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Merge branch 'main' of https://code.sdsdev.co.kr/SDSRV-IDP/sbt-idp into vietanh99-update-xlsx

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daovietanh99 2024-02-19 09:22:49 +07:00
commit 6cf90f1d19
11 changed files with 163 additions and 98 deletions
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1
.gitignore vendored
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@ -38,3 +38,4 @@ cope2n-ai-fi/Dockerfile_old_work
/feedback/
cope2n-api/public/SBT_report_20240122.csv
Jan.csv
*.csv

2
cope2n-ai-fi/modules/sdsvkvu

@ -1 +1 @@
Subproject commit 6907ea0183b141e3b4f3c21758c9123f1e9b2a27
Subproject commit b6d4fab46f7f8689dd6b050cfbff2faa6a6f3fec

4
cope2n-api/fwd_api/api/accuracy_view.py
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@ -433,10 +433,10 @@ class AccuracyViewSet(viewsets.ViewSet):
@action(detail=False, url_path="overview", methods=["GET"])
def overview(self, request):
if request.method == 'GET':
subsidiary = request.GET.get('subsidiary', "ALL")
_subsidiary = request.GET.get('subsidiary', "ALL")
duration = request.GET.get('duration', "")
subsidiary = map_subsidiary_long_to_short(subsidiary)
subsidiary = map_subsidiary_long_to_short(_subsidiary)
# Retrive data from Redis
key = f"{subsidiary}_{duration}"

18
cope2n-api/fwd_api/migrations/0181_reportfile_subsidiary.py Normal file
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@ -0,0 +1,18 @@
# Generated by Django 4.1.3 on 2024-02-15 09:12
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('fwd_api', '0180_alter_reportfile_time_cost'),
]
operations = [
migrations.AddField(
model_name='reportfile',
name='subsidiary',
field=models.CharField(default='', max_length=200, null=True),
),
]

1
cope2n-api/fwd_api/models/ReportFile.py
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@ -9,6 +9,7 @@ class ReportFile(models.Model):
id = models.AutoField(primary_key=True)
correspond_request_id = models.CharField(max_length=200, default="")
correspond_redemption_id = models.CharField(max_length=200, default="")
subsidiary = models.CharField(default="", null=True, max_length=200)
created_at = models.DateTimeField(default=timezone.now, db_index=True)
updated_at = models.DateTimeField(auto_now=True)
report = models.ForeignKey(Report, related_name="files", on_delete=models.CASCADE)

