2 = (box2[0] + box2[2]) / 2, (box2[1] + box2[3]) / 2 + distance = math.sqrt((x1 - x2)**2 + (y1 - y2)**2) + return distance + +def y_distance(box_1, box_2): + return abs((box_1[1] + box_1[3]) / 2 - (box_2[1] + box_2[3])/ 2) \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/setup.cfg b/cope2n-ai-fi/modules/sdsvkie/setup.cfg new file mode 100755 index 0000000..e158110 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/setup.cfg @@ -0,0 +1,43 @@ +[tool:pytest] +norecursedirs = + .git + dist + build +addopts = + --strict + --doctest-modules + --durations=0 + +[coverage:report] +exclude_lines = + pragma: no-cover + pass + +[flake8] +max-line-length = 120 +exclude = .tox,*.egg,build,temp +select = E,W,F +doctests = True +verbose = 2 +# https://pep8.readthedocs.io/en/latest/intro.html#error-codes +format = pylint +# see: https://www.flake8rules.com/ +ignore = + E731 # Do not assign a lambda expression, use a def + W504 # Line break occurred after a binary operator + F401 # Module imported but unused + F841 # Local variable name is assigned to but never used + W605 # Invalid escape sequence 'x' + +# setup.cfg or tox.ini +[check-manifest] +ignore = + *.yml + .github + .github/* + +[metadata] +license_file = LICENSE +description-file = README.md +# long_description = file:README.md +# long_description_content_type = text/markdown \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvkie/setup.py b/cope2n-ai-fi/modules/sdsvkie/setup.py new file mode 100755 index 0000000..d2f803e --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvkie/setup.py @@ -0,0 +1,187 @@ +import os +import os.path as osp +import shutil +import sys +import warnings +from setuptools import find_packages, setup + + +def readme(): + with open('README.md', encoding='utf-8') as f: + content = f.read() + return content + + +version_file = 'sdsvkie/utils/version.py' +is_windows = sys.platform == 'win32' + + +def add_mim_extention(): + """Add extra files that are required to support MIM into the package. + + These files will be added by creating a symlink to the originals if the + package is installed in `editable` mode (e.g. pip install -e .), or by + copying from the originals otherwise. + """ + + # parse installment mode + if 'develop' in sys.argv: + # installed by `pip install -e .` + mode = 'symlink' + elif 'sdist' in sys.argv or 'bdist_wheel' in sys.argv: + # installed by `pip install .` + # or create source distribution by `python setup.py sdist` + mode = 'copy' + else: + return + + filenames = ['tools', 'configs', 'model-index.yml'] + repo_path = osp.dirname(__file__) + mim_path = osp.join(repo_path, 'mmocr', '.mim') + os.makedirs(mim_path, exist_ok=True) + + for filename in filenames: + if osp.exists(filename): + src_path = osp.join(repo_path, filename) + tar_path = osp.join(mim_path, filename) + + if osp.isfile(tar_path) or osp.islink(tar_path): + os.remove(tar_path) + elif osp.isdir(tar_path): + shutil.rmtree(tar_path) + + if mode == 'symlink': + src_relpath = osp.relpath(src_path, osp.dirname(tar_path)) + try: + os.symlink(src_relpath, tar_path) + except OSError: + # Creating a symbolic link on windows may raise an + # `OSError: [WinError 1314]` due to privilege. If + # the error happens, the src file will be copied + mode = 'copy' + warnings.warn( + f'Failed to create a symbolic link for {src_relpath}, ' + f'and it will be copied to {tar_path}') + else: + continue + + if mode == 'copy': + if osp.isfile(src_path): + shutil.copyfile(src_path, tar_path) + elif osp.isdir(src_path): + shutil.copytree(src_path, tar_path) + else: + warnings.warn(f'Cannot copy file {src_path}.') + else: + raise ValueError(f'Invalid mode {mode}') + + +def get_version(): + with open(version_file, 'r') as f: + exec(compile(f.read(), version_file, 'exec')) + import sys + + # return short version for sdist + if 'sdist' in sys.argv or 'bdist_wheel' in sys.argv: + return locals()['short_version'] + else: + return locals()['__version__'] + + +def parse_requirements(fname='requirements.txt', with_version=True): + """Parse the package dependencies listed in a requirements file but strip + specific version information. + + Args: + fname (str): Path to requirements file. + with_version (bool, default=False): If True, include version specs. + Returns: + info (list[str]): List of requirements items. + CommandLine: + python -c "import setup; print(setup.parse_requirements())" + """ + import re + import sys + from os.path import exists + require_fpath = fname + + def parse_line(line): + """Parse information from a line in a requirements text file.""" + if line.startswith('-r '): + # Allow specifying requirements in other files + target = line.split(' ')[1] + for info in parse_require_file(target): + yield info + else: + info = {'line': line} + if line.startswith('-e '): + info['package'] = line.split('#egg=')[1] + else: + # Remove versioning from the package + pat = '(' + '|'.join(['>=', '==', '>']) + ')' + parts = re.split(pat, line, maxsplit=1) + parts = [p.strip() for p in parts] + + info['package'] = parts[0] + if len(parts) > 1: + op, rest = parts[1:] + if ';' in rest: + # Handle platform specific dependencies + # http://setuptools.readthedocs.io/en/latest/setuptools.html#declaring-platform-specific-dependencies + version, platform_deps = map(str.strip, + rest.split(';')) + info['platform_deps'] = platform_deps + else: + version = rest # NOQA + info['version'] = (op, version) + yield info + + def parse_require_file(fpath): + with open(fpath, 'r') as f: + for line in f.readlines(): + line = line.strip() + if line and not line.startswith('#'): + for info in parse_line(line): + yield info + + def gen_packages_items(): + if exists(require_fpath): + for info in parse_require_file(require_fpath): + parts = [info['package']] + if with_version and 'version' in info: + parts.extend(info['version']) + if not sys.version.startswith('3.4'): + # apparently package_deps are broken in 3.4 + platform_deps = info.get('platform_deps') + if platform_deps is not None: + parts.append(';' + platform_deps) + item = ''.join(parts) + yield item + + packages = list(gen_packages_items()) + return packages + + +if __name__ == '__main__': + setup( + name='sdsvkie', + version=get_version(), + description='SDSV OCR Team: KIE Invoice', + long_description=readme(), + long_description_content_type='text/markdown', + packages=find_packages(exclude=('configs', 'tools', 'demo')), + include_package_data=True, + url='https://github.com/open-mmlab/mmocr', + classifiers=[ + 'Development Status :: 4 - Beta', + 'License :: OSI Approved :: Apache Software License', + 'Operating System :: OS Independent', + 'Programming Language :: Python :: 3', + 'Programming Language :: Python :: 3.6', + 'Programming Language :: Python :: 3.7', + 'Programming Language :: Python :: 3.8', + 'Programming Language :: Python :: 3.9', + ], + license='Apache License 2.0', + install_requires=parse_requirements('requirements.txt'), + zip_safe=False) diff --git a/cope2n-ai-fi/modules/sdsvtd b/cope2n-ai-fi/modules/sdsvtd new file mode 160000 index 0000000..a9a796f --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtd @@ -0,0 +1 @@ +Subproject commit a9a796f843f6ad99977a8dcba02d65fe75225574 diff --git a/cope2n-ai-fi/modules/sdsvtr/._bit/FETCH_HEAD b/cope2n-ai-fi/modules/sdsvtr/._bit/FETCH_HEAD new file mode 100755 index 0000000..e69de29 diff --git a/cope2n-ai-fi/modules/sdsvtr/._bit/HEAD b/cope2n-ai-fi/modules/sdsvtr/._bit/HEAD new file mode 100755 index 0000000..b870d82 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/._bit/HEAD @@ -0,0 +1 @@ +ref: refs/heads/main diff --git a/cope2n-ai-fi/modules/sdsvtr/._bit/config b/cope2n-ai-fi/modules/sdsvtr/._bit/config new file mode 100755 index 0000000..0e9786a --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/._bit/config @@ -0,0 +1,11 @@ +[core] + repositoryformatversion = 0 + filemode = true + bare = false + logallrefupdates = true +[remote "origin"] + url = https://github.com/thuc248997/sdsvtr.git + fetch = +refs/heads/*:refs/remotes/origin/* +[branch "main"] + remote = origin + merge = refs/heads/main diff --git a/cope2n-ai-fi/modules/sdsvtr/._bit/description b/cope2n-ai-fi/modules/sdsvtr/._bit/description new file mode 100755 index 0000000..498b267 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/._bit/description @@ -0,0 +1 @@ +Unnamed repository; edit this file 'description' to name the repository. diff --git a/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/applypatch-msg.sample b/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/applypatch-msg.sample new file mode 100755 index 0000000..a5d7b84 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/applypatch-msg.sample @@ -0,0 +1,15 @@ +#!/bin/sh +# +# An example hook script to check the commit log message taken by +# applypatch from an e-mail message. +# +# The hook should exit with non-zero status after issuing an +# appropriate message if it wants to stop the commit. The hook is +# allowed to edit the commit message file. +# +# To enable this hook, rename this file to "applypatch-msg". + +. git-sh-setup +commitmsg="$(git rev-parse --git-path hooks/commit-msg)" +test -x "$commitmsg" && exec "$commitmsg" ${1+"$@"} +: diff --git a/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/commit-msg.sample b/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/commit-msg.sample new file mode 100755 index 0000000..b58d118 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/commit-msg.sample @@ -0,0 +1,24 @@ +#!/bin/sh +# +# An example hook script to check the commit log message. +# Called by "git commit" with one argument, the name of the file +# that has the commit message. The hook should exit with non-zero +# status after issuing an appropriate message if it wants to stop the +# commit. The hook is allowed to edit the commit message file. +# +# To enable this hook, rename this file to "commit-msg". + +# Uncomment the below to add a Signed-off-by line to the message. +# Doing this in a hook is a bad idea in general, but the prepare-commit-msg +# hook is more suited to it. +# +# SOB=$(git var GIT_AUTHOR_IDENT | sed -n 's/^\(.*>\).*$/Signed-off-by: \1/p') +# grep -qs "^$SOB" "$1" || echo "$SOB" >> "$1" + +# This example catches duplicate Signed-off-by lines. + +test "" = "$(grep '^Signed-off-by: ' "$1" | + sort | uniq -c | sed -e '/^[ ]*1[ ]/d')" || { + echo >&2 Duplicate Signed-off-by lines. + exit 1 +} diff --git a/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/fsmonitor-watchman.sample b/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/fsmonitor-watchman.sample new file mode 100755 index 0000000..ef94fa2 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/fsmonitor-watchman.sample @@ -0,0 +1,109 @@ +#!/usr/bin/perl + +use strict; +use warnings; +use IPC::Open2; + +# An example hook script to integrate Watchman +# (https://facebook.github.io/watchman/) with git to speed up detecting +# new and modified files. +# +# The hook is passed a version (currently 1) and a time in nanoseconds +# formatted as a string and outputs to stdout all files that have been +# modified since the given time. Paths must be relative to the root of +# the working tree and separated by a single NUL. +# +# To enable this hook, rename this file to "query-watchman" and set +# 'git config core.fsmonitor .git/hooks/query-watchman' +# +my ($version, $time) = @ARGV; + +# Check the hook interface version + +if ($version == 1) { + # convert nanoseconds to seconds + # subtract one second to make sure watchman will return all changes + $time = int ($time / 1000000000) - 1; +} else { + die "Unsupported query-fsmonitor hook version '$version'.