def compute_visuals(self):
mid = self.opt.nframes // 2
self.LR = self.LR[:, mid, ...]
if self.opt.phase in ("train", "test"):
self.HR_GroundTruth = self.HR_GroundTruth[:, mid, ...]
if self.opt.phase in ("test", "apply"):
# remove pad for LR
if self.opt.phase == "test":
h, w = self.HR_GroundTruth.shape[
-2], self.HR_GroundTruth.shape[-1]
else: # apply
h, w = self.HR_GT_h, self.HR_GT_w
self.LR = remove_pad_for_tensor(tensor=self.LR,
HR_GT_h_w=(h, w),
factor=self.SR_factor,
LR_flag=True)
# remove pad for HR_G
self.HR_G = remove_pad_for_tensor(tensor=self.HR_G,
HR_GT_h_w=(h, w),
factor=self.SR_factor,
LR_flag=False)
# 将HR_G的边缘部分替换为LR的 两个像素
assert self.LR.shape == self.HR_G.shape # [1,3,H,W]
self.HR_G[..., 0:2, :] = self.LR[..., 0:2, :]
self.HR_G[..., -2:, :] = self.LR[..., -2:, :]
self.HR_G[..., :, 0:2] = self.LR[..., :, 0:2]
self.HR_G[..., :, -2:] = self.LR[..., :, -2:]
def compute_visuals(self):
mid = self.opt.nframes // 2
self.LR = self.LR[:, mid, ...]
if self.opt.phase == "test":
# remove pad for LR
self.LR = remove_pad_for_tensor(
tensor=self.LR,
HR_GT_h_w=(self.HR_GroundTruth.shape[-2],
self.HR_GroundTruth.shape[-1]),
factor=self.SR_factor,
LR_flag=True)
# remove pad for HR_G
self.HR_G = remove_pad_for_tensor(
tensor=self.HR_G,
HR_GT_h_w=(self.HR_GroundTruth.shape[-2],
self.HR_GroundTruth.shape[-1]),
factor=self.SR_factor,
LR_flag=False)
self.HR_Bicubic = torch.nn.functional.interpolate(
self.LR,
scale_factor=self.SR_factor,
mode='bicubic',
align_corners=False)