72
cope2n-api/fwd_api/utils/accuracy.py
View File

@ -9,6 +9,7 @@ import uuid
from fwd_api.models import SubscriptionRequest, SubscriptionRequestFile, ReportFile
from ..celery_worker.client_connector import c_connector
from ..utils.file import dict2xlsx, save_workbook_file, save_report_to_S3
from ..utils.subsidiary import map_subsidiary_short_to_long
from django.db.models import Q
from django.utils import timezone
import redis
@ -29,6 +30,8 @@ class ReportAccumulateByRequest:
self.total_format = {
'subs': "+",
'extraction_date': "Subtotal ()",
'num_imei': 0,
'num_invoice': 0,
'total_images': 0,
'images_quality': {
'successful': 0,
@ -49,6 +52,7 @@ class ReportAccumulateByRequest:
'usage': {
'imei':0,
'invoice': 0,
'total_images': 0,
'request': 0
},
'feedback_accuracy': {
@ -90,6 +94,7 @@ class ReportAccumulateByRequest:
'usage': {
'imei': 0,
'invoice': 0,
'total_images': 0,
'request': 0
},
'feedback_accuracy': {
@ -113,7 +118,13 @@ class ReportAccumulateByRequest:
total["total_images"] += 1
total["images_quality"]["successful"] += 1 if not report_file.is_bad_image else 0
total["images_quality"]["bad"] += 1 if report_file.is_bad_image else 0
# total["report_files"].append(report_file)
doc_type = "imei"
if report_file.doc_type in ["imei", "invoice", "all"]:
doc_type = report_file.doc_type
else:
print(f"[WARM]: Weird doc type {report_file.doc_type} if request id: {report_file.correspond_request_id}")
total["num_imei"] += 1 if doc_type == "imei" else 0
total["num_invoice"] += 1 if doc_type == "invoice" else 0
if sum([len(report_file.reviewed_accuracy[x]) for x in report_file.reviewed_accuracy.keys() if "_count" not in x]) > 0 :
total["average_accuracy_rate"]["imei"].add(report_file.reviewed_accuracy.get("imei_number", []))
@ -136,8 +147,14 @@ class ReportAccumulateByRequest:
total["average_processing_time"][report_file.doc_type] = IterAvg()
total["average_processing_time"][report_file.doc_type].add_avg(report_file.time_cost, 1) if report_file.time_cost else 0
total["usage"]["imei"] += 1 if report_file.doc_type == "imei" else 0
total["usage"]["invoice"] += 1 if report_file.doc_type == "invoice" else 0
doc_type = "imei"
if report_file.doc_type in ["imei", "invoice", "all"]:
doc_type = report_file.doc_type
else:
print(f"[WARM]: Weird doc type {report_file.doc_type} if request id: {report_file.correspond_request_id}")
total["usage"]["imei"] += 1 if doc_type == "imei" else 0
total["usage"]["invoice"] += 1 if doc_type == "invoice" else 0
total["usage"]["total_images"] += 1
return total
@ -146,8 +163,13 @@ class ReportAccumulateByRequest:
day_data["total_images"] += 1
day_data["images_quality"]["successful"] += 1 if not report_file.is_bad_image else 0
day_data["images_quality"]["bad"] += 1 if report_file.is_bad_image else 0
day_data["num_imei"] += 1 if report_file.doc_type == "imei" else 0
day_data["num_invoice"] += 1 if report_file.doc_type == "invoice" else 0
doc_type = "imei"
if report_file.doc_type in ["imei", "invoice", "all"]:
doc_type = report_file.doc_type
else:
print(f"[WARM]: Weird doc type {report_file.doc_type} if request id: {report_file.correspond_request_id}")
day_data["num_imei"] += 1 if doc_type == "imei" else 0
day_data["num_invoice"] += 1 if doc_type == "invoice" else 0
day_data["report_files"].append(report_file)
if sum([len(report_file.reviewed_accuracy[x]) for x in report_file.reviewed_accuracy.keys() if "_count" not in x]) > 0 :
@ -186,6 +208,7 @@ class ReportAccumulateByRequest:
self.data[this_month][1][this_day]["usage"]["imei"] = usage.get("imei", 0)
self.data[this_month][1][this_day]["usage"]["invoice"] = usage.get("invoice", 0)
self.data[this_month][1][this_day]["usage"]["request"] = usage.get("request", 0)
self.data[this_month][1][this_day]["usage"]["total_images"] = usage.get("imei", 0) + usage.get("invoice", 0)
self.data[this_month][1][this_day]['num_request'] += 1
self.data[this_month][0]['num_request'] += 1
@ -213,6 +236,7 @@ class ReportAccumulateByRequest:
day_keys = list(report_data[month][1].keys())
day_keys.sort(reverse = True)
for day in day_keys:
report_data[month][1][day]['subs'] = map_subsidiary_short_to_long(report_data[month][1][day]['subs'])
fine_data.append(report_data[month][1][day])