\n" . + "Falling back to scanning...\n"; +} + +my $git_work_tree; +if ($^O =~ 'msys' || $^O =~ 'cygwin') { + $git_work_tree = Win32::GetCwd(); + $git_work_tree =~ tr/\\/\//; +} else { + require Cwd; + $git_work_tree = Cwd::cwd(); +} + +my $retry = 1; + +launch_watchman(); + +sub launch_watchman { + + my $pid = open2(\*CHLD_OUT, \*CHLD_IN, 'watchman -j --no-pretty') + or die "open2() failed: $!\n" . + "Falling back to scanning...\n"; + + # In the query expression below we're asking for names of files that + # changed since $time but were not transient (ie created after + # $time but no longer exist). + # + # To accomplish this, we're using the "since" generator to use the + # recency index to select candidate nodes and "fields" to limit the + # output to file names only. + + my $query = <<" END"; + ["query", "$git_work_tree", { + "since": $time, + "fields": ["name"] + }] + END + + print CHLD_IN $query; + close CHLD_IN; + my $response = do {local $/; }; + + die "Watchman: command returned no output.\n" . + "Falling back to scanning...\n" if $response eq ""; + die "Watchman: command returned invalid output: $response\n" . + "Falling back to scanning...\n" unless $response =~ /^\{/; + + my $json_pkg; + eval { + require JSON::XS; + $json_pkg = "JSON::XS"; + 1; + } or do { + require JSON::PP; + $json_pkg = "JSON::PP"; + }; + + my $o = $json_pkg->new->utf8->decode($response); + + if ($retry > 0 and $o->{error} and $o->{error} =~ m/unable to resolve root .* directory (.*) is not watched/) { + print STDERR "Adding '$git_work_tree' to watchman's watch list.\n"; + $retry--; + qx/watchman watch "$git_work_tree"/; + die "Failed to make watchman watch '$git_work_tree'.\n" . + "Falling back to scanning...\n" if $? != 0; + + # Watchman will always return all files on the first query so + # return the fast "everything is dirty" flag to git and do the + # Watchman query just to get it over with now so we won't pay + # the cost in git to look up each individual file. + print "/\0"; + eval { launch_watchman() }; + exit 0; + } + + die "Watchman: $o->{error}.\n" . + "Falling back to scanning...\n" if $o->{error}; + + binmode STDOUT, ":utf8"; + local $, = "\0"; + print @{$o->{files}}; +} diff --git a/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/post-update.sample b/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/post-update.sample new file mode 100755 index 0000000..ec17ec1 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/post-update.sample @@ -0,0 +1,8 @@ +#!/bin/sh +# +# An example hook script to prepare a packed repository for use over +# dumb transports. +# +# To enable this hook, rename this file to "post-update". + +exec git update-server-info diff --git a/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/pre-applypatch.sample b/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/pre-applypatch.sample new file mode 100755 index 0000000..4142082 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/pre-applypatch.sample @@ -0,0 +1,14 @@ +#!/bin/sh +# +# An example hook script to verify what is about to be committed +# by applypatch from an e-mail message. +# +# The hook should exit with non-zero status after issuing an +# appropriate message if it wants to stop the commit. +# +# To enable this hook, rename this file to "pre-applypatch". + +. git-sh-setup +precommit="$(git rev-parse --git-path hooks/pre-commit)" +test -x "$precommit" && exec "$precommit" ${1+"$@"} +: diff --git a/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/pre-commit.sample b/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/pre-commit.sample new file mode 100755 index 0000000..6a75641 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/pre-commit.sample @@ -0,0 +1,49 @@ +#!/bin/sh +# +# An example hook script to verify what is about to be committed. +# Called by "git commit" with no arguments. The hook should +# exit with non-zero status after issuing an appropriate message if +# it wants to stop the commit. +# +# To enable this hook, rename this file to "pre-commit". + +if git rev-parse --verify HEAD >/dev/null 2>&1 +then + against=HEAD +else + # Initial commit: diff against an empty tree object + against=$(git hash-object -t tree /dev/null) +fi + +# If you want to allow non-ASCII filenames set this variable to true. +allownonascii=$(git config --bool hooks.allownonascii) + +# Redirect output to stderr. +exec 1>&2 + +# Cross platform projects tend to avoid non-ASCII filenames; prevent +# them from being added to the repository. We exploit the fact that the +# printable range starts at the space character and ends with tilde. +if [ "$allownonascii" != "true" ] && + # Note that the use of brackets around a tr range is ok here, (it's + # even required, for portability to Solaris 10's /usr/bin/tr), since + # the square bracket bytes happen to fall in the designated range. + test $(git diff --cached --name-only --diff-filter=A -z $against | + LC_ALL=C tr -d '[ -~]\0' | wc -c) != 0 +then + cat <<\EOF +Error: Attempt to add a non-ASCII file name. + +This can cause problems if you want to work with people on other platforms. + +To be portable it is advisable to rename the file. + +If you know what you are doing you can disable this check using: + + git config hooks.allownonascii true +EOF + exit 1 +fi + +# If there are whitespace errors, print the offending file names and fail. +exec git diff-index --check --cached $against -- diff --git a/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/pre-merge-commit.sample b/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/pre-merge-commit.sample new file mode 100755 index 0000000..399eab1 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/pre-merge-commit.sample @@ -0,0 +1,13 @@ +#!/bin/sh +# +# An example hook script to verify what is about to be committed. +# Called by "git merge" with no arguments. The hook should +# exit with non-zero status after issuing an appropriate message to +# stderr if it wants to stop the merge commit. +# +# To enable this hook, rename this file to "pre-merge-commit". + +. git-sh-setup +test -x "$GIT_DIR/hooks/pre-commit" && + exec "$GIT_DIR/hooks/pre-commit" +: diff --git a/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/pre-push.sample b/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/pre-push.sample new file mode 100755 index 0000000..6187dbf --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/pre-push.sample @@ -0,0 +1,53 @@ +#!/bin/sh + +# An example hook script to verify what is about to be pushed. Called by "git +# push" after it has checked the remote status, but before anything has been +# pushed. If this script exits with a non-zero status nothing will be pushed. +# +# This hook is called with the following parameters: +# +# $1 -- Name of the remote to which the push is being done +# $2 -- URL to which the push is being done +# +# If pushing without using a named remote those arguments will be equal. +# +# Information about the commits which are being pushed is supplied as lines to +# the standard input in the form: +# +# +# +# This sample shows how to prevent push of commits where the log message starts +# with "WIP" (work in progress). + +remote="$1" +url="$2" + +z40=0000000000000000000000000000000000000000 + +while read local_ref local_sha remote_ref remote_sha +do + if [ "$local_sha" = $z40 ] + then + # Handle delete + : + else + if [ "$remote_sha" = $z40 ] + then + # New branch, examine all commits + range="$local_sha" + else + # Update to existing branch, examine new commits + range="$remote_sha..$local_sha" + fi + + # Check for WIP commit + commit=`git rev-list -n 1 --grep '^WIP' "$range"` + if [ -n "$commit" ] + then + echo >&2 "Found WIP commit in $local_ref, not pushing" + exit 1 + fi + fi +done + +exit 0 diff --git a/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/pre-rebase.sample b/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/pre-rebase.sample new file mode 100755 index 0000000..6cbef5c --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/pre-rebase.sample @@ -0,0 +1,169 @@ +#!/bin/sh +# +# Copyright (c) 2006, 2008 Junio C Hamano +# +# The "pre-rebase" hook is run just before "git rebase" starts doing +# its job, and can prevent the command from running by exiting with +# non-zero status. +# +# The hook is called with the following parameters: +# +# $1 -- the upstream the series was forked from. +# $2 -- the branch being rebased (or empty when rebasing the current branch). +# +# This sample shows how to prevent topic branches that are already +# merged to 'next' branch from getting rebased, because allowing it +# would result in rebasing already published history. + +publish=next +basebranch="$1" +if test "$#" = 2 +then + topic="refs/heads/$2" +else + topic=`git symbolic-ref HEAD` || + exit 0 ;# we do not interrupt rebasing detached HEAD +fi + +case "$topic" in +refs/heads/??/*) + ;; +*) + exit 0 ;# we do not interrupt others. + ;; +esac + +# Now we are dealing with a topic branch being rebased +# on top of master. Is it OK to rebase it? + +# Does the topic really exist? +git show-ref -q "$topic" || { + echo >&2 "No such branch $topic" + exit 1 +} + +# Is topic fully merged to master? +not_in_master=`git rev-list --pretty=oneline ^master "$topic"` +if test -z "$not_in_master" +then + echo >&2 "$topic is fully merged to master; better remove it." + exit 1 ;# we could allow it, but there is no point. +fi + +# Is topic ever merged to next? If so you should not be rebasing it. +only_next_1=`git rev-list ^master "^$topic" ${publish} | sort` +only_next_2=`git rev-list ^master ${publish} | sort` +if test "$only_next_1" = "$only_next_2" +then + not_in_topic=`git rev-list "^$topic" master` + if test -z "$not_in_topic" + then + echo >&2 "$topic is already up to date with master" + exit 1 ;# we could allow it, but there is no point. + else + exit 0 + fi +else + not_in_next=`git rev-list --pretty=oneline ^${publish} "$topic"` + /usr/bin/perl -e ' + my $topic = $ARGV[0]; + my $msg = "* $topic has commits already merged to public branch:\n"; + my (%not_in_next) = map { + /^([0-9a-f]+) /; + ($1 => 1); + } split(/\n/, $ARGV[1]); + for my $elem (map { + /^([0-9a-f]+) (.