mdiapipe pose姿态 onnx推理_pose_landmark_lite.tflite

python -m tf2onnx.convert --opset 11 --tflite pose_landmark_lite.tflite --output pose_landmark_lite.onnx

onnx 推理代码：

效果图：

import os
 
import cv2
 
import onnxruntime
import time
os.environ['TF_CPP_MIN_LOG_LEVEL']='3'
os.environ['CUDA_VISIBLE_DEVICES'] = '0'
 
import numpy as np
 
if __name__ == '__main__':
 
    for aa in [1,2]:
 
        # img_path=f'./166_{aa}.jpg'
        img_path=f'./03.jpg'
        img=cv2.imread(img_path)
 
        if img is None:
            exit(1)
        t_h, t_w = img.shape[:2]
        a_w = max(t_w, t_h)
        img_b = np.zeros((a_w, a_w, 3), dtype=np.uint8)
        if t_h > t_w:
            img_b[:,