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