130 lines
3.3 KiB
Python
130 lines
3.3 KiB
Python
import os
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import json
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import glob
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from tqdm import tqdm
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from pdf2image import convert_from_path
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from dicttoxml import dicttoxml
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def create_dir(save_dir=''):
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if not os.path.exists(save_dir):
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os.makedirs(save_dir, exist_ok=True)
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# else:
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# print("DIR already existed.")
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# print('Save dir : {}'.format(save_dir))
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def convert_pdf2img(pdf_dir, save_dir):
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pdf_files = glob.glob(f'{pdf_dir}/*.pdf')
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print('No. pdf files:', len(pdf_files))
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print(pdf_files)
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for file in tqdm(pdf_files):
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pdf2img(file, save_dir, n_pages=-1, return_fname=False)
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# pages = convert_from_path(file, 500)
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# for i, page in enumerate(pages):
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# page.save(os.path.join(save_dir, os.path.basename(file).replace('.pdf', f'_{i}.jpg')), 'JPEG')
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print('Done!!!')
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def pdf2img(pdf_path, save_dir, n_pages=-1, return_fname=False):
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file_names = []
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pages = convert_from_path(pdf_path)
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if n_pages != -1:
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pages = pages[:n_pages]
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for i, page in enumerate(pages):
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_save_path = os.path.join(save_dir, os.path.basename(pdf_path).replace('.pdf', f'_{i}.jpg'))
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page.save(_save_path, 'JPEG')
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file_names.append(_save_path)
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if return_fname:
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return file_names
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def xyxy2xywh(bbox):
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return [
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float(bbox[0]),
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float(bbox[1]),
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float(bbox[2]) - float(bbox[0]),
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float(bbox[3]) - float(bbox[1]),
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]
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def write_to_json(file_path, content):
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with open(file_path, mode='w', encoding='utf8') as f:
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json.dump(content, f, ensure_ascii=False)
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def read_json(file_path):
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with open(file_path, 'r') as f:
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return json.load(f)
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def read_xml(file_path):
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with open(file_path, 'r') as xml_file:
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return xml_file.read()
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def write_to_xml(file_path, content):
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with open(file_path, mode="w", encoding='utf8') as f:
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f.write(content)
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def write_to_xml_from_dict(file_path, content):
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xml = dicttoxml(content)
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xml = content
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xml_decode = xml.decode()
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with open(file_path, mode="w") as f:
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f.write(xml_decode)
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def read_txt(ocr_path):
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with open(ocr_path, "r") as f:
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lines = f.read().splitlines()
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return lines
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def load_ocr_result(ocr_path):
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with open(ocr_path, 'r') as f:
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lines = f.read().splitlines()
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preds = []
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for line in lines:
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preds.append(line.split('\t'))
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return preds
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def post_process_basic_ocr(lwords: list) -> list:
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pp_lwords = []
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for word in lwords:
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pp_lwords.append(word.replace("✪", " "))
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return pp_lwords
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def read_ocr_result_from_txt(file_path: str):
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'''
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return list of bounding boxes, list of words
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'''
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with open(file_path, 'r') as f:
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lines = f.read().splitlines()
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boxes, words = [], []
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for line in lines:
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if line == "":
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continue
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word_info = line.split("\t")
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if len(word_info) == 6:
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x1, y1, x2, y2, text, _ = word_info
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elif len(word_info) == 5:
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x1, y1, x2, y2, text = word_info
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x1, y1, x2, y2 = int(float(x1)), int(float(y1)), int(float(x2)), int(float(y2))
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if text and text != " ":
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words.append(text)
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boxes.append((x1, y1, x2, y2))
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return boxes, words
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