*)$/; + [$1 => $2]; + } split(/\n/, $ARGV[2])) { + if (!exists $not_in_next{$elem->[0]}) { + if ($msg) { + print STDERR $msg; + undef $msg; + } + print STDERR " $elem->[1]\n"; + } + } + ' "$topic" "$not_in_next" "$not_in_master" + exit 1 +fi + +<<\DOC_END + +This sample hook safeguards topic branches that have been +published from being rewound. + +The workflow assumed here is: + + * Once a topic branch forks from "master", "master" is never + merged into it again (either directly or indirectly). + + * Once a topic branch is fully cooked and merged into "master", + it is deleted. If you need to build on top of it to correct + earlier mistakes, a new topic branch is created by forking at + the tip of the "master". This is not strictly necessary, but + it makes it easier to keep your history simple. + + * Whenever you need to test or publish your changes to topic + branches, merge them into "next" branch. + +The script, being an example, hardcodes the publish branch name +to be "next", but it is trivial to make it configurable via +$GIT_DIR/config mechanism. + +With this workflow, you would want to know: + +(1) ... if a topic branch has ever been merged to "next". Young + topic branches can have stupid mistakes you would rather + clean up before publishing, and things that have not been + merged into other branches can be easily rebased without + affecting other people. But once it is published, you would + not want to rewind it. + +(2) ... if a topic branch has been fully merged to "master". + Then you can delete it. More importantly, you should not + build on top of it -- other people may already want to + change things related to the topic as patches against your + "master", so if you need further changes, it is better to + fork the topic (perhaps with the same name) afresh from the + tip of "master". + +Let's look at this example: + + o---o---o---o---o---o---o---o---o---o "next" + / / / / + / a---a---b A / / + / / / / + / / c---c---c---c B / + / / / \ / + / / / b---b C \ / + / / / / \ / + ---o---o---o---o---o---o---o---o---o---o---o "master" + + +A, B and C are topic branches. + + * A has one fix since it was merged up to "next". + + * B has finished. It has been fully merged up to "master" and "next", + and is ready to be deleted. + + * C has not merged to "next" at all. + +We would want to allow C to be rebased, refuse A, and encourage +B to be deleted. + +To compute (1): + + git rev-list ^master ^topic next + git rev-list ^master next + + if these match, topic has not merged in next at all. + +To compute (2): + + git rev-list master..topic + + if this is empty, it is fully merged to "master". + +DOC_END diff --git a/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/pre-receive.sample b/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/pre-receive.sample new file mode 100755 index 0000000..a1fd29e --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/pre-receive.sample @@ -0,0 +1,24 @@ +#!/bin/sh +# +# An example hook script to make use of push options. +# The example simply echoes all push options that start with 'echoback=' +# and rejects all pushes when the "reject" push option is used. +# +# To enable this hook, rename this file to "pre-receive". + +if test -n "$GIT_PUSH_OPTION_COUNT" +then + i=0 + while test "$i" -lt "$GIT_PUSH_OPTION_COUNT" + do + eval "value=\$GIT_PUSH_OPTION_$i" + case "$value" in + echoback=*) + echo "echo from the pre-receive-hook: ${value#*=}" >&2 + ;; + reject) + exit 1 + esac + i=$((i + 1)) + done +fi diff --git a/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/prepare-commit-msg.sample b/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/prepare-commit-msg.sample new file mode 100755 index 0000000..10fa14c --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/prepare-commit-msg.sample @@ -0,0 +1,42 @@ +#!/bin/sh +# +# An example hook script to prepare the commit log message. +# Called by "git commit" with the name of the file that has the +# commit message, followed by the description of the commit +# message's source. The hook's purpose is to edit the commit +# message file. If the hook fails with a non-zero status, +# the commit is aborted. +# +# To enable this hook, rename this file to "prepare-commit-msg". + +# This hook includes three examples. The first one removes the +# "# Please enter the commit message..." help message. +# +# The second includes the output of "git diff --name-status -r" +# into the message, just before the "git status" output. It is +# commented because it doesn't cope with --amend or with squashed +# commits. +# +# The third example adds a Signed-off-by line to the message, that can +# still be edited. This is rarely a good idea. + +COMMIT_MSG_FILE=$1 +COMMIT_SOURCE=$2 +SHA1=$3 + +/usr/bin/perl -i.bak -ne 'print unless(m/^. Please enter the commit message/..m/^#$/)' "$COMMIT_MSG_FILE" + +# case "$COMMIT_SOURCE,$SHA1" in +# ,|template,) +# /usr/bin/perl -i.bak -pe ' +# print "\n" . `git diff --cached --name-status -r` +# if /^#/ && $first++ == 0' "$COMMIT_MSG_FILE" ;; +# *) ;; +# esac + +# SOB=$(git var GIT_COMMITTER_IDENT | sed -n 's/^\(.*>\).*$/Signed-off-by: \1/p') +# git interpret-trailers --in-place --trailer "$SOB" "$COMMIT_MSG_FILE" +# if test -z "$COMMIT_SOURCE" +# then +# /usr/bin/perl -i.bak -pe 'print "\n" if !$first_line++' "$COMMIT_MSG_FILE" +# fi diff --git a/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/update.sample b/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/update.sample new file mode 100755 index 0000000..80ba941 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/._bit/hooks/update.sample @@ -0,0 +1,128 @@ +#!/bin/sh +# +# An example hook script to block unannotated tags from entering. +# Called by "git receive-pack" with arguments: refname sha1-old sha1-new +# +# To enable this hook, rename this file to "update". +# +# Config +# ------ +# hooks.allowunannotated +# This boolean sets whether unannotated tags will be allowed into the +# repository. By default they won't be. +# hooks.allowdeletetag +# This boolean sets whether deleting tags will be allowed in the +# repository. By default they won't be. +# hooks.allowmodifytag +# This boolean sets whether a tag may be modified after creation. By default +# it won't be. +# hooks.allowdeletebranch +# This boolean sets whether deleting branches will be allowed in the +# repository. By default they won't be. +# hooks.denycreatebranch +# This boolean sets whether remotely creating branches will be denied +# in the repository. By default this is allowed. +# + +# --- Command line +refname="$1" +oldrev="$2" +newrev="$3" + +# --- Safety check +if [ -z "$GIT_DIR" ]; then + echo "Don't run this script from the command line." >&2 + echo " (if you want, you could supply GIT_DIR then run" >&2 + echo " $0 )" >&2 + exit 1 +fi + +if [ -z "$refname" -o -z "$oldrev" -o -z "$newrev" ]; then + echo "usage: $0 " >&2 + exit 1 +fi + +# --- Config +allowunannotated=$(git config --bool hooks.allowunannotated) +allowdeletebranch=$(git config --bool hooks.allowdeletebranch) +denycreatebranch=$(git config --bool hooks.denycreatebranch) +allowdeletetag=$(git config --bool hooks.allowdeletetag) +allowmodifytag=$(git config --bool hooks.allowmodifytag) + +# check for no description +projectdesc=$(sed -e '1q' "$GIT_DIR/description") +case "$projectdesc" in +"Unnamed repository"* | "") + echo "*** Project description file hasn't been set" >&2 + exit 1 + ;; +esac + +# --- Check types +# if $newrev is 0000...0000, it's a commit to delete a ref. +zero="0000000000000000000000000000000000000000" +if [ "$newrev" = "$zero" ]; then + newrev_type=delete +else + newrev_type=$(git cat-file -t $newrev) +fi + +case "$refname","$newrev_type" in + refs/tags/*,commit) + # un-annotated tag + short_refname=${refname##refs/tags/} + if [ "$allowunannotated" != "true" ]; then + echo "*** The un-annotated tag, $short_refname, is not allowed in this repository" >&2 + echo "*** Use 'git tag [ -a | -s ]' for tags you want to propagate." >&2 + exit 1 + fi + ;; + refs/tags/*,delete) + # delete tag + if [ "$allowdeletetag" != "true" ]; then + echo "*** Deleting a tag is not allowed in this repository" >&2 + exit 1 + fi + ;; + refs/tags/*,tag) + # annotated tag + if [ "$allowmodifytag" != "true" ] && git rev-parse $refname > /dev/null 2>&1 + then + echo "*** Tag '$refname' already exists." >&2 + echo "*** Modifying a tag is not allowed in this repository." >&2 + exit 1 + fi + ;; + refs/heads/*,commit) + # branch + if [ "$oldrev" = "$zero" -a "$denycreatebranch" = "true" ]; then + echo "*** Creating a branch is not allowed in this repository" >&2 + exit 1 + fi + ;; + refs/heads/*,delete) + # delete branch + if [ "$allowdeletebranch" != "true" ]; then + echo "*** Deleting a branch is not allowed in this repository" >&2 + exit 1 + fi + ;; + refs/remotes/*,commit) + # tracking branch + ;; + refs/remotes/*,delete) + # delete tracking branch + if [ "$allowdeletebranch" != "true" ]; then + echo "*** Deleting a tracking branch is not allowed in this repository" >&2 + exit 1 + fi + ;; + *) + # Anything else (is there anything else?) + echo "*** Update hook: unknown type of update to ref $refname of type $newrev_type" >&2 + exit 1 + ;; +esac + +# --- Finished +exit 0 diff --git a/cope2n-ai-fi/modules/sdsvtr/._bit/index b/cope2n-ai-fi/modules/sdsvtr/._bit/index new file mode 100755 index 0000000..f0233a0 Binary files /dev/null and b/cope2n-ai-fi/modules/sdsvtr/._bit/index differ diff --git a/cope2n-ai-fi/modules/sdsvtr/._bit/info/exclude b/cope2n-ai-fi/modules/sdsvtr/._bit/info/exclude new file mode 100755 index 0000000..a5196d1 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/._bit/info/exclude @@ -0,0 +1,6 @@ +# git ls-files --others --exclude-from=.git/info/exclude +# Lines that start with '#' are comments. +# For a project mostly in C, the following would be a good set of +# exclude patterns (uncomment them if you want to use them): +# *.[oa] +# *~ diff --git a/cope2n-ai-fi/modules/sdsvtr/._bit/logs/HEAD b/cope2n-ai-fi/modules/sdsvtr/._bit/logs/HEAD new file mode 100755 index 0000000..47aa1dd --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/._bit/logs/HEAD @@ -0,0 +1 @@ +0000000000000000000000000000000000000000 2c788e9e2d7fe369869d474fbb22426a4ca84590 Your Name 1675423869 +0700 clone: from https://github.com/thuc248997/sdsvtr.git diff --git a/cope2n-ai-fi/modules/sdsvtr/._bit/logs/refs/heads/main b/cope2n-ai-fi/modules/sdsvtr/._bit/logs/refs/heads/main new file mode 100755 index 0000000..47aa1dd --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/._bit/logs/refs/heads/main @@ -0,0 +1 @@ +0000000000000000000000000000000000000000 2c788e9e2d7fe369869d474fbb22426a4ca84590 Your Name 1675423869 +0700 clone: from https://github.com/thuc248997/sdsvtr.git diff --git a/cope2n-ai-fi/modules/sdsvtr/._bit/logs/refs/remotes/origin/HEAD b/cope2n-ai-fi/modules/sdsvtr/._bit/logs/refs/remotes/origin/HEAD new file mode 100755 index 0000000..47aa1dd --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/._bit/logs/refs/remotes/origin/HEAD @@ -0,0 +1 @@ +0000000000000000000000000000000000000000 2c788e9e2d7fe369869d474fbb22426a4ca84590 Your Name 1675423869 +0700 clone: from https://github.com/thuc248997/sdsvtr.git diff --git a/cope2n-ai-fi/modules/sdsvtr/._bit/objects/0d/8bca4703a228b184ac2924faeb0175809df7d4 b/cope2n-ai-fi/modules/sdsvtr/._bit/objects/0d/8bca4703a228b184ac2924faeb0175809df7d4 new file mode 100755 index 0000000..82dc358 Binary files /dev/null and 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changing it is not allowed. + + Preamble + + The GNU General Public License is a free, copyleft license for +software and other kinds of works. + + The licenses for most software and other practical works are designed +to take away your freedom to share and change the works. By contrast, +the GNU General Public License