2018-08-17 17:46 GMT+03:00 Pedro Arthur <bygran...@gmail.com>: > Hi, > > You did not provided any pre trained model files, so anyone trying to > test it has to perform the whole training! > I'm attaching the models I generated, if anyone is interested in testing > it. > > When applying the filter with tf backend there are artifacts in the > borders, for both srcnn and espcn (out_[srcnn|espcn]_tf.jpg). > It seems that a few lines in the top row of the image are repeated for > espcn using native backend (out_srcnn_nt.jpg). >
I guess, it is because I didn't add any padding to the image and tf fills borders with 0 for 'SAME' padding in convolutions. I'll add required padding size calculation and insert padding operation to the graph. > The model/model_filename options are not coherent, the model type > should be defined in the file anyway therefore there is no need for > both options. > It is also buggy, if you specify the model_filename but not the model > type it will default to srcnn even if the model file is for espcn, no > error is generated and the output ofc is buggy. > I think, I can remove model type and check if model changes input size. I think all my switches for model type actually depend on this condition. If I remove conversions inside the filter and make it to work only for one plane, it basically will become a filter that executes neural network for one channel input. But there is a problem with float format - it brokes fate on some 32 bit hosts, as James stated, and I need first to fix this issue, or, otherwise, revert to doing conversions in the filter. > I personally would prefer to use only model=file as it is shorter than > model_filename=file. _______________________________________________ ffmpeg-devel mailing list ffmpeg-devel@ffmpeg.org http://ffmpeg.org/mailman/listinfo/ffmpeg-devel
