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