(image_pred, image_gt, valid_mask=None, reduction='mean')
| 10 | return value |
| 11 | |
| 12 | def psnr(image_pred, image_gt, valid_mask=None, reduction='mean'): |
| 13 | return -10*torch.log10(mse(image_pred, image_gt, valid_mask, reduction)) |
| 14 | |
| 15 | def ssim(image_pred, image_gt, reduction='mean'): |
| 16 | """ |