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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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