I try testing my images using the following command:
python3.5 test.py --dataroot /Desktop/to/data --name 20Jan --model test --netG unet_256 --direction AtoB --dataset_mode single --norm batch --preprocess scale_width_and_crop
and I receive the following problem:
Traceback (most recent call last):
File "test.py", line 56, in
for i, data in enumerate(dataset):
File "/Desktop/pytorch-CycleGAN-and-pix2pix-master/data/init.py", line 90, in iter
for i, data in enumerate(self.dataloader):
File "/.local/lib/python3.5/site-packages/torch/utils/data/dataloader.py", line 637, in next
return self._process_next_batch(batch)
File "/.local/lib/python3.5/site-packages/torch/utils/data/dataloader.py", line 658, in _process_next_batch
raise batch.exc_type(batch.exc_msg)
ValueError: Traceback (most recent call last):
File "/.local/lib/python3.5/site-packages/torch/utils/data/dataloader.py", line 138, in _worker_loop
samples = collate_fn([dataset[i] for i in batch_indices])
File "/.local/lib/python3.5/site-packages/torch/utils/data/dataloader.py", line 138, in
samples = collate_fn([dataset[i] for i in batch_indices])
File "/Desktop/pytorch-CycleGAN-and-pix2pix-master/data/single_dataset.py", line 35, in getitem
A = self.transform(A_img)
File "/.local/lib/python3.5/site-packages/torchvision/transforms/transforms.py", line 49, in call
img = t(img)
File "/.local/lib/python3.5/site-packages/torchvision/transforms/transforms.py", line 421, in call
i, j, h, w = self.get_params(img, self.size)
File "/.local/lib/python3.5/site-packages/torchvision/transforms/transforms.py", line 399, in get_params
i = random.randint(0, h - th)
File "/usr/lib/python3.5/random.py", line 218, in randint
return self.randrange(a, b+1)
File "/usr/lib/python3.5/random.py", line 196, in randrange
raise ValueError("empty range for randrange() (%d,%d, %d)" % (istart, istop, width))
ValueError: empty range for randrange() (0,-185, -185)
However, when i remove the --preprocess, using:
python3.5 test.py --dataroot /Desktop/to/data --name 20Jan --model test --netG unet_256 --direction AtoB --dataset_mode single --norm batch
It actually works. (Though it is necessary since I trained the model by scaling the width and cropping).
The error is caused by cropping when crop_size is larger than the height or width of the image. Maybe you height (after rescaling) is smaller than crop_size. This Q & A might be relevant. Training and test preprocess options do not have to be the same.
Hello everyone,
I try testing my images using the following command:
and I receive the following problem:
However, when i remove the --preprocess, using:
It actually works. (Though it is necessary since I trained the model by scaling the width and cropping).
Thanks in advance!