def draw_handpose()

in src/controlnet_aux/open_pose/util.py [0:0]

• 25 lines of code
• 12 McCabe index (conditional complexity)

def draw_handpose(canvas: np.ndarray, keypoints: Union[List[Keypoint], None]) -> np.ndarray:
    import matplotlib
    """
    Draw keypoints and connections representing hand pose on a given canvas.

    Args:
        canvas (np.ndarray): A 3D numpy array representing the canvas (image) on which to draw the hand pose.
        keypoints (List[Keypoint]| None): A list of Keypoint objects representing the hand keypoints to be drawn
                                          or None if no keypoints are present.

    Returns:
        np.ndarray: A 3D numpy array representing the modified canvas with the drawn hand pose.

    Note:
        The function expects the x and y coordinates of the keypoints to be normalized between 0 and 1.
    """
    if not keypoints:
        return canvas
    
    H, W, C = canvas.shape

    edges = [[0, 1], [1, 2], [2, 3], [3, 4], [0, 5], [5, 6], [6, 7], [7, 8], [0, 9], [9, 10], \
             [10, 11], [11, 12], [0, 13], [13, 14], [14, 15], [15, 16], [0, 17], [17, 18], [18, 19], [19, 20]]

    for ie, (e1, e2) in enumerate(edges):
        k1 = keypoints[e1]
        k2 = keypoints[e2]
        if k1 is None or k2 is None:
            continue
        
        x1 = int(k1.x * W)
        y1 = int(k1.y * H)
        x2 = int(k2.x * W)
        y2 = int(k2.y * H)
        if x1 > eps and y1 > eps and x2 > eps and y2 > eps:
            cv2.line(canvas, (x1, y1), (x2, y2), matplotlib.colors.hsv_to_rgb([ie / float(len(edges)), 1.0, 1.0]) * 255, thickness=2)

    for keypoint in keypoints:
        x, y = keypoint.x, keypoint.y
        x = int(x * W)
        y = int(y * H)
        if x > eps and y > eps:
            cv2.circle(canvas, (x, y), 4, (0, 0, 255), thickness=-1)
    return canvas