| |
|
|
| import json |
| import os |
|
|
| import datasets |
| import gdown |
|
|
| logger = datasets.logging.get_logger(__name__) |
|
|
|
|
| _CITATION = """\ |
| @article{park2019cord, |
| title={CORD: A Consolidated Receipt Dataset for Post-OCR Parsing}, |
| author={Park, Seunghyun and Shin, Seung and Lee, Bado and Lee, Junyeop and Surh, Jaeheung and Seo, Minjoon and Lee, Hwalsuk} |
| booktitle={Document Intelligence Workshop at Neural Information Processing Systems} |
| year={2019} |
| } |
| """ |
|
|
| _DESCRIPTION = """\ |
| https://github.com/clovaai/cord |
| """ |
| _URL = "https://drive.google.com/uc?id=1MqhTbcj-AHXOqYoeoh12aRUwIprzTJYI" |
|
|
|
|
| def gdrive_downloader(url, path): |
| gdown.download(url, path, quiet=False) |
|
|
|
|
| class CordConfig(datasets.BuilderConfig): |
| """BuilderConfig for CORD""" |
|
|
| def __init__(self, **kwargs): |
| """BuilderConfig for CORD. |
| Args: |
| **kwargs: keyword arguments forwarded to super. |
| """ |
| super(CordConfig, self).__init__(**kwargs) |
|
|
|
|
| class Cord(datasets.GeneratorBasedBuilder): |
| """Conll2003 dataset.""" |
|
|
| BUILDER_CONFIGS = [ |
| CordConfig(name="cord", version=datasets.Version( |
| "1.0.0"), description="FUNSD dataset"), |
| ] |
|
|
| def _info(self): |
| return datasets.DatasetInfo( |
| description=_DESCRIPTION, |
| features=datasets.Features( |
| { |
| "id": datasets.Value("string"), |
| "tokens": datasets.Sequence(datasets.Value("string")), |
| "bboxes": datasets.Sequence(datasets.Sequence(datasets.Value("int64"))), |
| "roi": datasets.Sequence(datasets.Sequence(datasets.Value("int64"))), |
| "ner_tags": datasets.Sequence( |
| datasets.features.ClassLabel( |
| names=['menu.cnt', |
| 'menu.discountprice', |
| 'menu.etc', |
| 'menu.itemsubtotal', |
| 'menu.nm', |
| 'menu.num', |
| 'menu.price', |
| 'menu.sub_cnt', |
| 'menu.sub_etc', |
| 'menu.sub_nm', |
| 'menu.sub_price', |
| 'menu.sub_unitprice', |
| 'menu.unitprice', |
| 'menu.vatyn', |
| 'sub_total.discount_price', |
| 'sub_total.etc', |
| 'sub_total.othersvc_price', |
| 'sub_total.service_price', |
| 'sub_total.subtotal_price', |
| 'sub_total.tax_price', |
| 'total.cashprice', |
| 'total.changeprice', |
| 'total.creditcardprice', |
| 'total.emoneyprice', |
| 'total.menuqty_cnt', |
| 'total.menutype_cnt', |
| 'total.total_etc', |
| 'total.total_price', |
| 'void_menu.nm', |
| 'void_menu.price'] |
| ) |
| ), |
| "image_path": datasets.Value("string"), |
| } |
| ), |
| supervised_keys=None, |
| homepage="https://github.com/clovaai/cord", |
| citation=_CITATION, |
| ) |
|
|
| def _split_generators(self, dl_manager: datasets.DownloadManager): |
| """Returns SplitGenerators.""" |
| url_or_urls = ['https://drive.google.com/uc?id=1MqhTbcj-AHXOqYoeoh12aRUwIprzTJYI', |
| 'https://drive.google.com/uc?id=1wYdp5nC9LnHQZ2FcmOoC0eClyWvcuARU'] |
|
|
| downloaded_file = dl_manager.extract( |
| dl_manager.download_custom(url_or_urls, gdrive_downloader)) |
|
|
| return [ |
| datasets.SplitGenerator( |
| name=datasets.Split.TRAIN, gen_kwargs={ |
| "filepaths": downloaded_file, "mode": "/CORD/train"} |
| ), |
| datasets.SplitGenerator( |
| name=datasets.Split.TEST, gen_kwargs={ |
| "filepaths": downloaded_file, "mode": "/CORD/test"} |
| ), |
| datasets.SplitGenerator( |
| name=datasets.Split.VALIDATION, gen_kwargs={ |
| "filepaths": downloaded_file, "mode": "/CORD/dev"} |
| ), |
| ] |
|
|
| def _generate_examples(self, filepaths, mode): |
| guid = -1 |
| for filepath in filepaths: |
| filepath_folder = filepath + mode |
| logger.info("⏳ Generating examples from = %s", filepath_folder) |
| ann_dir = os.path.join(filepath_folder, "json") |
| if not os.path.exists(ann_dir): |
| continue |
| img_dir = os.path.join(filepath_folder, "image") |
| for file in sorted(os.listdir(ann_dir)): |
| guid +=1 |
| tokens = [] |
| bboxes = [] |
| ner_tags = [] |
|
|
| file_path = os.path.join(ann_dir, file) |
| with open(file_path, "r", encoding="utf8") as f: |
| data = json.load(f) |
|
|
| image_path = os.path.join(img_dir, file) |
| image_path = image_path.replace("json", "png") |
|
|
| if not os.path.exists(image_path): |
| other_dir_idx = int(not (filepaths.index(filepath)+2)%2) |
| image_path = image_path.replace( |
| filepath, filepaths[other_dir_idx]) |
|
|
| roi = data["roi"] |
| if roi: |
| top_left = [roi["x1"], roi["y1"]] |
| bottom_right = [roi["x3"], roi["y3"]] |
| bottom_left = [roi["x4"], roi["y4"]] |
| top_right = [roi["x2"], roi["y2"]] |
| roi = [top_left, top_right, bottom_right, bottom_left] |
| else: |
| roi = [] |
|
|
|
|
| for item in data["valid_line"]: |
| for word in item['words']: |
| |
| txt = word['text'] |
|
|
| |
| x1 = word['quad']['x1'] |
| y1 = word['quad']['y1'] |
| x3 = word['quad']['x3'] |
| y3 = word['quad']['y3'] |
|
|
| box = [x1, y1, x3, y3] |
|
|
| |
| |
| if len(txt) < 1: |
| continue |
|
|
| tokens.append(txt) |
| bboxes.append(box) |
| ner_tags.append(item['category']) |
|
|
| yield guid, {"id": str(guid), "tokens": tokens, "bboxes": bboxes, "ner_tags": ner_tags, "image_path": image_path, "roi":roi} |
|
|