# save daily reports
report_id = root_report_id + "_" + day
@ -293,6 +317,7 @@ class ReportAccumulateByRequest:
_data[month][0]["usage"]["imei"] = num_transaction_imei
_data[month][0]["usage"]["invoice"] = num_transaction_invoice
_data[month][0]["usage"]["total_images"] = num_transaction_invoice + num_transaction_imei
_data[month][0]["average_accuracy_rate"]["imei"] = _data[month][0]["average_accuracy_rate"]["imei"]()
_data[month][0]["average_accuracy_rate"]["purchase_date"] = _data[month][0]["average_accuracy_rate"]["purchase_date"]()
_data[month][0]["average_accuracy_rate"]["retailer_name"] = _data[month][0]["average_accuracy_rate"]["retailer_name"]()
@ -311,7 +336,6 @@ class ReportAccumulateByRequest:
return _data
class MonthReportAccumulate:
def __init__(self):
self.month = None
@ -513,6 +537,7 @@ def extract_report_detail_list(report_detail_list, lower=False, in_percent=True)
data = []
for report_file in report_detail_list:
data.append({
"Subs": report_file.subsidiary,
"Request ID": report_file.correspond_request_id,
"Redemption Number": report_file.correspond_redemption_id,
"Image type": report_file.doc_type,
@ -600,6 +625,9 @@ def align_fine_result(ready_predict, fine_result):
# print(f"[DEBUG]: fine_result: {fine_result}")
# print(f"[DEBUG]: ready_predict: {ready_predict}")
if fine_result:
if isinstance(ready_predict["purchase_date"], str):
ready_predict["purchase_date"] = [ready_predict["purchase_date"]]
# ready_predict.save()
if fine_result["purchase_date"] and len(ready_predict["purchase_date"]) == 0:
ready_predict["purchase_date"] = [None]
if fine_result["retailername"] and not ready_predict["retailername"]:
@ -616,6 +644,7 @@ def update_temp_accuracy(accuracy, acc, keys):
for key in keys:
accuracy[key].add(acc[key])
return accuracy
def calculate_accuracy(key_name, inference, target):
"""_summary_
@ -661,7 +690,10 @@ def calculate_avg_accuracy(acc, type, keys=[]):
acc_list = []
# print(f"[DEBUG]: type: {type} - acc: {acc}")
for key in keys:
acc_list += acc.get(type, {}).get(key, [])
this_acc = acc.get(type, {}).get(key, [])
if len(this_acc) > 0:
this_acc = [max(this_acc)]
acc_list += this_acc
acc_list = [x for x in acc_list if x is not None]
return sum(acc_list)/len(acc_list) if len(acc_list) > 0 else None
@ -732,6 +764,12 @@ def calculate_and_save_subcription_file(report, request):
return request_att
def acc_maximize_list_values(acc):
for k in acc.keys():
if isinstance(acc[k], list) and len(acc[k]) > 0:
acc[k] = [max(acc[k])]
return acc
def calculate_a_request(report, request):
request_att = {"acc": {"feedback": {"imei_number": [],
"purchase_date": [],
@ -753,19 +791,30 @@ def calculate_a_request(report, request):
status, att = calculate_subcription_file(image)
if status != 200:
continue
image.feedback_accuracy = att["acc"]["feedback"]
image.reviewed_accuracy = att["acc"]["reviewed"]
image.feedback_accuracy = att["acc"]["feedback"] # dict {key: [values]}
image.reviewed_accuracy = att["acc"]["reviewed"] # dict {key: [values]}
image.is_bad_image_quality = att["is_bad_image"]
if not image.doc_type:
# try to revert doc type from filename
_doc_type = image.file_name.split("_")[1]
if _doc_type in ["imei", "invoice"]:
image.doc_type = _doc_type
image.save()
_sub = "NA"
if request.redemption_id:
_sub = map_subsidiary_short_to_long(request.redemption_id[:2])
else:
print(f"[WARM]: empty redemption_id, check request: {request.request_id}")
new_report_file = ReportFile(report=report,
subsidiary=_sub,
correspond_request_id=request.request_id,
correspond_redemption_id=request.redemption_id,
doc_type=image.doc_type,
predict_result=image.predict_result,
feedback_result=image.feedback_result,
reviewed_result=image.reviewed_result,
feedback_accuracy=att["acc"]["feedback"],
reviewed_accuracy=att["acc"]["reviewed"],
feedback_accuracy=acc_maximize_list_values(att["acc"]["feedback"]),
reviewed_accuracy=acc_maximize_list_values(att["acc"]["reviewed"]),
acc=att["avg_acc"],
is_bad_image=att["is_bad_image"],
time_cost=image.processing_time,
@ -798,7 +847,6 @@ def calculate_a_request(report, request):
return request_att, report_files
def calculate_subcription_file(subcription_request_file):
att = {"acc": {"feedback": {},
"reviewed": {}},

