mmsegmentation/tools/imagenets_submit.py

59 lines
1.8 KiB
Python
Raw Normal View History

# Copyright (c) OpenMMLab. All rights reserved.
import argparse
import os
import shutil
def parse_args():
parser = argparse.ArgumentParser(description='Inference')
parser.add_argument(
'--imgfile_prefix',
type=str,
required=True,
help='The prefix of output image file')
parser.add_argument(
'--method',
default='example submission',
help='Method name in method description file(method.txt).')
parser.add_argument(
'--arch',
metavar='ARCH',
help='The model architecture in method description file(method.txt).')
parser.add_argument(
'--train_data',
default='null',
help='Training data in method description file(method.txt).')
parser.add_argument(
'--train_scheme',
default='null',
help='Training scheme in method description file(method.txt), '
'e.g., SSL, Sup, SSL+Sup.')
parser.add_argument(
'--link',
default='null',
help='Paper/project link in method description file(method.txt).')
parser.add_argument(
'--description',
default='null',
help='Method description in method description file(method.txt).')
args = parser.parse_args()
return args
if __name__ == '__main__':
args = parse_args()
method = 'Method name: {}\n'.format(args.method) + \
'Training data: {}\nTraining scheme: {}\n'.format(
args.train_data, args.train_scheme) + \
'Networks: {}\nPaper/Project link: {}\n'.format(
args.arch, args.link) + \
'Method description: {}'.format(args.description)
with open(os.path.join(args.imgfile_prefix, 'method.txt'), 'w') as f:
f.write(method)
# zip for submission
shutil.make_archive(
args.imgfile_prefix, 'zip', root_dir=args.imgfile_prefix)