Transform affecting my Images

[bolt25 (Dharmik Bhatt)]

Im working on fringe pattern denoising and in that I have fringe patterns like:-

but when I apply the transform of ToTensor()

and then print the image, it turns so bad that my model isn’t learning anything:-

any suggestions on what can I do?
Because I dont think that its possible train my model on the images without converting them into tensors?

[Nikronic (Nikan Doosti)]

Hi,

Can you share one of the images in your dataset and also the method to visualize transformed images?

It would be great also if you could combine your questions into single topic as they are highly correlated.

Normalisation necessary for image reconstruction?

I have a dataset which needs to be denoised. When I was looking at the images of my dataloader which are fed into network I saw that the images from dataloader and images in my dataset are very different. Now the only transformation I used are resize and ToTensor(). Is it because of ToTensor()? Is it normalizing my image and is that causing my model to learn nothing? Can I stop this?

Bests

[bolt25 (Dharmik Bhatt)]

The above image is from dataset and the below image is after transform in the image mention in the above question.

[Nikronic (Nikan Doosti)]

I meant the original image file so I can test a few things.
Also, I think the way you visualize your data is not correct, that is why I am asking the method of visualization for your transformed data.

[bolt25 (Dharmik Bhatt)]

def dispImageFromModel(tensor):
    img = tensor.cpu().detach().numpy()
    img = img.reshape((512,512))
    img, cb, cr = Image.fromarray(img, 'YCbCr').split()
    return img

[bolt25 (Dharmik Bhatt)]

For anyone who is looking for answers!
Follow the below link!

Normalisation necessary for image reconstruction?

Thank you so so much!! This worked like a charm!!

Thank you! @Nikronic