(img, bounding_boxes, facial_landmarks=[])
return img_copy
Draw bounding boxes and facial landmarks.

    Arguments:
        img: an instance of PIL.Image.
        bounding_boxes: a float numpy array of shape [n, 5].
        facial_landmarks: a float numpy array of shape [n, 10].

    Returns:
        an instance of PIL.Image.
Draw bounding boxes and facial landmarks.
Draw bounding boxes and facial landmarks .
def show_bboxes(img, bounding_boxes, facial_landmarks=[]):
    """Draw bounding boxes and facial landmarks.

    Arguments:
        img: an instance of PIL.Image.
        bounding_boxes: a float numpy array of shape [n, 5].
        facial_landmarks: a float numpy array of shape [n, 10].

    Returns:
        an instance of PIL.Image.
    """

    img_copy = img.copy()
    draw = ImageDraw.Draw(img_copy)

    for b in bounding_boxes:
        draw.rectangle([
            (b[0], b[1]), (b[2], b[3])
        ], outline='white')

    for p in facial_landmarks:
        for i in range(5):
            draw.ellipse([
                (p[i] - 1.0, p[i + 5] - 1.0),
                (p[i] + 1.0, p[i + 5] + 1.0)
            ], outline='blue')

    return img_copy
def show_bboxes ( img , bounding_boxes , facial_landmarks = [ ] ) : img_copy = img . copy ( ) draw = ImageDraw . Draw ( img_copy ) for b in bounding_boxes : draw . rectangle ( [ ( b [ 0 ] , b [ 1 ] ) , ( b [ 2 ] , b [ 3 ] ) ] , outline = 'white' ) for p in facial_landmarks : for i in range ( 5 ) : draw . ellipse ( [ ( p [ i ] - 1.0 , p [ i + 5 ] - 1.0 ) , ( p [ i ] + 1.0 , p [ i + 5 ] + 1.0 ) ] , outline = 'blue' ) return img_copy