def __call__(self, pic, target):
"""
Args:
pic (PIL Image or numpy.ndarray): Image to be converted to tensor.
Returns:
Tensor: Converted image.
"""
return F.to_tensor(pic), F.to_tensor(target)
def __call__(self, sample):
"""
Args:
pic (PIL Image or numpy.ndarray): Image to be converted to tensor.
Returns:
Tensor: Converted image.
"""
return F.to_tensor(sample)
def __call__(self, img, label):
"""
Args:
img (PIL Image): Image to be cropped.
Returns:
PIL Image: Cropped image.
"""
if self.padding > 0:
img = F.pad(img, self.padding)
# pad the width if needed
if self.pad_if_needed and img.size[0] < self.size[1]:
img = F.pad(img, (int((1 + self.size[1] - img.size[0]) / 2), 0))
# pad the height if needed
if self.pad_if_needed and img.size[1] < self.size[0]:
img = F.pad(img, (0, int((1 + self.size[0] - img.size[1]) / 2)))
i, j, h, w = self.get_params(img, self.size)
return F.to_tensor(F.crop(img, i, j, h,
w)), F.to_tensor(F.crop(label, i, j, h, w))