import cv2 import numpy as np import onnxruntime as ort import os from .xxxdet import inference_detector from .xxxpose import inference_pose import os class Wholebody: def __init__(self): device = 'cuda:0' providers = ['CPUExecutionProvider' ] if device == 'cpu' else ['CUDAExecutionProvider'] onnx_det = f'./dw_pose/checkpoints/yolox_l.xxx' onnx_pose = f'./dw_pose/checkpoints/dw-ll_ucoco_384.xxx' self.session_det = ort.InferenceSession(path_or_bytes=onnx_det, providers=providers) self.session_pose = ort.InferenceSession(path_or_bytes=onnx_pose, providers=providers) def __call__(self, oriImg): det_result = inference_detector(self.session_det, oriImg) keypoints, scores = inference_pose(self.session_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