is intended to guarantee your freedom to +share and change all versions of a program--to make sure it remains free +software for all its users. We, the Free Software Foundation, use the +GNU General Public License for most of our software; it applies also to +any other work released this way by its authors. You can apply it to +your programs, too. + + When we speak of free software, we are referring to freedom, not +price. Our General Public Licenses are designed to make sure that you +have the freedom to distribute copies of free software (and charge for +them if you wish), that you receive source code or can get it if you +want it, that you can change the software or use pieces of it in new +free programs, and that you know you can do these things. + + To protect your rights, we need to prevent others from denying you +these rights or asking you to surrender the rights. Therefore, you have +certain responsibilities if you distribute copies of the software, or if +you modify it: responsibilities to respect the freedom of others. + + For example, if you distribute copies of such a program, whether +gratis or for a fee, you must pass on to the recipients the same +freedoms that you received. You must make sure that they, too, receive +or can get the source code. And you must show them these terms so they +know their rights. + + Developers that use the GNU GPL protect your rights with two steps: +(1) assert copyright on the software, and (2) offer you this License +giving you legal permission to copy, distribute and/or modify it. + + For the developers' and authors' protection, the GPL clearly explains +that there is no warranty for this free software. For both users' and +authors' sake, the GPL requires that modified versions be marked as +changed, so that their problems will not be attributed erroneously to +authors of previous versions. + + Some devices are designed to deny users access to install or run +modified versions of the software inside them, although the manufacturer +can do so. This is fundamentally incompatible with the aim of +protecting users' freedom to change the software. The systematic +pattern of such abuse occurs in the area of products for individuals to +use, which is precisely where it is most unacceptable. Therefore, we +have designed this version of the GPL to prohibit the practice for those +products. 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If your program is a subroutine library, you +may consider it more useful to permit linking proprietary applications with +the library. If this is what you want to do, use the GNU Lesser General +Public License instead of this License. But first, please read +. diff --git a/cope2n-ai-fi/modules/sdsvtr/README.md b/cope2n-ai-fi/modules/sdsvtr/README.md new file mode 100755 index 0000000..5cbd0b0 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/README.md @@ -0,0 +1,76 @@ +## Introduction +This repo serve as source code storage for the Standalone SATRN Text Recognizer packages. +Installing this package requires 3 additional packages: PyTorch, MMCV, and colorama. + + +## Installation +```shell +conda create -n sdsvtr-env python=3.8 +conda activate sdsvtr-env +conda install pytorch torchvision pytorch-cuda=11.6 -c pytorch -c nvidia +pip install -U openmim +mim install mmcv-full +pip install colorama +git clone https://github.com/moewiee/sdsvtr.git +cd sdsvtr +pip install -v -e . +``` + +## Basic Usage +```python +from sdsvtr import StandaloneSATRNRunner +runner = StandaloneSATRNRunner(version='satrn-lite-general-pretrain-20230106', return_confident=False, device='cpu') +``` + +The `version` parameter accepts version names declared in `sdsvtr.factory.online_model_factory` or a local path such as `$DIR\model.pth`. To check for available versions in the hub, run: +```python +import sdsvtr +print(sdsvtr.__hub_available_versions__) +``` + +Naturally, a `StandaloneSATRNRunner` instance assumes the input to be one of the following: an instance of `np.ndarray`, an instance of `str`, a list of `np.ndarray`, or a list of `str`, for examples: +```python +import numpy as np +from sdsvtr import StandaloneSATRNRunner +runner = StandaloneSATRNRunner(version='satrn-lite-general-pretrain-20230106', return_confident=False, device='cpu') + +dummy_list = [np.ndarray((32,128,3)) for _ in range(100)] +result = runner(dummy_list) +``` + +To run with a specific batchsize, try: +```python +import numpy as np +from sdsvtr import StandaloneSATRNRunner +runner = StandaloneSATRNRunner(version='satrn-lite-general-pretrain-20230106', return_confident=False, device='cuda:0') + +dummy_list = [np.ndarray(1,3,32,128) for _ in range(100)] +bs = min(32, len(imageFiles)) # batchsize = 32 + +all_results = [] +while len(dummy_list) > 0: + dummy_batch = dummy_list[:bs] + dummy_list = dummy_list[bs:] + all_results += runner(dummy_batch) +``` + +## Version Changelog +* **[0.0.1]** +Initial version with specified features. + + +* **[0.0.2]** +Update online model hub. + + +* **[0.0.3]** +Update API now able to inference with 4 types of inputs: list/instance of `np.ndarray`/`str` +Update API interface with `return_confident` parameter. +Update `wget` check and `sha256` check for model hub retrieval. + +* **[0.0.4]** +Update decoder module with EarlyStopping mechanism to possibly improve inference speed on short sequences. +Update API interface with optional argument `max_seq_len_overwrite` to overwrite checkpoint's `max_seq_len` config. + +* **[0.0.5]** +Allow inference on a specific device diff --git a/cope2n-ai-fi/modules/sdsvtr/requirements.txt b/cope2n-ai-fi/modules/sdsvtr/requirements.txt new file mode 100755 index 0000000..f4a74db --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/requirements.txt @@ -0,0 +1,3 @@ +torch +colorama +mmcv-full \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvtr/sdsvtr/__init__.py b/cope2n-ai-fi/modules/sdsvtr/sdsvtr/__init__.py new file mode 100755 index 0000000..dd8470d --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/sdsvtr/__init__.py @@ -0,0 +1,3 @@ +from .api import StandaloneSATRNRunner +from .version import __version__ +from .factory import __hub_available_versions__ \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvtr/sdsvtr/api.py b/cope2n-ai-fi/modules/sdsvtr/sdsvtr/api.py new file mode 100755 index 0000000..566a904 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/sdsvtr/api.py @@ -0,0 +1,106 @@ + +import torch +import torch.nn as nn + +from colorama import Fore, Style + +from .converter import AttnConvertor +from .backbone import ResNetABI +from .encoder import SatrnEncoder +from .decoder import NRTRDecoder +from .transform import DataPipelineSATRN +from .fp16_utils import patch_norm_fp32 +from .factory import _get as get_version + + +class SATRN(nn.Module): + """Standalone implementation for SATRN encode-decode recognizer.""" + + def __init__(self, + version, + return_confident=False, + device='cpu', + max_seq_len_overwrite=None): + + super().__init__() + + checkpoint = get_version(version) + + pt = torch.load(checkpoint, 'cpu') + if device == 'cpu': + print(Fore.RED + 'Warning: You are using CPU inference method. Init with device=cuda: to run with CUDA method.' + Style.RESET_ALL) + + self.pipeline = DataPipelineSATRN(**pt['pipeline_args'], device=device) + + # Convertor + self.label_convertor = AttnConvertor(**pt['label_convertor_args'], return_confident=return_confident) + + # Backbone + self.backbone = ResNetABI(**pt['backbone_args']) + + # Encoder module + self.encoder = SatrnEncoder(**pt['encoder_args']) + + # Decoder module + decoder_max_seq_len = max_seq_len_overwrite if max_seq_len_overwrite is not None else pt['max_seq_len'] + self.decoder = NRTRDecoder( + **pt['decoder_args'], + max_seq_len=decoder_max_seq_len, + num_classes=self.label_convertor.num_classes(), + start_idx=self.label_convertor.start_idx, + padding_idx=self.label_convertor.padding_idx, + return_confident=return_confident, + end_idx=self.label_convertor.end_idx + ) + + self.load_state_dict(pt['state_dict'], strict=True) + print(f'Text recognition from version {version}.') + + if device != 'cpu': + self = self.to(device) + self = self.half() + patch_norm_fp32(self) + + self.eval() + for param in self.parameters(): + param.requires_grad = False + + def extract_feat(self, img): + x = self.backbone(img) + + return x + + def forward(self, img): + """Test function with test time augmentation. + + Args: + imgs (torch.Tensor): Image input tensor. + + Returns: + list[str]: Text label result of each image. + """ + img = self.pipeline(img) + feat = self.extract_feat(img) + out_enc = self.encoder(feat) + out_dec = self.decoder(out_enc).cpu().numpy() + label_strings = self.label_convertor(out_dec) + + return label_strings + + +class StandaloneSATRNRunner: + def __init__(self, + version, + return_confident, + device='cpu', + max_seq_len_overwrite=None): + self.device = device + self.model = SATRN(version=version, + return_confident=return_confident, + device=self.device, + max_seq_len_overwrite=max_seq_len_overwrite) + + def __call__(self, imgs): + results = self.model(imgs) + + return results \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvtr/sdsvtr/backbone.py b/cope2n-ai-fi/modules/sdsvtr/sdsvtr/backbone.py new file mode 100755 index 0000000..29c2509 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/sdsvtr/backbone.py @@ -0,0 +1,159 @@ +import torch.nn as nn + +def conv3x3(in_planes, out_planes, stride=1): + """3x3 convolution with padding.""" + return nn.Conv2d( + in_planes, + out_planes, + kernel_size=3, + stride=stride, + padding=1, + bias=False) + + +def conv1x1(in_planes, out_planes): + """1x1 convolution with padding.""" + return nn.Conv2d( + in_planes, out_planes, kernel_size=1, stride=1, padding=0, bias=False) + + +class BasicBlock(nn.Module): + + expansion = 1 + + def __init__(self, + inplanes, + planes, + stride=1, + downsample=None, + use_conv1x1=False): + super(BasicBlock, self).__init__() + + if use_conv1x1: + self.conv1 = conv1x1(inplanes, planes) + self.conv2 = conv3x3(planes, planes * self.expansion, stride) + else: + self.conv1 = conv3x3(inplanes, planes, stride) + self.conv2 = conv3x3(planes, planes * self.expansion) + + self.planes = planes + self.bn1 = nn.BatchNorm2d(planes) + self.relu = nn.ReLU(inplace=True) + self.bn2 = nn.BatchNorm2d(planes * self.expansion) + self.downsample = downsample + self.stride = stride + + def forward(self, x): + residual = x + out = self.conv1(x) + out = self.bn1(out) + out = self.relu(out) + out = self.conv2(out) + out = self.bn2(out) + if self.downsample is not None: + residual = self.downsample(x) + out += residual + out = self.relu(out) + + return out + +class ResNetABI(nn.Module): + """Implement ResNet backbone for text recognition, modified from `ResNet. + + `_ and + ``_ + + Args: + in_channels (int): Number of channels of input image tensor. + stem_channels (int): Number of stem channels. + base_channels (int): Number of base channels. + arch_settings (list[int]): List of BasicBlock number for each stage. + strides (Sequence[int]): Strides of the first block of each stage. + out_indices (None | Sequence[int]): Indices of output stages. If not + specified, only the last stage will be returned. + last_stage_pool (bool): If True, add `MaxPool2d` layer to last stage. + """ + + def __init__(self, + in_channels=3, + stem_channels=32, + base_channels=32, + arch_settings=[3, 4, 6, 6, 3], + strides=[2, 1, 2, 1, 1], + out_indices=None, + last_stage_pool=False): + super().