lavc/aarch64: Fix addp overflow in ff_pred16x16_plane_neon_10
[ffmpeg.git] / tools / python / convert.py
1 # Copyright (c) 2019 Guo Yejun
2 #
3 # This file is part of FFmpeg.
4 #
5 # FFmpeg is free software; you can redistribute it and/or
6 # modify it under the terms of the GNU Lesser General Public
7 # License as published by the Free Software Foundation; either
8 # version 2.1 of the License, or (at your option) any later version.
9 #
10 # FFmpeg is distributed in the hope that it will be useful,
11 # but WITHOUT ANY WARRANTY; without even the implied warranty of
12 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
13 # Lesser General Public License for more details.
14 #
15 # You should have received a copy of the GNU Lesser General Public
16 # License along with FFmpeg; if not, write to the Free Software
17 # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA
18 # ==============================================================================
19
20 # verified with Python 3.5.2 on Ubuntu 16.04
21 import argparse
22 import os
23 from convert_from_tensorflow import *
24
25 def get_arguments():
26 parser = argparse.ArgumentParser(description='generate native mode model with weights from deep learning model')
27 parser.add_argument('--outdir', type=str, default='./', help='where to put generated files')
28 parser.add_argument('--infmt', type=str, default='tensorflow', help='format of the deep learning model')
29 parser.add_argument('infile', help='path to the deep learning model with weights')
30 parser.add_argument('--dump4tb', type=str, default='no', help='dump file for visualization in tensorboard')
31
32 return parser.parse_args()
33
34 def main():
35 args = get_arguments()
36
37 if not os.path.isfile(args.infile):
38 print('the specified input file %s does not exist' % args.infile)
39 exit(1)
40
41 if not os.path.exists(args.outdir):
42 print('create output directory %s' % args.outdir)
43 os.mkdir(args.outdir)
44
45 basefile = os.path.split(args.infile)[1]
46 basefile = os.path.splitext(basefile)[0]
47 outfile = os.path.join(args.outdir, basefile) + '.model'
48 dump4tb = False
49 if args.dump4tb.lower() in ('yes', 'true', 't', 'y', '1'):
50 dump4tb = True
51
52 if args.infmt == 'tensorflow':
53 convert_from_tensorflow(args.infile, outfile, dump4tb)
54
55 if __name__ == '__main__':
56 main()