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prepare_data.py
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prepare_data.py
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# Copyright (c) 2020 Sarthak Mittal
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
import os
import glob
import argparse
import pdf2image
import simplejson
from tqdm import tqdm
from invoicenet import FIELDS, FIELD_TYPES
from invoicenet.common import util
def main():
ap = argparse.ArgumentParser()
ap.add_argument("--data_dir", type=str, required=True,
help="path to directory containing invoice document images")
ap.add_argument("--out_dir", type=str, default='processed_data/',
help="path to save prepared data")
ap.add_argument("--val_size", type=float, default=0.2,
help="validation split ration")
args = ap.parse_args()
os.makedirs(os.path.join(args.out_dir, 'train'), exist_ok=True)
os.makedirs(os.path.join(args.out_dir, 'val'), exist_ok=True)
filenames = [os.path.abspath(f) for f in glob.glob(args.data_dir + "**/*.pdf", recursive=True)]
idx = int(len(filenames) * args.val_size)
train_files = filenames[idx:]
val_files = filenames[:idx]
print("Total: {}".format(len(filenames)))
print("Training: {}".format(len(train_files)))
print("Validation: {}".format(len(val_files)))
for phase, filenames in [('train', train_files), ('val', val_files)]:
print("Preparing {} data...".format(phase))
for filename in tqdm(filenames):
try:
page = pdf2image.convert_from_path(filename)[0]
page.save(os.path.join(args.out_dir, phase, os.path.basename(filename)[:-3] + 'png'))
height = page.size[1]
width = page.size[0]
ngrams = util.create_ngrams(page)
for ngram in ngrams:
if "amount" in ngram["parses"]:
ngram["parses"]["amount"] = util.normalize(ngram["parses"]["amount"], key="amount")
if "date" in ngram["parses"]:
ngram["parses"]["date"] = util.normalize(ngram["parses"]["date"], key="date")
with open(filename[:-3] + 'json', 'r') as fp:
labels = simplejson.loads(fp.read())
fields = {}
for field in FIELDS:
if field in labels:
if FIELDS[field] == FIELD_TYPES["amount"]:
fields[field] = util.normalize(labels[field], key="amount")
elif FIELDS[field] == FIELD_TYPES["date"]:
fields[field] = util.normalize(labels[field], key="date")
else:
fields[field] = labels[field]
else:
fields[field] = ''
data = {
"fields": fields,
"nGrams": ngrams,
"height": height,
"width": width,
"filename": os.path.abspath(
os.path.join(args.out_dir, phase, os.path.basename(filename)[:-3] + 'png'))
}
with open(os.path.join(args.out_dir, phase, os.path.basename(filename)[:-3] + 'json'), 'w') as fp:
fp.write(simplejson.dumps(data, indent=2))
except Exception as exp:
print("Skipping {} : {}".format(filename, exp))
continue
if __name__ == '__main__':
main()