def main():
args = arg.preprocess_args()
data = helper.get_data(folder=args.folder, data_file=args.data)
print('data_loaded')
append(data, args)
for i in range(10):
append(data, args, str(i), '_')
def main():
args = arg.preprocess_args()
rand = random.randint(0, 9999999)
data, _ = helper.pre_processed_data(args, rand, dry=False)
# data = data.reshape(-1,48,48)
if args.mean:
label, _ = helper.pre_processed_label(args, rand, dry=False)
data = preprocess.mean_image(label, data)
elif args.split is not None or args.randomize:
label, _ = helper.pre_processed_label(args, rand, dry=False)
helper.write_data_to_file(
(args.folder or helper.FOLDER) + (args.name or 'processed_data') +
'_l' + helper.EXT,
label,
fmt='%d',
h='0')
# for i in range(4):
# for j in range(4):
helper.write_data_to_file(
(args.folder or helper.FOLDER) +
(args.name or 'processed_data') # + str(i) + str(j)
+ helper.EXT,
data,
# [k[i*12:(i*12)+12,j*12:(j*12)+12].flatten() for k in data],
h=', '.join(str(i) for i in range(len(data[0]))))
def main():
args = arg.preprocess_args()
rand = 0
data, _ = helper.pre_processed_data_all(args, rand, dry=False)
if args.mean:
rand = random.randint(0, 9999999)
label, _ = helper.pre_processed_label_all(args, rand, dry=False)
data = preprocess.mean_image(label, data)
helper.create_images_from_rows((args.name or 'img'), data)
def main():
args = arg.preprocess_args()
rand = random.randint(0, 9999999)
data, _ = helper.pre_processed_data_all(args, rand, dry=False)
if args.mean:
label, _ = helper.pre_processed_label_all(args, rand, dry=False)
data = preprocess.mean_image(label, data)
elif args.split is not None or args.randomize:
label, _ = helper.pre_processed_label(args, rand, dry=False)
helper.write_data_to_file(
(args.folder or helper.FOLDER) + (args.name or 'processed_data') +
'_l' + helper.EXT,
label,
fmt='%d',
h='0')
# for i in range(4):
# for j in range(4):
helper.write_data_to_file((args.folder or helper.FOLDER) +
(args.name or 'processed_data') + helper.EXT,
data,
h=', '.join(str(i) for i in range(len(data[0]))))