Function handDetect

DWPose/dwpose_utils/util.py:155–217

(candidate, subset, oriImg)

# detect hand according to body pose keypoints
# please refer to https://github.com/CMU-Perceptual-Computing-Lab/openpose/blob/master/src/openpose/hand/handDetector.cpp
def handDetect(candidate, subset, oriImg):
    # right hand: wrist 4, elbow 3, shoulder 2
    # left hand: wrist 7, elbow 6, shoulder 5
    ratioWristElbow = 0.33
    detect_result = []
    image_height, image_width = oriImg.shape[0:2]
    for person in subset.astype(int):
        # if any of three not detected
        has_left = np.sum(person[[5, 6, 7]] == -1) == 0
        has_right = np.sum(person[[2, 3, 4]] == -1) == 0
        if not (has_left or has_right):
            continue
        hands = []
        #left hand
        if has_left:
            left_shoulder_index, left_elbow_index, left_wrist_index = person[[5, 6, 7]]
            x1, y1 = candidate[left_shoulder_index][:2]
            x2, y2 = candidate[left_elbow_index][:2]
            x3, y3 = candidate[left_wrist_index][:2]
            hands.append([x1, y1, x2, y2, x3, y3, True])
        # right hand
        if has_right:
            right_shoulder_index, right_elbow_index, right_wrist_index = person[[2, 3, 4]]
            x1, y1 = candidate[right_shoulder_index][:2]
            x2, y2 = candidate[right_elbow_index][:2]
            x3, y3 = candidate[right_wrist_index][:2]
            hands.append([x1, y1, x2, y2, x3, y3, False])

        for x1, y1, x2, y2, x3, y3, is_left in hands:
            # pos_hand = pos_wrist + ratio * (pos_wrist - pos_elbox) = (1 + ratio) * pos_wrist - ratio * pos_elbox
            # handRectangle.x = posePtr[wrist*3] + ratioWristElbow * (posePtr[wrist*3] - posePtr[elbow*3]);
            # handRectangle.y = posePtr[wrist*3+1] + ratioWristElbow * (posePtr[wrist*3+1] - posePtr[elbow*3+1]);
            # const auto distanceWristElbow = getDistance(poseKeypoints, person, wrist, elbow);
            # const auto distanceElbowShoulder = getDistance(poseKeypoints, person, elbow, shoulder);
            # handRectangle.width = 1.5f * fastMax(distanceWristElbow, 0.9f * distanceElbowShoulder);
            x = x3 + ratioWristElbow * (x3 - x2)
            y = y3 + ratioWristElbow * (y3 - y2)
            distanceWristElbow = math.sqrt((x3 - x2) ** 2 + (y3 - y2) ** 2)
            distanceElbowShoulder = math.sqrt((x2 - x1) ** 2 + (y2 - y1) ** 2)
            width = 1.5 * max(distanceWristElbow, 0.9 * distanceElbowShoulder)
            # x-y refers to the center --> offset to topLeft point
            # handRectangle.x -= handRectangle.width / 2.f;
            # handRectangle.y -= handRectangle.height / 2.f;
            x -= width / 2
            y -= width / 2  # width = height
            # overflow the image
            if x < 0: x = 0
            if y < 0: y = 0
            width1 = width
            width2 = width
            if x + width > image_width: width1 = image_width - x
            if y + width > image_height: width2 = image_height - y
            width = min(width1, width2)
            # the max hand box value is 20 pixels
            if width >= 20:
                detect_result.append([int(x), int(y), int(width), is_left])

    ''&#x27;