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# ColorJitter

class torchvision.transforms.ColorJitter(brightness: Union[float, Tuple[float, float]] = 0, contrast: Union[float, Tuple[float, float]] = 0, saturation: Union[float, Tuple[float, float]] = 0, hue: Union[float, Tuple[float, float]] = 0)

  Randomly change the brightness, contrast, saturation and hue of an image. If the image is torch Tensor, it is expected to have […, 1 or 3, H, W] shape, where … means an arbitrary number of leading dimensions. If img is PIL Image, mode “1”, “I”, “F” and modes with transparency (alpha channel) are not supported.

  Parameters:

    - brightness (float or tuple of python:float (min, max)) – How much to jitter brightness. brightness_factor is chosen uniformly from [max(0, 1 - brightness), 1 + brightness] or the given [min, max]. Should be non negative numbers.

    - contrast (float or tuple of python:float (min, max)) – How much to jitter contrast. contrast_factor is chosen uniformly from [max(0, 1 - contrast), 1 + contrast] or the given [min, max]. Should be non-negative numbers.

    - saturation (float or tuple of python:float (min, max)) – How much to jitter saturation. saturation_factor is chosen uniformly from [max(0, 1 - saturation), 1 + saturation] or the given [min, max]. Should be non negative numbers.

    - hue (float or tuple of python:float (min, max)) – How much to jitter hue. hue_factor is chosen uniformly from [-hue, hue] or the given [min, max]. Should have 0<= hue <= 0.5 or -0.5 <= min <= max <= 0.5. To jitter hue, the pixel values of the input image has to be non-negative for conversion to HSV space; thus it does not work if you normalize your image to an interval with negative values, or use an interpolation that generates negative values before using this function.

  forward(img)
    Parameters:

      img (PIL Image or Tensor) – Input image.

    Returns:

      Color jittered image.

    Return type:

      PIL Image or Tensor

  static get_params(brightness: Optional[List[float]], contrast: Optional[List[float]], saturation: Optional[List[float]], hue: Optional[List[float]]) → Tuple[Tensor, Optional[float], Optional[float], Optional[float], Optional[float]]

    Get the parameters for the randomized transform to be applied on image.

    Parameters:

      - brightness (tuple of python:float (min, max), optional) – The range from which the brightness_factor is chosen uniformly. Pass None to turn off the transformation.

      - contrast (tuple of python:float (min, max), optional) – The range from which the contrast_factor is chosen uniformly. Pass None to turn off the transformation.

      - saturation (tuple of python:float (min, max), optional) – The range from which the saturation_factor is chosen uniformly. Pass None to turn off the transformation.

      - hue (tuple of python:float (min, max), optional) – The range from which the hue_factor is chosen uniformly. Pass None to turn off the transformation.

    Returns:

      The parameters used to apply the randomized transform along with their random order.

    Return type:

      tuple

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