__init__() + + self.out_indices = out_indices + self.last_stage_pool = last_stage_pool + self.block = BasicBlock + self.inplanes = stem_channels + + self._make_stem_layer(in_channels, stem_channels) + + self.res_layers = [] + planes = base_channels + for i, num_blocks in enumerate(arch_settings): + stride = strides[i] + res_layer = self._make_layer( + block=self.block, + inplanes=self.inplanes, + planes=planes, + blocks=num_blocks, + stride=stride) + self.inplanes = planes * self.block.expansion + planes *= 2 + layer_name = f'layer{i + 1}' + self.add_module(layer_name, res_layer) + self.res_layers.append(layer_name) + + def _make_layer(self, block, inplanes, planes, blocks, stride=1): + layers = [] + downsample = None + if stride != 1 or inplanes != planes: + downsample = nn.Sequential( + nn.Conv2d(inplanes, planes, 1, stride, bias=False), + nn.BatchNorm2d(planes), + ) + layers.append( + block( + inplanes, + planes, + use_conv1x1=True, + stride=stride, + downsample=downsample)) + inplanes = planes + for _ in range(1, blocks): + layers.append(block(inplanes, planes, use_conv1x1=True)) + + return nn.Sequential(*layers) + + def _make_stem_layer(self, in_channels, stem_channels): + self.conv1 = nn.Conv2d( + in_channels, stem_channels, kernel_size=3, stride=1, padding=1) + self.bn1 = nn.BatchNorm2d(stem_channels) + self.relu1 = nn.ReLU(inplace=True) + + def forward(self, x): + """ + Args: + x (Tensor): Image tensor of shape :math:`(N, 3, H, W)`. + + Returns: + Tensor or list[Tensor]: Feature tensor. Its shape depends on + ResNetABI's config. It can be a list of feature outputs at specific + layers if ``out_indices`` is specified. + """ + + x = self.conv1(x) + x = self.bn1(x) + x = self.relu1(x) + + outs = [] + for i, layer_name in enumerate(self.res_layers): + res_layer = getattr(self, layer_name) + x = res_layer(x) + if self.out_indices and i in self.out_indices: + outs.append(x) + + return tuple(outs) if self.out_indices else x diff --git a/cope2n-ai-fi/modules/sdsvtr/sdsvtr/conv.py b/cope2n-ai-fi/modules/sdsvtr/sdsvtr/conv.py new file mode 100755 index 0000000..950ec0c --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/sdsvtr/conv.py @@ -0,0 +1,173 @@ +import warnings +import torch.nn as nn +from torch.nn.modules.instancenorm import _InstanceNorm +from torch.nn.modules.batchnorm import _BatchNorm +from mmcv.cnn import build_padding_layer, build_conv_layer, build_norm_layer, build_activation_layer + +class ConvModule(nn.Module): + """A conv block that bundles conv/norm/activation layers. + + This block simplifies the usage of convolution layers, which are commonly + used with a norm layer (e.g., BatchNorm) and activation layer (e.g., ReLU). + It is based upon three build methods: `build_conv_layer()`, + `build_norm_layer()` and `build_activation_layer()`. + + Besides, we add some additional features in this module. + 1. Automatically set `bias` of the conv layer. + 2. Spectral norm is supported. + 3. More padding modes are supported. Before PyTorch 1.5, nn.Conv2d only + supports zero and circular padding, and we add "reflect" padding mode. + + Args: + in_channels (int): Number of channels in the input feature map. + Same as that in ``nn._ConvNd``. + out_channels (int): Number of channels produced by the convolution. + Same as that in ``nn._ConvNd``. + kernel_size (int | tuple[int]): Size of the convolving kernel. + Same as that in ``nn._ConvNd``. + stride (int | tuple[int]): Stride of the convolution. + Same as that in ``nn._ConvNd``. + padding (int | tuple[int]): Zero-padding added to both sides of + the input. Same as that in ``nn._ConvNd``. + dilation (int | tuple[int]): Spacing between kernel elements. + Same as that in ``nn._ConvNd``. + groups (int): Number of blocked connections from input channels to + output channels. Same as that in ``nn._ConvNd``. + bias (bool | str): If specified as `auto`, it will be decided by the + norm_cfg. Bias will be set as True if `norm_cfg` is None, otherwise + False. Default: "auto". + conv_cfg (dict): Config dict for convolution layer. Default: None, + which means using conv2d. + norm_cfg (dict): Config dict for normalization layer. Default: None. + act_cfg (dict): Config dict for activation layer. + Default: dict(type='ReLU'). + inplace (bool): Whether to use inplace mode for activation. + Default: True. + with_spectral_norm (bool): Whether use spectral norm in conv module. + Default: False. + padding_mode (str): If the `padding_mode` has not been supported by + current `Conv2d` in PyTorch, we will use our own padding layer + instead. Currently, we support ['zeros', 'circular'] with official + implementation and ['reflect'] with our own implementation. + Default: 'zeros'. + order (tuple[str]): The order of conv/norm/activation layers. It is a + sequence of "conv", "norm" and "act". Common examples are + ("conv", "norm", "act") and ("act", "conv", "norm"). + Default: ('conv', 'norm', 'act'). + """ + + _abbr_ = 'conv_block' + + def __init__(self, + in_channels, + out_channels, + kernel_size, + stride=1, + padding=0, + dilation=1, + groups=1, + bias='auto', + conv_cfg=None, + norm_cfg=None, + act_cfg=dict(type='ReLU'), + inplace=True, + with_spectral_norm=False, + padding_mode='zeros', + order=('conv', 'norm', 'act')): + super(ConvModule, self).__init__() + assert conv_cfg is None or isinstance(conv_cfg, dict) + assert norm_cfg is None or isinstance(norm_cfg, dict) + assert act_cfg is None or isinstance(act_cfg, dict) + official_padding_mode = ['zeros', 'circular'] + self.conv_cfg = conv_cfg + self.norm_cfg = norm_cfg + self.act_cfg = act_cfg + self.inplace = inplace + self.with_spectral_norm = with_spectral_norm + self.with_explicit_padding = padding_mode not in official_padding_mode + self.order = order + assert isinstance(self.order, tuple) and len(self.order) == 3 + assert set(order) == set(['conv', 'norm', 'act']) + + self.with_norm = norm_cfg is not None + self.with_activation = act_cfg is not None + # if the conv layer is before a norm layer, bias is unnecessary. + if bias == 'auto': + bias = not self.with_norm + self.with_bias = bias + + if self.with_explicit_padding: + pad_cfg = dict(type=padding_mode) + self.padding_layer = build_padding_layer(pad_cfg, padding) + + # reset padding to 0 for conv module + conv_padding = 0 if self.with_explicit_padding else padding + # build convolution layer + self.conv = build_conv_layer( + conv_cfg, + in_channels, + out_channels, + kernel_size, + stride=stride, + padding=conv_padding, + dilation=dilation, + groups=groups, + bias=bias) + # export the attributes of self.conv to a higher level for convenience + self.in_channels = self.conv.in_channels + self.out_channels = self.conv.out_channels + self.kernel_size = self.conv.kernel_size + self.stride = self.conv.stride + self.padding = padding + self.dilation = self.conv.dilation + self.transposed = self.conv.transposed + self.output_padding = self.conv.output_padding + self.groups = self.conv.groups + + if self.with_spectral_norm: + self.conv = nn.utils.spectral_norm(self.conv) + + # build normalization layers + if self.with_norm: + # norm layer is after conv layer + if order.index('norm') > order.index('conv'): + norm_channels = out_channels + else: + norm_channels = in_channels + self.norm_name, norm = build_norm_layer(norm_cfg, norm_channels) + self.add_module(self.norm_name, norm) + if self.with_bias: + if isinstance(norm, (_BatchNorm, _InstanceNorm)): + warnings.warn( + 'Unnecessary conv bias before batch/instance norm') + else: + self.norm_name = None + + # build activation layer + if self.with_activation: + act_cfg_ = act_cfg.copy() + # nn.Tanh has no 'inplace' argument + if act_cfg_['type'] not in [ + 'Tanh', 'PReLU', 'Sigmoid', 'HSigmoid', 'Swish' + ]: + act_cfg_.setdefault('inplace', inplace) + self.activate = build_activation_layer(act_cfg_) + + @property + def norm(self): + if self.norm_name: + return getattr(self, self.norm_name) + else: + return None + + def forward(self, x, activate=True, norm=True): + for layer in self.order: + if layer == 'conv': + if self.with_explicit_padding: + x = self.padding_layer(x) + x = self.conv(x) + elif layer == 'norm' and norm and self.with_norm: + x = self.norm(x) + elif layer == 'act' and activate and self.with_activation: + x = self.activate(x) + return x \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvtr/sdsvtr/converter.py b/cope2n-ai-fi/modules/sdsvtr/sdsvtr/converter.py new file mode 100755 index 0000000..4d9bf82 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/sdsvtr/converter.py @@ -0,0 +1,152 @@ +import torch +import numpy as np + +class BaseConvertor: + """Convert between text, index and tensor for text recognize pipeline. + + Args: + dict_type (str): Type of dict, options are 'DICT36', 'DICT37', 'DICT90' + and 'DICT91'. + dict_file (None|str): Character dict file path. If not none, + the dict_file is of higher priority than dict_type. + dict_list (None|list[str]): Character list. If not none, the list + is of higher priority than dict_type, but lower than dict_file. + """ + start_idx = end_idx = padding_idx = 0 + unknown_idx = None + lower = False + + DICT36 = tuple('0123456789abcdefghijklmnopqrstuvwxyz') + DICT63 = tuple('0123456789abcdefghijklmnopqrstuvwxyz' + 'ABCDEFGHIJKLMNOPQRSTUVWXYZ') + DICT90 = tuple('0123456789abcdefghijklmnopqrstuvwxyz' + 'ABCDEFGHIJKLMNOPQRSTUVWXYZ!"#$%&\'()' + '*+,-./:;<=>?@[\\]_`~') + DICT131 = tuple('0123456789abcdefghijklmnopqrstuvwxyz' + '!"#$%&\'()' + '*+,-./:;<=>?@[\\]_`~' + 'ạảãàáâậầấẩẫăắằặẳẵóòọõỏôộổỗồốơờớợởỡéèẻẹẽêếềệểễúùụủũưựữửừứíìịỉĩýỳỷỵỹđ') + DICT224 = tuple('0123456789abcdefghijklmnopqrstuvwxyz' + 'ABCDEFGHIJKLMNOPQRSTUVWXYZ!"#$%&\'()' + '*+,-./:;<=>?@[\\]_`~{}|^ ̂' + 'ạảãàáâậầấẩẫăắằặẳẵóòọõỏôộổỗồốơờớợởỡéèẻẹẽêếềệểễúùụủũưựữửừứíìịỉĩýỳỷỵỹđ' + 'ẠẢÃÀÁÂẬẦẤẨẪĂẮẰẶẲẴÓÒỌÕỎÔỘỔỖỒỐƠỜỚỢỞỠÉÈẺẸẼÊẾỀỆỂỄÚÙỤỦŨƯỰỮỬỪỨÍÌỊỈĨÝỲỶỴỸĐ✪') + + def __init__(self, dict_type='DICT90'): + assert dict_type in ('DICT36', 'DICT63', 'DICT90', 'DICT131', 'DICT224') + self.idx2char = [] + + if dict_type == 'DICT36': + self.idx2char = list(self.DICT36) + elif dict_type == 'DICT63': + self.idx2char = list(self.DICT63) + elif dict_type == 'DICT90': + self.idx2char = list(self.DICT90) + elif dict_type == 'DICT131': + self.idx2char = list(self.DICT131) + elif dict_type == 'DICT224': + self.idx2char = list(self.DICT224) + else: + raise ('Dictonary not implemented') + + assert len(set(self.idx2char)) == len(self.idx2char), \ + 'Invalid dictionary: Has duplicated characters.' + + self.char2idx = {char: idx for idx, char in enumerate(self.idx2char)} + + def num_classes(self): + """Number of output classes.""" + return len(self.idx2char) + + +class AttnConvertor(BaseConvertor): + """Convert between text, index and tensor for encoder-decoder based + pipeline. + + Args: + dict_type (str): Type of dict, should be one of {'DICT36', 'DICT90'}. + dict_file (None|str): Character dict file path. If not none, + higher priority than dict_type. + dict_list (None|list[str]): Character list. If not none, higher + priority than dict_type, but lower than dict_file. + with_unknown (bool): If True, add `UKN` token to class. + max_seq_len (int): Maximum sequence length of label. + lower (bool): If True, convert original string to lower case. + start_end_same (bool): Whether use the same index for + start and end token or not. Default: True. + """ + + def __init__(self, + dict_type='DICT90', + with_unknown=True, + max_seq_len=40, + lower=False, + start_end_same=True, + return_confident=False, + **kwargs): + super().