57 lines
2.2 KiB
Python
57 lines
2.2 KiB
Python
|
# 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()
|