Resulting Images Size

[sadbhawnathakur]

Is it possible to set the final inpainted image size same as the input images?

I tried the same and got this error:

Using cpu.
Model model/model_places2.pth loaded.

Inpainting...

Input size: (500, 333)
Traceback (most recent call last):
File "test.py", line 263, in
tester.inpaint(args.output, args.img, args.mask, merge_result=args.merge)
File "test.py", line 221, in inpaint
self.process_batch(batch, output)
File "test.py", line 172, in process_batch
result, alpha, raw = self.model(imgs_miss, masks)
File "/home/sadbhawna/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 532, in call
result = self.forward(*input, **kwargs)
File "/home/sadbhawna/torch/DFNet/model.py", line 260, in forward
out = decode(out, out_en[-i-2])
File "/home/sadbhawna/anaconda3/lib/python3.7/site-packages/torch/nn/modules/module.py", line 532, in call
result = self.forward(*input, **kwargs)
File "/home/sadbhawna/torch/DFNet/model.py", line 147, in forward
out = torch.cat([out, concat], dim=1)
RuntimeError: invalid argument 0: Sizes of tensors must match except in dimension 1. Got 2 and 3 in dimension 3 at /opt/conda/conda-bld/pytorch_1574150980135/work/aten/src/TH/generic/THTensor.cpp:612

[hughplay]

Actually U-Net like networks do have this limitation. The height and width must be divided by 2^n (n depends on the times of downsample). Because images will be downsampled and then upsampled.

You could hack it by:

1. resize the input image to make the height and width satisfied the condition mentioned above
2. resize the output image back to the original size

Hope this will help you.