in ()
2 result_no_prior,
3 result_tv_prior,
----> 4 result_deep_prior], factor=8, nrow=2);
~\Downloads\deep-image-prior\utils\common_utils.py in plot_image_grid(images_np, nrow, factor, interpolation)
74 images_np = [x if (x.shape[0] == n_channels) else np.concatenate([x, x, x], axis=0) for x in images_np]
75
---> 76 grid = get_image_grid(images_np, nrow)
77
78 plt.figure(figsize=(len(images_np) + factor, 12 + factor))
~\Downloads\deep-image-prior\utils\common_utils.py in get_image_grid(images_np, nrow)
56 '''Creates a grid from a list of images by concatenating them.'''
57 images_torch = [torch.from_numpy(x) for x in images_np]
---> 58 torch_grid = torchvision.utils.make_grid(images_torch, nrow)
59
60 return torch_grid.numpy()
~\Anaconda3\lib\site-packages\torchvision\utils.py in make_grid(tensor, nrow, padding, normalize, range, scale_each, pad_value)
33 # if list of tensors, convert to a 4D mini-batch Tensor
34 if isinstance(tensor, list):
---> 35 tensor = torch.stack(tensor, dim=0)
36
37 if tensor.dim() == 2: # single image H x W
RuntimeError: Expected a Tensor of type torch.FloatTensor but found a type torch.DoubleTensor for sequence element 1 in sequence argument at position #1 'tensors'
do you met similar problem?
if you know?I would appreciate your help.
Thanks a lot
plot_image_grid([imgs['HR_np'], result_no_prior, result_tv_prior, result_deep_prior], factor=8, nrow=2);
RuntimeError Traceback (most recent call last)