I have a transforms class which only does:
if transform is None:
transform = transforms.Compose([
transforms.Resize((256, 256)),
transforms.ToTensor()
])
root = os.path.join(PROJECT_ROOT_DIR, "data")
super(AttributesDataset, self).__init__()
self.data = torchvision.datasets.CelebA(
root=root,
split=split,
target_type='attr',
download=True,
transform=transform
)
I want to visualize some of the outputs coming from the model. As such, I created a simple method which does:-
for img, label in dataloader:
img.squeeze_(0)
# permute the channels. cv2 expects image in format (h, w, c)
unscaled_img = img.permute(1, 2, 0)
# move images to cpu and convert to numpy as required by cv2 library
unscaled_img = torch.round(unscaled_img * 255)
unscaled_img = unscaled_img.to(torch.uint8)
# unscaled_img = np.rint(unscaled_img * 255).astype(np.uint8)
unscaled_img = cv2.cvtColor(unscaled_img, cv2.COLOR_RGB2BGR)
cv2.imshow(unscaled_img.numpy())
However, all the images that are created have an unusually blue shade. For instance,
Can someone please tell me what exactly am I doing wrong here? Your help would be highly appreciated