Mirrors/ECCV2022-RIFE
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Fix ssim

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hzwer
2020-12-29 16:21:00 +08:00
parent 37c634cab8
commit b7d45bbc7c
1 changed files with 3 additions and 2 deletions
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benchmark/Vimeo90K.py
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@@ -8,6 +8,7 @@ import argparse
import numpy as np import numpy as np
from torch.nn import functional as F from torch.nn import functional as F
from pytorch_msssim import ssim_matlab from pytorch_msssim import ssim_matlab
# from model.RIFE2F15C import Model
from model.RIFE import Model from model.RIFE import Model
device = torch.device("cuda" if torch.cuda.is_available() else "cpu") device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
@@ -31,8 +32,8 @@ for i in f:
I0 = (torch.tensor(I0.transpose(2, 0, 1)).to(device) / 255.).unsqueeze(0) I0 = (torch.tensor(I0.transpose(2, 0, 1)).to(device) / 255.).unsqueeze(0)
I2 = (torch.tensor(I2.transpose(2, 0, 1)).to(device) / 255.).unsqueeze(0) I2 = (torch.tensor(I2.transpose(2, 0, 1)).to(device) / 255.).unsqueeze(0)
mid = model.inference(I0, I2)[0] mid = model.inference(I0, I2)[0]
ssim = ssim_matlab(torch.tensor(I1.transpose(2, 0, 1)).to(device).unsqueeze(0) / 255., mid.unsqueeze(0)).cpu().numpy() ssim = ssim_matlab(torch.tensor(I1.transpose(2, 0, 1)).to(device).unsqueeze(0) / 255., torch.round(mid * 255).unsqueeze(0) / 255.).detach().cpu().numpy()
mid = np.round((mid * 255).cpu().numpy()).astype('uint8').transpose(1, 2, 0) / 255. mid = np.round((mid * 255).detach().cpu().numpy()).astype('uint8').transpose(1, 2, 0) / 255.
I1 = I1 / 255. I1 = I1 / 255.
psnr = -10 * math.log10(((I1 - mid) * (I1 - mid)).mean()) psnr = -10 * math.log10(((I1 - mid) * (I1 - mid)).mean())
psnr_list.append(psnr) psnr_list.append(psnr)