out: torch.Tensor = (data * std) + mean
return out
def normalize_min_max(x: torch.Tensor, min_val: float = 0., max_val: float = 1., eps: float = 1e-6) -> torch.Tensor:
rNormalise an image tensor by MinMax and re-scales the value between a range.
After Change
out: torch.Tensor = (data.view(shape[0], shape[1], -1) * std) + mean
return out.view(shape)
def normalize_min_max(x: torch.Tensor, min_val: float = 0., max_val: float = 1., eps: float = 1e-6) -> torch.Tensor:
rNormalise an image tensor by MinMax and re-scales the value between a range.
