def __call__(self, oriImg):
        """call to process dwpose-detect

        Args:
            oriImg (np.ndarray): detected image

        """

        det_result = inference_jit_yolox(self.det, oriImg, detect_classes=[0])
        keypoints, scores = inference_jit_pose(self.pose, det_result, oriImg)

        keypoints_info = np.concatenate(
            (keypoints, scores[..., None]), axis=-1)
        # compute neck joint
        neck = np.mean(keypoints_info[:, [5, 6]], axis=1)
        # neck score when visualizing pred
        neck[:, 2:4] = np.logical_and(
            keypoints_info[:, 5, 2:4] > 0.3,
            keypoints_info[:, 6, 2:4] > 0.3).astype(int)
        new_keypoints_info = np.insert(
            keypoints_info, 17, neck, axis=1)
        mmpose_idx = [
            17, 6, 8, 10, 7, 9, 12, 14, 16, 13, 15, 2, 1, 4, 3
        ]
        openpose_idx = [
            1, 2, 3, 4, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16, 17
        ]
        new_keypoints_info[:, openpose_idx] = \
            new_keypoints_info[:, mmpose_idx]
        keypoints_info = new_keypoints_info

        keypoints, scores = keypoints_info[
            ..., :2], keypoints_info[..., 2]
        
        return keypoints, scores
call to process dwpose-detect

        Args:
            oriImg (np.ndarray): detected image

        
mimicmotion/dwpose/wholebody.py