Method get_params

transforms/transforms.py:317–350

Get a randomized transform to be applied on image. Arguments are same as that of __init__. Returns: Transform which randomly adjusts brightness, contrast and saturation in a random order.

(brightness, contrast, saturation, hue)

    @staticmethod
    def get_params(brightness, contrast, saturation, hue):
        """Get a randomized transform to be applied on image.

        Arguments are same as that of __init__.

        Returns:
            Transform which randomly adjusts brightness, contrast and
            saturation in a random order.
        """
        transforms = []
        if brightness > 0:
            brightness_factor = np.random.uniform(max(0, 1 - brightness), 1 + brightness)
            transforms.append(
                torch_tr.Lambda(lambda img: adjust_brightness(img, brightness_factor)))

        if contrast > 0:
            contrast_factor = np.random.uniform(max(0, 1 - contrast), 1 + contrast)
            transforms.append(
                torch_tr.Lambda(lambda img: adjust_contrast(img, contrast_factor)))

        if saturation > 0:
            saturation_factor = np.random.uniform(max(0, 1 - saturation), 1 + saturation)
            transforms.append(
                torch_tr.Lambda(lambda img: adjust_saturation(img, saturation_factor)))

        if hue > 0:
            hue_factor = np.random.uniform(-hue, hue)
            transforms.append(
                torch_tr.Lambda(lambda img: adjust_hue(img, hue_factor)))

        np.random.shuffle(transforms)
        transform = torch_tr.Compose(transforms)

        return transform

    def __call__(self, img):
        """