Commit 8d03fc1f authored by narugo1992's avatar narugo1992
Browse files

dev(narugo): fix docs

parent 92cfd18a

imgutils/preprocess/torchvision.py

+38 −5
Original line number Diff line number Diff line
@@ -397,13 +397,21 @@ if _HAS_TORCHVISION: 
        Resize and center-pad PIL image to target size with background color.

        TorchVision-compatible transform that can be composed.



        This transform first resizes the input image to fit within the target size

        while preserving its aspect ratio, then pads the result with the specified

        background color to reach the exact target dimensions.



        :param size: Target size as (height, width) tuple or single int for square output

        :type size: Union[Tuple[int, int], int]

        :param background_color: Color to use for padding. Can be string name, RGB/RGBA tuple, or single int

        :param interpolation: Interpolation mode for resizing, defaults to BILINEAR

        :type interpolation: InterpolationMode



        :raises ValueError: If size or background_color format is invalid



        :example:



        >>> transform = PadToSize(size=(300, 300), background_color='black')

        >>> padded_image = transform(input_image)

        """



        def __init__(self, size: Union[Tuple[int, int], int],
@@ -417,6 +425,15 @@ if _HAS_TORCHVISION: 
            _parse_color_to_rgba(self.background_color)



        def _pad_pil_image(self, pic):

            """

            Pad a PIL image to the target size.



            :param pic: Input PIL Image

            :type pic: PIL.Image.Image



            :return: Padded PIL Image

            :rtype: PIL.Image.Image

            """

            return pad_image_to_size(

                pic=pic,

                size=self.size,
@@ -425,6 +442,16 @@ if _HAS_TORCHVISION: 
            )



        def _pad_tensor(self, tensor):

            """

            Pad a tensor to the target size.



            :param tensor: Input tensor image

            :type tensor: torch.Tensor



            :return: Padded tensor

            :rtype: torch.Tensor

            :raises ValueError: If tensor dimensions are not 3 or 4

            """

            from ..data.pad import _parse_color_to_mode



            if tensor.ndim < 3 or tensor.ndim > 4:
@@ -488,12 +515,12 @@ if _HAS_TORCHVISION: 
            """

            Apply padding transform to input image.



            :param pic: Input PIL Image

            :type pic: PIL.Image.Image

            :param pic: Input image (PIL Image or torch.Tensor)

            :type pic: Union[PIL.Image.Image, torch.Tensor]



            :return: Padded image with target size

            :rtype: PIL.Image.Image

            :raises TypeError: If input is not a PIL Image

            :rtype: Union[PIL.Image.Image, torch.Tensor]

            :raises TypeError: If input is not a PIL Image or torch.Tensor

            """

            if isinstance(pic, Image.Image):

                return self._pad_pil_image(pic)
@@ -503,6 +530,12 @@ if _HAS_TORCHVISION: 
                raise TypeError('pic should be PIL Image or a tensor. Got {}'.format(type(pic)))



        def __repr__(self) -> str:

            """

            Return string representation of the transform.



            :return: String representation

            :rtype: str

            """

            detail = f"(size={self.size}, interpolation={self.interpolation.value}, background_color={self.background_color})"

            return f"{self.__class__.__name__}{detail}"