__init__(dict_type) + assert isinstance(with_unknown, bool) + assert isinstance(max_seq_len, int) + assert isinstance(lower, bool) + + self.with_unknown = with_unknown + self.max_seq_len = max_seq_len + self.lower = lower + self.start_end_same = start_end_same + self.return_confident = return_confident + + self.update_dict() + + def update_dict(self): + start_end_token = '' + unknown_token = '' + padding_token = '' + + # unknown + self.unknown_idx = None + if self.with_unknown: + self.idx2char.append(unknown_token) + self.unknown_idx = len(self.idx2char) - 1 + + # BOS/EOS + self.idx2char.append(start_end_token) + self.start_idx = len(self.idx2char) - 1 + if not self.start_end_same: + self.idx2char.append(start_end_token) + self.end_idx = len(self.idx2char) - 1 + + # padding + self.idx2char.append(padding_token) + self.padding_idx = len(self.idx2char) - 1 + + # update char2idx + self.char2idx = {} + for idx, char in enumerate(self.idx2char): + self.char2idx[char] = idx + + def __call__(self, indexes): + strings = [] + confidents = [] + if self.return_confident: + b,sq,_ = indexes.shape + for idx in range(b): + index = indexes[idx, :, :] + chars = index.argmax(-1) + confident = index.max(-1) + i = 0 + while i < sq and chars[i] != self.end_idx and chars[i] != self.padding_idx: i += 1 + chars = chars[:i] + confident = confident[:i].min() + string = [self.idx2char[i] for i in chars] + strings.append(''.join(string)) + confidents.append(confident) + + return strings, confidents + else: + for index in indexes: + i, l = 0, len(index) + while i < l and index[i] != self.end_idx and index[i] != self.padding_idx: i += 1 + index = index[:i] + string = [self.idx2char[i] for i in index] + strings.append(''.join(string)) + return strings \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvtr/sdsvtr/decoder.py b/cope2n-ai-fi/modules/sdsvtr/sdsvtr/decoder.py new file mode 100755 index 0000000..b4ec51a --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/sdsvtr/decoder.py @@ -0,0 +1,278 @@ +import torch +import torch.nn as nn +import torch.nn.functional as F +import math +import numpy as np +from .encoder import MultiHeadAttention + + +class PositionwiseFeedForward(nn.Module): + """Two-layer feed-forward module. + + Args: + d_in (int): The dimension of the input for feedforward + network model. + d_hid (int): The dimension of the feedforward + network model. + dropout (float): Dropout layer on feedforward output. + act_cfg (dict): Activation cfg for feedforward module. + """ + + def __init__(self, d_in, d_hid, dropout=0.1): + super().__init__() + self.w_1 = nn.Linear(d_in, d_hid) + self.w_2 = nn.Linear(d_hid, d_in) + self.act = nn.GELU() + self.dropout = nn.Dropout(dropout) + + def forward(self, x): + x = self.w_1(x) + x = self.act(x) + x = self.w_2(x) + x = self.dropout(x) + + return x + + +class PositionalEncoding(nn.Module): + """Fixed positional encoding with sine and cosine functions.""" + + def __init__(self, d_hid=512, n_position=200): + super().__init__() + + # Not a parameter + # Position table of shape (1, n_position, d_hid) + self.register_buffer( + 'position_table', + self._get_sinusoid_encoding_table(n_position, d_hid)) + + def _get_sinusoid_encoding_table(self, n_position, d_hid): + """Sinusoid position encoding table.""" + denominator = torch.Tensor([ + 1.0 / np.power(10000, 2 * (hid_j // 2) / d_hid) + for hid_j in range(d_hid) + ]) + denominator = denominator.view(1, -1) + pos_tensor = torch.arange(n_position).unsqueeze(-1).float() + sinusoid_table = pos_tensor * denominator + sinusoid_table[:, 0::2] = torch.sin(sinusoid_table[:, 0::2]) + sinusoid_table[:, 1::2] = torch.cos(sinusoid_table[:, 1::2]) + + return sinusoid_table.unsqueeze(0) + + def forward(self, x): + """ + Args: + x (Tensor): Tensor of shape (batch_size, pos_len, d_hid, ...) + """ + self.device = x.device + x = x + self.position_table[:, :x.size(1)].clone().detach() + return x + + + +class TFDecoderLayer(nn.Module): + """Transformer Decoder Layer. + + Args: + d_model (int): The number of expected features + in the decoder inputs (default=512). + d_inner (int): The dimension of the feedforward + network model (default=256). + n_head (int): The number of heads in the + multiheadattention models (default=8). + d_k (int): Total number of features in key. + d_v (int): Total number of features in value. + dropout (float): Dropout layer on attn_output_weights. + qkv_bias (bool): Add bias in projection layer. Default: False. + act_cfg (dict): Activation cfg for feedforward module. + operation_order (tuple[str]): The execution order of operation + in transformer. Such as ('self_attn', 'norm', 'enc_dec_attn', + 'norm', 'ffn', 'norm') or ('norm', 'self_attn', 'norm', + 'enc_dec_attn', 'norm', 'ffn'). + Default:None. + """ + + def __init__(self, + d_model=512, + d_inner=256, + n_head=8, + d_k=64, + d_v=64, + dropout=0.1, + qkv_bias=False): + super().__init__() + + self.norm1 = nn.LayerNorm(d_model) + self.norm2 = nn.LayerNorm(d_model) + self.norm3 = nn.LayerNorm(d_model) + + self.self_attn = MultiHeadAttention( + n_head, d_model, d_k, d_v, dropout=dropout, qkv_bias=qkv_bias) + + self.enc_attn = MultiHeadAttention( + n_head, d_model, d_k, d_v, dropout=dropout, qkv_bias=qkv_bias) + + self.mlp = PositionwiseFeedForward( + d_model, d_inner, dropout=dropout) + + def forward(self, + dec_input, + enc_output, + self_attn_mask=None, + dec_enc_attn_mask=None): + dec_input_norm = self.norm1(dec_input) + dec_attn_out = self.self_attn(dec_input_norm, dec_input_norm, + dec_input_norm, self_attn_mask) + dec_attn_out += dec_input + + enc_dec_attn_in = self.norm2(dec_attn_out) + enc_dec_attn_out = self.enc_attn(enc_dec_attn_in, enc_output, + enc_output, dec_enc_attn_mask) + enc_dec_attn_out += dec_attn_out + + mlp_out = self.mlp(self.norm3(enc_dec_attn_out)) + mlp_out += enc_dec_attn_out + + return mlp_out + +class NRTRDecoder(nn.Module): + """Transformer Decoder block with self attention mechanism. + + Args: + n_layers (int): Number of attention layers. + d_embedding (int): Language embedding dimension. + n_head (int): Number of parallel attention heads. + d_k (int): Dimension of the key vector. + d_v (int): Dimension of the value vector. + d_model (int): Dimension :math:`D_m` of the input from previous model. + d_inner (int): Hidden dimension of feedforward layers. + n_position (int): Length of the positional encoding vector. Must be + greater than ``max_seq_len``. + dropout (float): Dropout rate. + num_classes (int): Number of output classes :math:`C`. + max_seq_len (int): Maximum output sequence length :math:`T`. + start_idx (int): The index of ``. + padding_idx (int): The index of ``. + init_cfg (dict or list[dict], optional): Initialization configs. + + Warning: + This decoder will not predict the final class which is assumed to be + ``. Therefore, its output size is always :math:`C - 1`. `` + is also ignored by loss as specified in + :obj:`mmocr.models.textrecog.recognizer.EncodeDecodeRecognizer`. + """ + + def __init__(self, + n_layers=6, + d_embedding=512, + n_head=8, + d_k=64, + d_v=64, + d_model=512, + d_inner=256, + n_position=200, + dropout=0.1, + num_classes=93, + max_seq_len=40, + start_idx=1, + padding_idx=92, + return_confident=False, + end_idx=None, + **kwargs): + super().__init__() + + self.padding_idx = padding_idx + self.start_idx = start_idx + self.max_seq_len = max_seq_len + + self.trg_word_emb = nn.Embedding( + num_classes, d_embedding, padding_idx=padding_idx) + + self.position_enc = PositionalEncoding( + d_embedding, n_position=n_position) + + self.layer_stack = nn.ModuleList([ + TFDecoderLayer( + d_model, d_inner, n_head, d_k, d_v, dropout=dropout, **kwargs) + for _ in range(n_layers) + ]) + self.layer_norm = nn.LayerNorm(d_model, eps=1e-6) + + pred_num_class = num_classes - 1 # ignore padding_idx + self.classifier = nn.Linear(d_model, pred_num_class) + + self.return_confident = return_confident + self.end_idx = end_idx + + @staticmethod + def get_pad_mask(seq, pad_idx): + + return (seq != pad_idx).unsqueeze(-2) + + @staticmethod + def get_subsequent_mask(seq): + """For masking out the subsequent info.""" + len_s = seq.size(1) + subsequent_mask = 1 - torch.triu( + torch.ones((len_s, len_s), device=seq.device), diagonal=1) + subsequent_mask = subsequent_mask.unsqueeze(0).bool() + + return subsequent_mask + + def _attention(self, trg_seq, src, src_mask=None): + trg_embedding = self.trg_word_emb(trg_seq) + trg_pos_encoded = self.position_enc(trg_embedding) + trg_mask = self.get_pad_mask( + trg_seq, + pad_idx=self.padding_idx) & self.get_subsequent_mask(trg_seq) + output = trg_pos_encoded + for dec_layer in self.layer_stack: + output = dec_layer( + output, + src, + self_attn_mask=trg_mask, + dec_enc_attn_mask=src_mask) + output = self.layer_norm(output) + + return output + + def _get_mask(self, logit): + N, T, _ = logit.size() + mask = logit.new_ones((N, T)) + + return mask + + def forward(self, out_enc): + src_mask = self._get_mask(out_enc) + N = out_enc.size(0) + init_target_seq = torch.full((N, self.max_seq_len + 1), + self.padding_idx, + device=out_enc.device, + dtype=torch.long) + # bsz * seq_len + init_target_seq[:, 0] = self.start_idx + + outputs = [] + for step in range(0, self.max_seq_len): + decoder_output = self._attention( + trg_seq=init_target_seq, + src=out_enc, + src_mask=src_mask) + if self.return_confident: + step_result = torch.softmax(self.classifier(decoder_output[:, step, :]), -1) + next_step_init = step_result.argmax(-1) + init_target_seq[:, step + 1] = next_step_init + if next_step_init.min() >= self.end_idx: + break + else: + step_result = self.classifier(decoder_output[:, step, :]).argmax(-1) + init_target_seq[:, step + 1] = step_result + if step_result.min() >= self.end_idx: + break + + outputs.append(step_result) + + outputs = torch.stack(outputs, dim=1) + + return outputs \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvtr/sdsvtr/encoder.py b/cope2n-ai-fi/modules/sdsvtr/sdsvtr/encoder.py new file mode 100755 index 0000000..6ccb612 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/sdsvtr/encoder.py @@ -0,0 +1,317 @@ +import torch +import torch.nn as nn +import torch.nn.functional as F +import numpy as np +import math +from .conv import ConvModule + + +class LocalityAwareFeedforward(nn.Module): + """Locality-aware feedforward layer in SATRN, see `SATRN. + + `_ + """ + + def __init__(self, + d_in, + d_hid, + dropout=0.1): + super().