Applying a Conv2d filter to an image tensor

vision
1

Hey guys,

I’m new to Python, and trying to do some manipulations with filters in Pytorch.

I’m struggling re how to apply a Conv2d. I’ve got the following code which creates a 3x3 moving avg filter

resized_image4D = np.reshape(image_noisy, (1, 1, image_noisy.shape[0], image_noisy.shape[1]))
t = torch.from_numpy(resized_image4D)

conv = torch.nn.Conv2d(in_channels=1, out_channels=1, kernel_size=3, padding=1, bias=False)
conv.weight = torch.nn.Parameter(torch.ones((1,1,3, 3))/9.0)

Normally in np I’d just call convolve2x(image,kernel), but I’ve not been able to figure out what the PyTorch equivalent is after days of searching.

Apologies if a dumb question. Any pointers in the right direction would be greatly appreciated.

Thank you very much
Erik

2

You could use torch.nn.functional.conv2d then you can pass the input image right into the conv2d layer. Here is the documentation.

3

Got it, managed to get it to work. Thank you very much!!!