4
cope2n-api/scripts/re_feedback.py
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@ -17,8 +17,8 @@ login_token = None
# Define the login credentials
login_credentials = {
'username': 'sbt',
'password': '7Eg4AbWIXDnufgn'
# 'password': 'abc'
# 'password': '7Eg4AbWIXDnufgn'
'password': 'abc'
}
# Define the command to call the update API

6
cope2n-api/scripts/script.py
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@ -5,7 +5,7 @@ from datetime import datetime
# Get the proxy URL from the environment variable
interval = 60*60*1 # 1 minute
update_cost = 60*2
update_cost = int(60*1.5)
proxy_url = os.getenv('PROXY', "localhost")
# Define the login API URL
@ -15,8 +15,8 @@ login_token = None
# Define the login credentials
login_credentials = {
'username': 'sbt',
# 'password': '7Eg4AbWIXDnufgn'
'password': 'abc'
'password': '7Eg4AbWIXDnufgn'
# 'password': 'abc'
}
# Define the command to call the update API

2
deploy_images.sh
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@ -7,7 +7,7 @@ tag=$1
echo "[INFO] Tag received from Python: $tag"
# echo "[INFO] Updating everything the remote..."
# git submodule update --recursive --remote
git submodule update --recursive --remote
echo "[INFO] Pushing AI image with tag: $tag..."
docker compose -f docker-compose-dev.yml build cope2n-fi-sbt

16
docker-compose-dev.yml
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@ -84,12 +84,12 @@ services:
depends_on:
db-sbt:
condition: service_started
# command: sh -c "chmod -R 777 /app; sleep 5; python manage.py collectstatic --no-input &&
# python manage.py makemigrations &&
# python manage.py migrate &&
# python manage.py compilemessages &&
# gunicorn fwd.asgi:application -k uvicorn.workers.UvicornWorker --timeout 300 -b 0.0.0.0:9000" # pre-makemigrations on prod
command: bash -c "tail -f > /dev/null"
command: sh -c "chmod -R 777 /app; sleep 5; python manage.py collectstatic --no-input &&
python manage.py makemigrations &&
python manage.py migrate &&
python manage.py compilemessages &&
gunicorn fwd.asgi:application -k uvicorn.workers.UvicornWorker --timeout 300 -b 0.0.0.0:9000" # pre-makemigrations on prod
# command: bash -c "tail -f > /dev/null"
minio:
image: minio/minio
@ -174,8 +174,8 @@ services:
- ./cope2n-api:/app
working_dir: /app
command: sh -c "celery -A fwd_api.celery_worker.worker worker -l INFO -c 5"
# command: bash -c "tail -f > /dev/null"
# command: sh -c "celery -A fwd_api.celery_worker.worker worker -l INFO -c 5"
command: bash -c "tail -f > /dev/null"
# Back-end persistent
db-sbt:

