| import cv2 |
| import numpy as np |
|
|
| import onnxruntime as ort |
| from .onnxdet import inference_detector |
| from .onnxpose import inference_pose |
|
|
| class Wholebody: |
| def __init__(self): |
| device = 'cuda:0' |
| providers = ['CPUExecutionProvider' |
| ] if device == 'cpu' else ['CUDAExecutionProvider'] |
| onnx_det = 'annotator/ckpts/yolox_l.onnx' |
| onnx_pose = 'annotator/ckpts/dw-ll_ucoco_384.onnx' |
|
|
| 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) |
| |
| neck = np.mean(keypoints_info[:, [5, 6]], axis=1) |
| |
| 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 |
|
|
|
|
|
|