__init__() + self.conv1 = ConvModule( + d_in, + d_hid, + kernel_size=1, + padding=0, + bias=False, + norm_cfg=dict(type='BN'), + act_cfg=dict(type='ReLU')) + + self.depthwise_conv = ConvModule( + d_hid, + d_hid, + kernel_size=3, + padding=1, + bias=False, + groups=d_hid, + norm_cfg=dict(type='BN'), + act_cfg=dict(type='ReLU')) + + self.conv2 = ConvModule( + d_hid, + d_in, + kernel_size=1, + padding=0, + bias=False, + norm_cfg=dict(type='BN'), + act_cfg=dict(type='ReLU')) + + def forward(self, x): + x = self.conv1(x) + x = self.depthwise_conv(x) + x = self.conv2(x) + + return x + + +class ScaledDotProductAttention(nn.Module): + """Scaled Dot-Product Attention Module. This code is adopted from + https://github.com/jadore801120/attention-is-all-you-need-pytorch. + + Args: + temperature (float): The scale factor for softmax input. + attn_dropout (float): Dropout layer on attn_output_weights. + """ + + def __init__(self, temperature, attn_dropout=0.1): + super().__init__() + self.temperature = temperature + self.dropout = nn.Dropout(attn_dropout) + + def forward(self, q, k, v, mask=None): + + attn = torch.matmul(q / self.temperature, k.transpose(2, 3)) + + if mask is not None: + attn = attn.masked_fill(mask == 0, float('-inf')) + + attn = self.dropout(F.softmax(attn, dim=-1)) + output = torch.matmul(attn, v) + + return output, attn + + +class MultiHeadAttention(nn.Module): + """Multi-Head Attention module. + + Args: + n_head (int): The number of heads in the + multiheadattention models (default=8). + d_model (int): The number of expected features + in the decoder inputs (default=512). + d_k (int): Total number of features in key. + d_v (int): Total number of features in value. + dropout (float): Dropout layer on attn_output_weights. + qkv_bias (bool): Add bias in projection layer. Default: False. + """ + + def __init__(self, + n_head=8, + d_model=512, + d_k=64, + d_v=64, + dropout=0.1, + qkv_bias=False): + super().__init__() + self.n_head = n_head + self.d_k = d_k + self.d_v = d_v + + self.dim_k = n_head * d_k + self.dim_v = n_head * d_v + + self.linear_q = nn.Linear(self.dim_k, self.dim_k, bias=qkv_bias) + self.linear_k = nn.Linear(self.dim_k, self.dim_k, bias=qkv_bias) + self.linear_v = nn.Linear(self.dim_v, self.dim_v, bias=qkv_bias) + + self.attention = ScaledDotProductAttention(d_k**0.5, dropout) + + self.fc = nn.Linear(self.dim_v, d_model, bias=qkv_bias) + self.proj_drop = nn.Dropout(dropout) + + def forward(self, q, k, v, mask=None): + batch_size, len_q, _ = q.size() + _, len_k, _ = k.size() + + q = self.linear_q(q).view(batch_size, len_q, self.n_head, self.d_k) + k = self.linear_k(k).view(batch_size, len_k, self.n_head, self.d_k) + v = self.linear_v(v).view(batch_size, len_k, self.n_head, self.d_v) + + q, k, v = q.transpose(1, 2), k.transpose(1, 2), v.transpose(1, 2) + + if mask is not None: + if mask.dim() == 3: + mask = mask.unsqueeze(1) + elif mask.dim() == 2: + mask = mask.unsqueeze(1).unsqueeze(1) + + attn_out, _ = self.attention(q, k, v, mask=mask) + + attn_out = attn_out.transpose(1, 2).contiguous().view( + batch_size, len_q, self.dim_v) + + attn_out = self.fc(attn_out) + attn_out = self.proj_drop(attn_out) + + return attn_out + + +class SatrnEncoderLayer(nn.Module): + """""" + + def __init__(self, + d_model=512, + d_inner=512, + n_head=8, + d_k=64, + d_v=64, + dropout=0.1, + qkv_bias=False): + super().__init__() + self.norm1 = nn.LayerNorm(d_model) + self.attn = MultiHeadAttention( + n_head, d_model, d_k, d_v, qkv_bias=qkv_bias, dropout=dropout) + self.norm2 = nn.LayerNorm(d_model) + self.feed_forward = LocalityAwareFeedforward( + d_model, d_inner, dropout=dropout) + + def forward(self, x, h, w, mask=None): + n, hw, c = x.size() + residual = x + x = self.norm1(x) + x = residual + self.attn(x, x, x, mask) + residual = x + x = self.norm2(x) + x = x.transpose(1, 2).contiguous().view(n, c, h, w) + x = self.feed_forward(x) + x = x.view(n, c, hw).transpose(1, 2) + x = residual + x + return x + + +class Adaptive2DPositionalEncoding(nn.Module): + """Implement Adaptive 2D positional encoder for SATRN, see + `SATRN `_ + Modified from https://github.com/Media-Smart/vedastr + Licensed under the Apache License, Version 2.0 (the "License"); + Args: + d_hid (int): Dimensions of hidden layer. + n_height (int): Max height of the 2D feature output. + n_width (int): Max width of the 2D feature output. + dropout (int): Size of hidden layers of the model. + """ + + def __init__(self, + d_hid=512, + n_height=100, + n_width=100, + dropout=0.1): + super().__init__() + + h_position_encoder = self._get_sinusoid_encoding_table(n_height, d_hid) + h_position_encoder = h_position_encoder.transpose(0, 1) + h_position_encoder = h_position_encoder.view(1, d_hid, n_height, 1) + + w_position_encoder = self._get_sinusoid_encoding_table(n_width, d_hid) + w_position_encoder = w_position_encoder.transpose(0, 1) + w_position_encoder = w_position_encoder.view(1, d_hid, 1, n_width) + + self.register_buffer('h_position_encoder', h_position_encoder) + self.register_buffer('w_position_encoder', w_position_encoder) + + self.h_scale = self.scale_factor_generate(d_hid) + self.w_scale = self.scale_factor_generate(d_hid) + self.pool = nn.AdaptiveAvgPool2d(1) + self.dropout = nn.Dropout(p=dropout) + + def _get_sinusoid_encoding_table(self, n_position, d_hid): + """Sinusoid position encoding table.""" + denominator = torch.Tensor([ + 1.0 / np.power(10000, 2 * (hid_j // 2) / d_hid) + for hid_j in range(d_hid) + ]) + denominator = denominator.view(1, -1) + pos_tensor = torch.arange(n_position).unsqueeze(-1).float() + sinusoid_table = pos_tensor * denominator + sinusoid_table[:, 0::2] = torch.sin(sinusoid_table[:, 0::2]) + sinusoid_table[:, 1::2] = torch.cos(sinusoid_table[:, 1::2]) + + return sinusoid_table + + def scale_factor_generate(self, d_hid): + scale_factor = nn.Sequential( + nn.Conv2d(d_hid, d_hid, kernel_size=1), nn.ReLU(inplace=True), + nn.Conv2d(d_hid, d_hid, kernel_size=1), nn.Sigmoid()) + + return scale_factor + + def forward(self, x): + b, c, h, w = x.size() + + avg_pool = self.pool(x) + + h_pos_encoding = \ + self.h_scale(avg_pool) * self.h_position_encoder[:, :, :h, :] + w_pos_encoding = \ + self.w_scale(avg_pool) * self.w_position_encoder[:, :, :, :w] + + out = x + h_pos_encoding + w_pos_encoding + + out = self.dropout(out) + + return out + + +class SatrnEncoder(nn.Module): + """Implement encoder for SATRN, see `SATRN. + + `_. + + Args: + n_layers (int): Number of attention layers. + n_head (int): Number of parallel attention heads. + d_k (int): Dimension of the key vector. + d_v (int): Dimension of the value vector. + d_model (int): Dimension :math:`D_m` of the input from previous model. + n_position (int): Length of the positional encoding vector. Must be + greater than ``max_seq_len``. + d_inner (int): Hidden dimension of feedforward layers. + dropout (float): Dropout rate. + init_cfg (dict or list[dict], optional): Initialization configs. + """ + + def __init__(self, + n_layers=12, + n_head=8, + d_k=64, + d_v=64, + d_model=512, + n_position=100, + d_inner=256, + dropout=0.1, + **kwargs): + super().__init__() + self.d_model = d_model + self.position_enc = Adaptive2DPositionalEncoding( + d_hid=d_model, + n_height=n_position, + n_width=n_position, + dropout=dropout) + self.layer_stack = nn.ModuleList([ + SatrnEncoderLayer( + d_model, d_inner, n_head, d_k, d_v, dropout=dropout) + for _ in range(n_layers) + ]) + self.layer_norm = nn.LayerNorm(d_model) + + def forward(self, feat): + """ + Args: + feat (Tensor): Feature tensor of shape :math:`(N, D_m, H, W)`. + + Returns: + Tensor: A tensor of shape :math:`(N, T, D_m)`. + """ + feat = feat + self.position_enc(feat) + n, c, h, w = feat.size() + mask = feat.new_zeros((n, h, w)) + mask[:,:,:w] = 1 + + mask = mask.view(n, h * w) + feat = feat.view(n, c, h * w) + + output = feat.permute(0, 2, 1).contiguous() + for enc_layer in self.layer_stack: + output = enc_layer(output, h, w, mask) + output = self.layer_norm(output) + + return output \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvtr/sdsvtr/factory.py b/cope2n-ai-fi/modules/sdsvtr/sdsvtr/factory.py new file mode 100755 index 0000000..773d5a0 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/sdsvtr/factory.py @@ -0,0 +1,57 @@ +import os +import shutil +import colorama +import hashlib + +def sha256sum(filename): + h = hashlib.sha256() + b = bytearray(128*1024) + mv = memoryview(b) + with open(filename, 'rb', buffering=0) as f: + for n in iter(lambda : f.readinto(mv), 0): + h.update(mv[:n]) + return h.hexdigest() + + +online_model_factory = { + 'satrn-lite-general-pretrain-20230106': { + 'url': 'https://github.com/moewiee/satrn-model-factory/raw/main/jxqhbem4to.pth', + 'hash': 'b0069a72bf6fc080ad5d431d5ce650c3bfbab535141adef1631fce331cb1471c'}, + 'satrn-lite-captcha-finetune-20230108': { + 'url': 'https://github.com/moewiee/satrn-model-factory/raw/main/l27vitogmc.pth', + 'hash': 'efcbcf2955b6b21125b073f83828d2719e908c7303b0d9901e94be5a8efba916'}, + 'satrn-lite-handwritten-finetune-20230108': { + 'url': 'https://github.com/moewiee/satrn-model-factory/raw/main/lj9gkwelns.pth', + 'hash': 'bccd8e985b131fcd4701114af5ceaef098f2eac50654bbb1d828e7f829e711dd'}, +} + +__hub_available_versions__ = online_model_factory.keys() + +def _get(version): + use_online = version in __hub_available_versions__ + + if not use_online and not os.path.exists(version): + raise ValueError(f'Model version {version} not found online and not found local.') + + hub_path = os.path.join(os.path.dirname(os.path.dirname(__file__)), 'hub') + if not os.path.exists(hub_path): + os.makedirs(hub_path) + if use_online: + version_url = online_model_factory[version]['url'] + file_path = os.path.join(hub_path, os.path.basename(version_url)) + else: + file_path = os.path.join(hub_path, os.path.basename(version)) + + if not os.path.exists(file_path): + if use_online: + os.system(f'wget -O {file_path} {version_url}') + assert os.path.exists(file_path), \ + colorama.Fore.RED + 'wget failed while trying to retrieve from hub.' + colorama.Style.RESET_ALL + downloaded_hash = sha256sum(file_path) + if downloaded_hash != online_model_factory[version]['hash']: + os.remove(file_path) + raise ValueError(colorama.Fore.RED + 'sha256 hash doesnt match for version retrieved from hub.' + colorama.Style.RESET_ALL) + else: + shutil.copy2(version, file_path) + + return file_path \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvtr/sdsvtr/fp16_utils.py b/cope2n-ai-fi/modules/sdsvtr/sdsvtr/fp16_utils.py new file mode 100755 index 0000000..126ff02 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/sdsvtr/fp16_utils.py @@ -0,0 +1,78 @@ +import torch +import torch.nn as nn +import numpy as np +from collections import abc + + +def cast_tensor_type(inputs, src_type, dst_type): + """Recursively convert Tensor in inputs from src_type to dst_type. + + Args: + inputs: Inputs that to be casted. + src_type (torch.dtype): Source type.. + dst_type (torch.dtype): Destination type. + + Returns: + The same type with inputs, but all contained Tensors have been cast. + """ + if isinstance(inputs, nn.Module): + return inputs + elif isinstance(inputs, torch.Tensor): + return inputs.to(dst_type) + elif isinstance(inputs, str): + return inputs + elif isinstance(inputs, np.ndarray): + return inputs + elif isinstance(inputs, abc.Mapping): + return type(inputs)({ + k: cast_tensor_type(v, src_type, dst_type) + for k, v in inputs.items() + }) + elif isinstance(inputs, abc.Iterable): + return type(inputs)( + cast_tensor_type(item, src_type, dst_type) for item in inputs) + else: + return inputs + + +def patch_forward_method(func, src_type, dst_type, convert_output=True): + """Patch the forward method of a module. + + Args: + func (callable): The original forward method. + src_type (torch.dtype): Type of input arguments to be converted from. + dst_type (torch.dtype): Type of input arguments to be converted to. + convert_output (bool): Whether to convert the output back to src_type. + + Returns: + callable: The patched forward method. + """ + + def new_forward(*args, **kwargs): + output = func(*cast_tensor_type(args, src_type, dst_type), + **cast_tensor_type(kwargs, src_type, dst_type)) + if convert_output: + output = cast_tensor_type(output, dst_type, src_type) + return output + + return new_forward + + +def patch_norm_fp32(module): + """Recursively convert normalization layers from FP16 to FP32. + + Args: + module (nn.Module): The modules to be converted in FP16. + + Returns: + nn.Module: The converted module, the normalization layers have been + converted to FP32. + """ + if isinstance(module, (nn.modules.batchnorm._BatchNorm, nn.GroupNorm)): + module.float() + if isinstance(module, nn.GroupNorm) or torch.