Function rescale

src/transformers/src/transformers/image_transforms.py:97–132

Rescales `image` by `scale`. Args: image (`np.ndarray`): The image to rescale. scale (`float`): The scale to use for rescaling the image. data_format (`ChannelDimension`, *optional*): The channel dimension format of the image. If

(
    image: np.ndarray,
    scale: float,
    data_format: Optional[ChannelDimension] = None,
    dtype: np.dtype = np.float32,
    input_data_format: Optional[Union[str, ChannelDimension]] = None,
)

def rescale(
    image: np.ndarray,
    scale: float,
    data_format: Optional[ChannelDimension] = None,
    dtype: np.dtype = np.float32,
    input_data_format: Optional[Union[str, ChannelDimension]] = None,
) -> np.ndarray:
    """
    Rescales `image` by `scale`.

    Args:
        image (`np.ndarray`):
            The image to rescale.
        scale (`float`):
            The scale to use for rescaling the image.
        data_format (`ChannelDimension`, *optional*):
            The channel dimension format of the image. If not provided, it will be the same as the input image.
        dtype (`np.dtype`, *optional*, defaults to `np.float32`):
            The dtype of the output image. Defaults to `np.float32`. Used for backwards compatibility with feature
            extractors.
        input_data_format (`ChannelDimension`, *optional*):
            The channel dimension format of the input image. If not provided, it will be inferred from the input image.

    Returns:
        `np.ndarray`: The rescaled image.
    """
    if not isinstance(image, np.ndarray):
        raise TypeError(f"Input image must be of type np.ndarray, got {type(image)}")

    rescaled_image = image * scale
    if data_format is not None:
        rescaled_image = to_channel_dimension_format(rescaled_image, data_format, input_data_format)

    rescaled_image = rescaled_image.astype(dtype)

    return rescaled_image


def _rescale_for_pil_conversion(image):