Same error, solution didn't work: RuntimeError expected input... to have 28 channels, but got 27 channels instead

[dkoslicki]

I ran into the same error as #14 , and verified that self.nonblind_denoising was set to True here, but still receive the error:

line 585, in _conv_forward
    return F.conv3d(
RuntimeError: Given groups=1, weight of size [96, 28, 1, 3, 3], expected input[1, 27, 40, 128, 128] to have 28 channels, but got 27 channels instead

This is using the dataset VRT/testsets/REDS4/sharp_bicubic via the call python main_test_vrt.py --task 008_VRT_videodenoising_DAVIS --folder_lq testsets/REDS4/sharp_bicubic --tile 40 128 128 --tile_overlap 2 20 20. I ultimately want to run this on my own folder of PNGs from a video.

[JingyunLiang]

It's a bug. Try to add --sigma 1 for quick fix. It should output similar results as no added noise. We will fix it later.

Also note that we train it as a non-blind denoising model. You may need to try different sigmas (e.g., larger sigma if the video is heavily corrupted by Gaussian noise).

[dkoslicki]

I see; but unfortunately --sigma 1 did not fix the issue: I got the exact same error message.

[JingyunLiang]

I see. It's because you didn't specify --folder_gt, so it uses another dataloader. We did not provide an interface for lq-only-input in denoising.

[haikunzhang95]

It's a bug. Try to add --sigma 1 for quick fix. It should output similar results as no added noise. We will fix it later.

Also note that we train it as a non-blind denoising model. You may need to try different sigmas (e.g., larger sigma if the video is heavily corrupted by Gaussian noise).

Have you fixed the bug?