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- # Copyright (c) 2019 Guo Yejun
- #
- # This file is part of FFmpeg.
- #
- # FFmpeg is free software; you can redistribute it and/or
- # modify it under the terms of the GNU Lesser General Public
- # License as published by the Free Software Foundation; either
- # version 2.1 of the License, or (at your option) any later version.
- #
- # FFmpeg is distributed in the hope that it will be useful,
- # but WITHOUT ANY WARRANTY; without even the implied warranty of
- # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
- # Lesser General Public License for more details.
- #
- # You should have received a copy of the GNU Lesser General Public
- # License along with FFmpeg; if not, write to the Free Software
- # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
- # ==============================================================================
- # verified with Python 3.5.2 on Ubuntu 16.04
- import argparse
- import os
- from convert_from_tensorflow import *
- def get_arguments():
- parser = argparse.ArgumentParser(description='generate native mode model with weights from deep learning model')
- parser.add_argument('--outdir', type=str, default='./', help='where to put generated files')
- parser.add_argument('--infmt', type=str, default='tensorflow', help='format of the deep learning model')
- parser.add_argument('infile', help='path to the deep learning model with weights')
- parser.add_argument('--dump4tb', type=str, default='no', help='dump file for visualization in tensorboard')
- return parser.parse_args()
- def main():
- args = get_arguments()
- if not os.path.isfile(args.infile):
- print('the specified input file %s does not exist' % args.infile)
- exit(1)
- if not os.path.exists(args.outdir):
- print('create output directory %s' % args.outdir)
- os.mkdir(args.outdir)
- basefile = os.path.split(args.infile)[1]
- basefile = os.path.splitext(basefile)[0]
- outfile = os.path.join(args.outdir, basefile) + '.model'
- dump4tb = False
- if args.dump4tb.lower() in ('yes', 'true', 't', 'y', '1'):
- dump4tb = True
- if args.infmt == 'tensorflow':
- convert_from_tensorflow(args.infile, outfile, dump4tb)
- if __name__ == '__main__':
- main()
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