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Published 20 hours ago • verified publisher icon fingerk28

Metrics on RGB or Y?

Open jiaqixuac opened this issue 2 years ago • 2 comments

Hi,

Thank you for your nice work. I want to know how you calculate the metrics for reporting.

Here are some results using your code and your model weights.

  1. python inference.py --checkpoint student-setting1.pth xxx and save the restored images.
  2. Calculate psnr and ssim using a) RGB: torchPSNR(pred_image, gt_image) + pytorch_ssim.ssim(pred_image, gt_image); b) Y: torchPSNR(rgb2ycbcr(pred_image[0]), rgb2ycbcr(gt_image[0])) + sk_cpt_ssim(rgb2ycbcr(pred_image[0]), rgb2ycbcr(gt_image[0]), data_range=1.0, multichannel=True).

The val data (and numbers) are: SOTS outdoor (500), Rain1400 (1400), CSD (2000).

Here are my results compared to the CVPR version:

Haze Rain Snow
RGB 31.35/0.9441 30.54/0.9004 30.10/0.9334
Y 33.39/0.9693 32.51/0.9218 31.68/0.9495
Yours 33.95/0.98 33.13/0.93 31.35/0.95

I think the metrics calculated on the Y channel are close to yours. Can you clarify this? Thanks!

jiaqixuac avatar Dec 19 '22 05:12 jiaqixuac

I get the same value on Rain1400 testset

huang-hz avatar Mar 31 '23 04:03 huang-hz

Do you generate the meta file for training? can you provide the generate code by dataset path?

jjb202 avatar Sep 07 '23 06:09 jjb202