__version__ < '1.3': + module.forward = patch_forward_method(module.forward, torch.half, + torch.float) + for child in module.children(): + patch_norm_fp32(child) + return module \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvtr/sdsvtr/transform.py b/cope2n-ai-fi/modules/sdsvtr/sdsvtr/transform.py new file mode 100755 index 0000000..e366a4c --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/sdsvtr/transform.py @@ -0,0 +1,33 @@ +import torchvision.transforms.functional as TF +import cv2 +import torch + +class DataPipelineSATRN: + def __init__(self, + resize_height, + resize_width, + norm_mean, + norm_std, + device='cpu'): + self.resize_height = resize_height + self.resize_width = resize_width + self.norm_mean = norm_mean + self.norm_std = norm_std + self.device = device + + def __call__(self, imgs): + if not isinstance(imgs, list): + imgs = [imgs] + datas = [] + for img in imgs: + if isinstance(img, str): + img = cv2.imread(img) + data = torch.from_numpy(cv2.resize(img, (self.resize_width, self.resize_height), interpolation=cv2.INTER_LINEAR)) + datas.append(data) + + data = torch.stack(datas, dim=0) + data = data.to(self.device) + data = data.float().div_(255.).permute((0,3,1,2)) + TF.normalize(data, mean=self.norm_mean, std=self.norm_std, inplace=True) + + return data.half() if self.device != 'cpu' else data \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvtr/sdsvtr/version.py b/cope2n-ai-fi/modules/sdsvtr/sdsvtr/version.py new file mode 100755 index 0000000..a55ccd2 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/sdsvtr/version.py @@ -0,0 +1 @@ +__version__ = '0.0.5' \ No newline at end of file diff --git a/cope2n-ai-fi/modules/sdsvtr/setup.py b/cope2n-ai-fi/modules/sdsvtr/setup.py new file mode 100755 index 0000000..4df1557 --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/setup.py @@ -0,0 +1,187 @@ +import os +import os.path as osp +import shutil +import sys +import warnings +from setuptools import find_packages, setup + + +def readme(): + with open('README.md', encoding='utf-8') as f: + content = f.read() + return content + + +version_file = 'sdsvtr/version.py' +is_windows = sys.platform == 'win32' + + +def add_mim_extention(): + """Add extra files that are required to support MIM into the package. + + These files will be added by creating a symlink to the originals if the + package is installed in `editable` mode (e.g. pip install -e .), or by + copying from the originals otherwise. + """ + + # parse installment mode + if 'develop' in sys.argv: + # installed by `pip install -e .` + mode = 'symlink' + elif 'sdist' in sys.argv or 'bdist_wheel' in sys.argv: + # installed by `pip install .` + # or create source distribution by `python setup.py sdist` + mode = 'copy' + else: + return + + filenames = ['tools', 'configs', 'model-index.yml'] + repo_path = osp.dirname(__file__) + mim_path = osp.join(repo_path, 'mmocr', '.mim') + os.makedirs(mim_path, exist_ok=True) + + for filename in filenames: + if osp.exists(filename): + src_path = osp.join(repo_path, filename) + tar_path = osp.join(mim_path, filename) + + if osp.isfile(tar_path) or osp.islink(tar_path): + os.remove(tar_path) + elif osp.isdir(tar_path): + shutil.rmtree(tar_path) + + if mode == 'symlink': + src_relpath = osp.relpath(src_path, osp.dirname(tar_path)) + try: + os.symlink(src_relpath, tar_path) + except OSError: + # Creating a symbolic link on windows may raise an + # `OSError: [WinError 1314]` due to privilege. If + # the error happens, the src file will be copied + mode = 'copy' + warnings.warn( + f'Failed to create a symbolic link for {src_relpath}, ' + f'and it will be copied to {tar_path}') + else: + continue + + if mode == 'copy': + if osp.isfile(src_path): + shutil.copyfile(src_path, tar_path) + elif osp.isdir(src_path): + shutil.copytree(src_path, tar_path) + else: + warnings.warn(f'Cannot copy file {src_path}.') + else: + raise ValueError(f'Invalid mode {mode}') + + +def get_version(): + with open(version_file, 'r') as f: + exec(compile(f.read(), version_file, 'exec')) + import sys + + # return short version for sdist + if 'sdist' in sys.argv or 'bdist_wheel' in sys.argv: + return locals()['short_version'] + else: + return locals()['__version__'] + + +def parse_requirements(fname='requirements.txt', with_version=True): + """Parse the package dependencies listed in a requirements file but strip + specific version information. + + Args: + fname (str): Path to requirements file. + with_version (bool, default=False): If True, include version specs. + Returns: + info (list[str]): List of requirements items. + CommandLine: + python -c "import setup; print(setup.parse_requirements())" + """ + import re + import sys + from os.path import exists + require_fpath = fname + + def parse_line(line): + """Parse information from a line in a requirements text file.""" + if line.startswith('-r '): + # Allow specifying requirements in other files + target = line.split(' ')[1] + for info in parse_require_file(target): + yield info + else: + info = {'line': line} + if line.startswith('-e '): + info['package'] = line.split('#egg=')[1] + else: + # Remove versioning from the package + pat = '(' + '|'.join(['>=', '==', '>']) + ')' + parts = re.split(pat, line, maxsplit=1) + parts = [p.strip() for p in parts] + + info['package'] = parts[0] + if len(parts) > 1: + op, rest = parts[1:] + if ';' in rest: + # Handle platform specific dependencies + # http://setuptools.readthedocs.io/en/latest/setuptools.html#declaring-platform-specific-dependencies + version, platform_deps = map(str.strip, + rest.split(';')) + info['platform_deps'] = platform_deps + else: + version = rest # NOQA + info['version'] = (op, version) + yield info + + def parse_require_file(fpath): + with open(fpath, 'r') as f: + for line in f.readlines(): + line = line.strip() + if line and not line.startswith('#'): + for info in parse_line(line): + yield info + + def gen_packages_items(): + if exists(require_fpath): + for info in parse_require_file(require_fpath): + parts = [info['package']] + if with_version and 'version' in info: + parts.extend(info['version']) + if not sys.version.startswith('3.4'): + # apparently package_deps are broken in 3.4 + platform_deps = info.get('platform_deps') + if platform_deps is not None: + parts.append(';' + platform_deps) + item = ''.join(parts) + yield item + + packages = list(gen_packages_items()) + return packages + + +if __name__ == '__main__': + setup( + name='sdsvtr', + version=get_version(), + description='SDSV OCR Team Text Recognizer', + long_description=readme(), + long_description_content_type='text/markdown', + packages=find_packages(exclude=('configs', 'tools', 'demo')), + include_package_data=True, + url='https://github.com/open-mmlab/mmocr', + classifiers=[ + 'Development Status :: 4 - Beta', + 'License :: OSI Approved :: Apache Software License', + 'Operating System :: OS Independent', + 'Programming Language :: Python :: 3', + 'Programming Language :: Python :: 3.6', + 'Programming Language :: Python :: 3.7', + 'Programming Language :: Python :: 3.8', + 'Programming Language :: Python :: 3.9', + ], + license='Apache License 2.0', + install_requires=parse_requirements('requirements.txt'), + zip_safe=False) diff --git a/cope2n-ai-fi/modules/sdsvtr/test.py b/cope2n-ai-fi/modules/sdsvtr/test.py new file mode 100755 index 0000000..b929e7e --- /dev/null +++ b/cope2n-ai-fi/modules/sdsvtr/test.py @@ -0,0 +1,12 @@ +import numpy as np +from sdsvtr import StandaloneSATRNRunner +runner = StandaloneSATRNRunner(version='satrn-lite-general-pretrain-20230106', return_confident=False, device='cuda:1') + +dummy_list = [np.ndarray((32,128,3)) for _ in range(100)] +bs = 32 + +all_results = [] +while len(dummy_list) > 0: + dummy_batch = dummy_list[:bs] + dummy_list = dummy_list[bs:] + all_results += runner(dummy_batch) \ No newline at end of file diff --git a/cope2n-api/fwd_api/utils/S3_process.py b/cope2n-api/fwd_api/utils/S3_process.py index 0cdbb7e..60d8380 100755 --- a/cope2n-api/fwd_api/utils/S3_process.py +++ b/cope2n-api/fwd_api/utils/S3_process.py @@ -1,18 +1,25 @@ import boto3 class MinioS3Client: - def __init__(self, endpoint, access_key, secret_key, bucket_name): + def __init__(self, access_key, secret_key, bucket_name, endpoint=""): self.endpoint = endpoint self.access_key = access_key self.secret_key = secret_key self.bucket_name = bucket_name try: - self.s3_client = boto3.client( - 's3', - endpoint_url=endpoint, - aws_access_key_id=access_key, - aws_secret_access_key=secret_key - ) + if len(endpoint) > 0: + self.s3_client = boto3.client( + 's3', + endpoint_url=endpoint, + aws_access_key_id=access_key, + aws_secret_access_key=secret_key + ) + else: + self.s3_client = boto3.client( + 's3', + aws_access_key_id=access_key, + aws_secret_access_key=secret_key + ) except Exception as e: print(f"[WARM] Unable to create an s3 client, {e}") self.s3_client = None @@ -46,17 +53,17 @@ class MinioS3Client: print(f"Error downloading file from S3: {str(e)}") if __name__=="__main__": - FILE = "/app/media/users/2/subscriptions/34/requests/invoice/Ctel33aed8ecc189447a81c23a86c5262403/temp_Ctel33aed8ecc189447a81c23a86c5262403.jpg" + FILE = "/app/media/users/1/subscriptions/33/requests/sbt_invoice/SAP00c6c229c2954e498b119968a318d366/temp_SAP00c6c229c2954e498b119968a318d366.jpg" s3_client = MinioS3Client( - endpoint='http://minio:9884', - access_key='TannedCung', - secret_key='TannedCung', - bucket_name='ocr-data' + # endpoint='http://minio:9884', + access_key='AKIA3AFPFVWZD77UACHE', + secret_key='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', + bucket_name='ocr-sds' ) # Read the content of the JPG image file - with open(FILE, 'rb') as file: - image_content = file.read() + # with open(FILE, 'rb') as file: + # image_content = file.read() # Update the object in S3 with the new content # res = s3_client.update_object('invoice/viettinbank/image.jpg', image_content)