# 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 16.04import argparseimport osfrom 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()
# 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()