def test(epoch):
avg_psnr = 0
avg_ssim = 0
for left, right in testing_data_loader:
if args.direction == 'lr':
input.data.resize_(left.size()).copy_(left)
target.data.resize_(right.size()).copy_(right)
else:
input.data.resize_(right.size()).copy_(right)
target.data.resize_(left.size()).copy_(left)
prediction = netG(input)
im_true = np.transpose(target.data.cpu().numpy(), (0, 2, 3, 1))
im_test = np.transpose(prediction.data.cpu().numpy(), (0, 2, 3, 1))
for i in range(input.size(0)):
avg_psnr += psnr(im_true[i], im_test[i])
avg_ssim += (ssim(im_true[i,:,:,0], im_test[i,:,:,0]) + ssim(im_true[i,:,:,1], im_test[i,:,:,1]) + ssim(im_true[i,:,:,2], im_test[i,:,:,2])) / 3
print("[TEST] PSNR: {:.4f}; SSIM: {:.4f}".format(avg_psnr / len(test_set), avg_ssim / len(test_set)))
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