|
|
|
|
|
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} |
|
|