127
scripts/crawl_database_by_time_with_accuracy_contrain.py
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@ -10,23 +10,34 @@ from pytz import timezone
from dotenv import load_dotenv
load_dotenv("../.env_prod")
# load_dotenv(".env_prod")
# load_dotenv("../.env")
OUTPUT_NAME = "0131-0206"
START_DATE = datetime(2024, 1, 31, tzinfo=timezone('Asia/Singapore'))
END_DATE = datetime(2024, 2, 6, tzinfo=timezone('Asia/Singapore'))
OUTPUT_NAME = "0116-0216"
START_DATE = datetime(2024, 1, 16, tzinfo=timezone('Asia/Singapore'))
END_DATE = datetime(2024, 2, 16, tzinfo=timezone('Asia/Singapore'))
BAD_THRESHOLD = 0.75
# ("requestId", "redemptionNumber", "fileName", "userSubmitResults", "OCRResults", "revisedResults_by_SDSRV", "accuracy")
REQUEST_ID_COL = 3
REQUEST_NUMBER_COL = 6
REQUEST_REDEMPTION_COL = 27
FILE_NAME_COL = 1
OCR_RESULT_COL = 16
FEEDBACK_RESULT_COL = 15
REVIEWED_RESULT_COL = 17
REVIEW_ACC_COL = 19
FEEDBACK_ACC_COL = 18
REQUEST_ID_COL = 6
# Database connection details
db_host = os.environ.get('DB_HOST', "")
# db_host = "42.96.42.13"
db_name = os.environ.get('DB_SCHEMA', "")
db_user = os.environ.get('DB_USER', "")
db_password = os.environ.get('DB_PASSWORD', "")
# db_host = "sbt.cxetpslawu4p.ap-southeast-1.rds.amazonaws.com"
# db_name = "sbt2"
# db_user = "sbt"
# db_password = "sbtCH240"
# S3 bucket details
s3_bucket_name = os.environ.get('S3_BUCKET_NAME', "")
@ -36,40 +47,6 @@ s3_folder_prefix = 'sbt_invoice'
access_key = os.environ.get('S3_ACCESS_KEY', "")
secret_key = os.environ.get('S3_SECRET_KEY', "")
class RequestAtt:
def __init__(self) -> None:
self.feedback_accuracy = []
self.reiviewed_accuracy = []
self.acc = 0
self.request_id = None
self.is_bad = False
self.data = []
def add_file(self, file):
self.data.append(file)
if file[REVIEW_ACC_COL]:
for key in file[REVIEW_ACC_COL].keys():
self.feedback_accuracy += file[REVIEW_ACC_COL][key]
if file[FEEDBACK_ACC_COL]:
for key in file[FEEDBACK_ACC_COL].keys():
self.feedback_accuracy += file[FEEDBACK_ACC_COL][key]
def is_bad_image(self):
fb = min(self.feedback_accuracy)/len(self.feedback_accuracy) if len(self.feedback_accuracy) else None
rv = min(self.reiviewed_accuracy)/len(self.reiviewed_accuracy) if len(self.reiviewed_accuracy) else None
if not fb and not rv:
self.is_bad = False
return False
elif fb and rv is None:
self.is_bad = fb < BAD_THRESHOLD
self.acc = fb
return fb < BAD_THRESHOLD
elif fb and rv:
self.is_bad = rv < BAD_THRESHOLD
self.acc = rv
return rv < BAD_THRESHOLD
return False
def get_request(cursor, request_in_id):
query = "SELECT * FROM fwd_api_subscriptionrequest WHERE id = %s"
cursor.execute(query, (request_in_id,))
@ -99,44 +76,62 @@ def main():
# Define the CSV file path
csv_file_path = f'{OUTPUT_NAME}.csv'
data_dict = {}
bad_image_list = [] # [("requestId", "redemptionNumber", "fileName", "userSubmitResults", "OCRResults", "revisedResults_by_SDSRV", "accuracy"), ...]
request_ids = [] # for crawling images
# Filter out requests request that has quality < 75%
for i, _d in enumerate(data):
if not data_dict.get(_d[REQUEST_ID_COL], None):
data_dict[_d[REQUEST_ID_COL]] = RequestAtt()
data_dict[_d[REQUEST_ID_COL]].request_id = _d[REQUEST_ID_COL]
data_dict[_d[REQUEST_ID_COL]].add_file(_d)
if _d[FEEDBACK_ACC_COL] and _d[FEEDBACK_RESULT_COL]:
acc_len = 0
for key in _d[FEEDBACK_ACC_COL].keys():
if key == "purchase_date":
continue
acc_len += len(_d[FEEDBACK_ACC_COL][key])
