torchvision/transforms/functional.py
def to_grayscale(img, num_output_channels=1):
    """Convert image to grayscale version of image.

    Args:
        img (PIL Image): Image to be converted to grayscale.

    Returns:
        PIL Image: Grayscale version of the image.
            if num_output_channels = 1 : returned image is single channel

            if num_output_channels = 3 : returned image is 3 channel with r = g = b
    """
    if not _is_pil_image(img):
        raise TypeError('img should be PIL Image. Got {}'.format(type(img)))

    if num_output_channels == 1:
        img = img.convert('L')
    elif num_output_channels == 3:
        img = img.convert('L')
        np_img = np.array(img, dtype=np.uint8)
        np_img = np.dstack([np_img, np_img, np_img])
        img = Image.fromarray(np_img, 'RGB')
    else:
        raise ValueError('num_output_channels should be either 1 or 3')

    return img
def to_grayscale(img, num_output_channels=1):
    if not _is_pil_image(img):
        raise TypeError('img should be PIL Image. Got {}'.format(type(img)))

    if num_output_channels == 1:
        img = img.convert('L')
    elif num_output_channels == 3:
        img = img.convert('L')
        np_img = np.array(img, dtype=np.uint8)
        np_img = np.dstack([np_img, np_img, np_img])
        img = Image.fromarray(np_img, 'RGB')
    else:
        raise ValueError('num_output_channels should be either 1 or 3')

    return img
def to_grayscale ( img , num_output_channels = 1 ) : if not _is_pil_image ( img ) : raise TypeError ( 'img should be PIL Image. Got {}' . format ( type ( img ) ) ) if num_output_channels == 1 : img = img . convert ( 'L' ) elif num_output_channels == 3 : img = img . convert ( 'L' ) np_img = np . array ( img , dtype = np . uint8 ) np_img = np . dstack ( [ np_img , np_img , np_img ] ) img = Image . fromarray ( np_img , 'RGB' ) else : raise ValueError ( 'num_output_channels should be either 1 or 3' ) return img
Convert image to grayscale version of image.

    Args:
        img (PIL Image): Image to be converted to grayscale.

    Returns:
        PIL Image: Grayscale version of the image.
            if num_output_channels = 1 : returned image is single channel

            if num_output_channels = 3 : returned image is 3 channel with r = g = b
Convert image to grayscale version of image .