def load_file(path):
image = pdf2image.convert_from_path(path)[0]
height = image.size[1]
width = image.size[0]
ngrams = util.create_ngrams(image)
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")
fields = {field: '0' for field in FIELDS}
page = {
"fields": fields,
"nGrams": ngrams,
"height": height,
"width": width,
"filename": path
}
return {'image': image, 'page': page}
def process_file(filename, out_dir, phase):
try:
page = pdf2image.convert_from_path(filename)[0]
page.save(
os.path.join(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(out_dir, phase,
os.path.basename(filename)[:-3] + 'png'))
}
with open(
os.path.join(out_dir, phase,
os.path.basename(filename)[:-3] + 'json'),
'w') as fp:
fp.write(simplejson.dumps(data, indent=2))
return True
except Exception as exp:
print("Skipping {} : {}".format(filename, exp))
return False
def _prepare_data(self):
self._get_inputs()
if self.args["data_dir"] == '':
messagebox.showerror("Error", "No files were selected!")
return
if not os.path.exists(self.args["data_dir"]):
messagebox.showerror("Error", "No files were selected!")
return
self.progressbar["value"] = 0
self.progress_label.configure(text="Preparing Data:")
data_dir = os.path.join(self.args["prepared_data"], 'predict')
os.makedirs(data_dir, exist_ok=True)
filenames = [os.path.abspath(f) for f in glob.glob(data_dir + "**/*.json", recursive=True)]
filenames += [os.path.abspath(f) for f in glob.glob(data_dir + "**/*.png", recursive=True)]
for f in filenames:
os.remove(f)
filenames = []
if self.args["data_dir"] and os.path.exists(self.args["data_dir"]):
filenames = [os.path.abspath(f) for f in glob.glob(self.args["data_dir"] + "**/*.pdf", recursive=True)]
if self.args["data_file"] and os.path.exists(self.args["data_file"]):
filenames += [self.args["data_file"]]
self.logger.log("Total: {}".format(len(filenames)))
self.logger.log("Preparing data for extraction...")
total_samples = len(filenames)
sample_idx = 0
for filename in tqdm(filenames):
try:
page = pdf2image.convert_from_path(filename)[0]
page.save(os.path.join(data_dir, 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")
fields = {field: '0' for field in FIELDS}
data = {
"fields": fields,
"nGrams": ngrams,
"height": height,
"width": width,
"filename": os.path.abspath(os.path.join(data_dir, os.path.basename(filename)[:-3] + 'png'))
}
with open(os.path.join(data_dir, os.path.basename(filename)[:-3] + 'json'),
'w') as fp:
fp.write(simplejson.dumps(data, indent=2))
except Exception as exp:
self.logger.log("Skipping {} : {}".format(filename, exp))
sample_idx += 1
self.progress_label.configure(text="Preparing data [{}/{}]:".format(sample_idx, total_samples))
self.progressbar["value"] = (sample_idx / total_samples) * 100
self.progressbar.update()
self.progress_label.configure(text="Completed!")
self.progressbar["value"] = 100
self.progressbar.update()
self.logger.log("Prepared data stored in '{}'".format(data_dir))
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)]
filenames = [
os.path.abspath(item) for sublist in [
glob.glob(args.data_dir + ext, recursive=True)
for ext in ["**/*.pdf", "**/*.jpg", "**/*.png"]
] for item in sublist
]
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, dpi=500)[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:
if "png" in filename or "jpg" in filename:
import cv2
page = cv2.imread(filename)
cv2.imwrite(
os.path.join(args.out_dir, phase,
os.path.basename(filename)[:-3] + 'png'),
page)
height = page.shape[0]
width = page.shape[1]
ngrams = util.create_ngrams(page, height, width)
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))
def _prepare_data(self):
self._get_inputs()
if self.args["data_dir"] == '':
messagebox.showerror("Error", "Data folder does not exist!")
return
if not os.path.exists(self.args["data_dir"]):
messagebox.showerror("Error", "Data folder does not exist!")
return
self.progressbar["value"] = 0
self.progress_label.configure(text="Preparing Data:")
os.makedirs(os.path.join(self.args["prepared_data"], 'train'),
exist_ok=True)
os.makedirs(os.path.join(self.args["prepared_data"], 'val'),
exist_ok=True)
filenames = [
os.path.abspath(f)
for f in glob.glob(self.args["data_dir"] + "**/*.pdf",
recursive=True)
]
random.shuffle(filenames)
idx = int(len(filenames) * 0.2)
train_files = filenames[idx:]
val_files = filenames[:idx]
self.logger.log("Total: {}".format(len(filenames)))
self.logger.log("Training: {}".format(len(train_files)))
self.logger.log("Validation: {}".format(len(val_files)))
total_samples = len(filenames)
sample_idx = 0
for phase, filenames in [('train', train_files), ('val', val_files)]:
self.logger.log("Preparing {} data...".format(phase))
for filename in tqdm(filenames):
# try:
page = pdf2image.convert_from_path(filename)[0]
page.save(
os.path.join(self.args["prepared_data"], 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(self.args["prepared_data"], phase,
os.path.basename(filename)[:-3] + 'png'))
}
with open(
os.path.join(self.args["prepared_data"], phase,
os.path.basename(filename)[:-3] + 'json'),
'w') as fp:
fp.write(simplejson.dumps(data, indent=2))
# except Exception as exp:
# self.logger.log("Skipping {} : {}".format(filename, exp))
sample_idx += 1
self.progress_label.configure(
text="Preparing data [{}/{}]:".format(
sample_idx, total_samples))
self.progressbar["value"] = (sample_idx / total_samples) * 100
self.progressbar.update()
self.progress_label.configure(text="Completed!")
self.progressbar["value"] = 100
self.progressbar.update()
self.logger.log("Prepared data stored in '{}'".format(
self.args["prepared_data"]))
