(img, gamma, gain=1)
return img
Perform gamma correction on an image.

    Also known as Power Law Transform. Intensities in RGB mode are adjusted
    based on the following equation:

        I_out = 255 * gain * ((I_in / 255) ** gamma)

    See https://en.wikipedia.org/wiki/Gamma_correction for more details.

    Args:
        img (PIL Image): PIL Image to be adjusted.
        gamma (float): Non negative real number. gamma larger than 1 make the
            shadows darker, while gamma smaller than 1 make dark regions
            lighter.
        gain (float): The constant multiplier.
Perform gamma correction on an image.
Perform gamma correction on an image .
def adjust_gamma(img, gamma, gain=1):
    """Perform gamma correction on an image.

    Also known as Power Law Transform. Intensities in RGB mode are adjusted
    based on the following equation:

        I_out = 255 * gain * ((I_in / 255) ** gamma)

    See https://en.wikipedia.org/wiki/Gamma_correction for more details.

    Args:
        img (PIL Image): PIL Image to be adjusted.
        gamma (float): Non negative real number. gamma larger than 1 make the
            shadows darker, while gamma smaller than 1 make dark regions
            lighter.
        gain (float): The constant multiplier.
    """
    if not _is_pil_image(img):
        raise TypeError('img should be PIL Image. Got {}'.format(type(img)))

    if gamma < 0:
        raise ValueError('Gamma should be a non-negative real number')

    input_mode = img.mode
    img = img.convert('RGB')

    np_img = np.array(img, dtype=np.float32)
    np_img = 255 * gain * ((np_img / 255) ** gamma)
    np_img = np.uint8(np.clip(np_img, 0, 255))

    img = Image.fromarray(np_img, 'RGB').convert(input_mode)
    return img
def adjust_gamma ( img , gamma , gain = 1 ) : if not _is_pil_image ( img ) : raise TypeError ( 'img should be PIL Image. Got {}' . format ( type ( img ) ) ) if gamma < 0 : raise ValueError ( 'Gamma should be a non-negative real number' ) input_mode = img . mode img = img . convert ( 'RGB' ) np_img = np . array ( img , dtype = np . float32 ) np_img = 255 * gain * ( ( np_img / 255 ) ** gamma ) np_img = np . uint8 ( np . clip ( np_img , 0 , 255 ) ) img = Image . fromarray ( np_img , 'RGB' ) . convert ( input_mode ) return img