if len(_d[FEEDBACK_ACC_COL][key]):
if min(_d[FEEDBACK_ACC_COL][key]) < BAD_THRESHOLD:
parent_request = get_request(cursor, _d[REQUEST_NUMBER_COL])
requestId = parent_request[REQUEST_ID_COL]
redemptionNumber = parent_request[REQUEST_REDEMPTION_COL]
fileName = _d[FILE_NAME_COL]
userSubmitResults = str(_d[FEEDBACK_RESULT_COL][key]) if _d[FEEDBACK_RESULT_COL] else ""
OCRResults = str(_d[OCR_RESULT_COL][key]) if _d[OCR_RESULT_COL] else ""
revisedResults_by_SDSRV = str(_d[REVIEWED_RESULT_COL][key]) if _d[REVIEWED_RESULT_COL] else ""
accuracy = _d[FEEDBACK_ACC_COL][key]
bad_image_list.append((requestId, redemptionNumber, fileName, userSubmitResults, OCRResults, revisedResults_by_SDSRV, accuracy))
request_ids.append(requestId)
if acc_len == 0: # This is the request with acc < 0.75
for key in _d[FEEDBACK_ACC_COL].keys():
if key == "purchase_date":
continue
# if not
if str(_d[FEEDBACK_RESULT_COL][key]) == str(_d[OCR_RESULT_COL][key]):
continue
parent_request = get_request(cursor, _d[REQUEST_NUMBER_COL])
requestId = parent_request[REQUEST_ID_COL]
redemptionNumber = parent_request[REQUEST_REDEMPTION_COL]
fileName = _d[FILE_NAME_COL]
userSubmitResults = str(_d[FEEDBACK_RESULT_COL][key]) if _d[FEEDBACK_RESULT_COL] else ""
OCRResults = str(_d[OCR_RESULT_COL][key]) if _d[OCR_RESULT_COL] else ""
revisedResults_by_SDSRV = str(_d[REVIEWED_RESULT_COL][key]) if _d[REVIEWED_RESULT_COL] else ""
accuracy = "Unknown (avg request acc < 0.75 is excluded from the acc report)"
bad_image_list.append((requestId, redemptionNumber, fileName, userSubmitResults, OCRResults, revisedResults_by_SDSRV, accuracy))
request_ids.append(requestId)
bad_images = []
for k in data_dict.keys():
if data_dict[k].is_bad_image():
bad_images.append(data_dict[k])
request_ids = []
# Write the data to the CSV file
for bad_image in bad_images:
request = get_request(cursor, bad_image.request_id)
if request:
request_ids.append(request[3])
# for bad_image in bad_images:
# request = get_request(cursor, bad_image.request_id)
# if request:
# request_ids.append(request[3])
# ###################### Get bad requests ######################
placeholders = ','.join(['%s'] * len(request_ids))
# Execute the SELECT query with the filter
query = f"SELECT * FROM fwd_api_subscriptionrequest WHERE request_id IN ({placeholders})"
cursor.execute(query, request_ids)
# Fetch the filtered data
data = cursor.fetchall()
# Define the CSV file path
csv_file_path = f'{OUTPUT_NAME}.csv'
# Write the data to the CSV file
with open(csv_file_path, 'w', newline='') as csv_file:
writer = csv.writer(csv_file)
writer.writerow([desc[0] for desc in cursor.description]) # Write column headers
writer.writerows(data) # Write the filtered data rows
writer.writerow(["requestId", "redemptionNumber", "fileName", "userSubmitResults", "OCRResults", "revisedResults_by_SDSRV", "accuracy"]) # Write column headers
writer.writerows(bad_image_list) # Write the filtered data rows
# Close the cursor and database connection
cursor.close()
@ -149,6 +144,8 @@ def main():
aws_secret_access_key=secret_key
)
request_ids = list(set(request_ids))
for request_id in tqdm(request_ids):
folder_key = f"{s3_folder_prefix}/{request_id}/" # Assuming folder structure like: s3_bucket_name/s3_folder_prefix/request_id/
local_folder_path = f"{OUTPUT_NAME}/{request_id}/" # Path to the local folder to save the downloaded files