diff options
| author | Jules Laplace <julescarbon@gmail.com> | 2018-06-25 15:30:59 +0200 |
|---|---|---|
| committer | Jules Laplace <julescarbon@gmail.com> | 2018-06-25 15:30:59 +0200 |
| commit | 284dc5fe46bdaaf78f0416bfc6a5067a868b9062 (patch) | |
| tree | 3459069cb90198a4e084c121a64ef9236fac4ba1 /run.py | |
| parent | 60ff067355997fc7dbd3e5309616ddd3812e2634 (diff) | |
go hey
Diffstat (limited to 'run.py')
| -rw-r--r-- | run.py | 10 |
1 files changed, 7 insertions, 3 deletions
@@ -49,7 +49,9 @@ if not os.path.exists('./renders'): moduleNetwork = Network(arguments_strModel).cuda() tensorOutput = torch.FloatTensor() -def process_tree(moduleNetwork, tensorInputFirst, tensorInputSecond, tensorOutput, steps): +def process_tree(moduleNetwork, a, b, tensorOutput, steps): + tensorInputFirst = torch.FloatTensor(a) + tensorInputSecond = torch.FloatTensor(b) process(moduleNetwork, tensorInputFirst, tensorInputSecond, tensorOutput) tensorMiddle = (numpy.rollaxis(tensorOutput.clamp(0.0, 1.0).numpy(), 0, 3)[:,:,::-1] * 255.0).astype(numpy.uint8) if steps < 2: @@ -76,12 +78,14 @@ if arguments_strVideo and arguments_strVideoOut: writer.close() else: # Process image - tensorInputFirst = torch.FloatTensor(numpy.rollaxis(numpy.asarray(PIL.Image.open(arguments_strFirst))[:,:,::-1], 2, 0).astype(numpy.float32) / 255.0) - tensorInputSecond = torch.FloatTensor(numpy.rollaxis(numpy.asarray(PIL.Image.open(arguments_strSecond))[:,:,::-1], 2, 0).astype(numpy.float32) / 255.0) if arguments_steps == 0: + tensorInputFirst = torch.FloatTensor(numpy.rollaxis(numpy.asarray(PIL.Image.open(arguments_strFirst))[:,:,::-1], 2, 0).astype(numpy.float32) / 255.0) + tensorInputSecond = torch.FloatTensor(numpy.rollaxis(numpy.asarray(PIL.Image.open(arguments_strSecond))[:,:,::-1], 2, 0).astype(numpy.float32) / 255.0) process(moduleNetwork, tensorInputFirst, tensorInputSecond, tensorOutput) PIL.Image.fromarray((numpy.rollaxis(tensorOutput.clamp(0.0, 1.0).numpy(), 0, 3)[:,:,::-1] * 255.0).astype(numpy.uint8)).save(arguments_strOut) else: + tensorInputFirst = numpy.rollaxis(numpy.asarray(PIL.Image.open(arguments_strFirst))[:,:,::-1], 2, 0).astype(numpy.float32) / 255.0 + tensorInputSecond = numpy.rollaxis(numpy.asarray(PIL.Image.open(arguments_strSecond))[:,:,::-1], 2, 0).astype(numpy.float32) / 255.0 tree = process_tree(moduleNetwork, tensorInputFirst, tensorInputSecond, tensorOutput, arguments_steps) writer = FFMPEG_VideoWriter('./renders/' + arguments_strVideoOut, (1024, 512), 25) writer.write_frame(tensorInputFirst) |