使用YOLOv8进行姿态估计（ONNX推理）

转化为onnx权重：

from ultralytics import YOLO

model = YOLO("yolov8n-pose.pt")
success = model.export(format="onnx", simplify=True)  # export the model to onnx format
assert success
print("转换成功")

推理：

import onnxruntime
import numpy as np
import cv2
import time
# 调色板
palette = np.array([[255, 128, 0], [255, 153, 51], [255, 178, 102],
                    [230, 230, 0], [255, 153, 255], [153, 204, 255],
                    [255, 102, 255], [255, 51, 255], [102, 178, 255],
                    [51, 153, 255], [255, 153, 153], [255, 102, 102],
                    [255, 51, 51], [153, 255, 153], [102, 255, 102],
                    [51, 255, 51], [0, 255, 0], [0, 0, 255], [255, 0, 0],
                    [255, 255, 255]])
# 17个关键点连接顺序
skeleton = [[16, 14], [14, 12], [17, 15], [15, 13], [12, 13], [6, 12],
            [7, 13], [6, 7], [6, 8], [7, 9], [8, 10], [9, 11], [2, 3],
            [1, 2], [1, 3], [2, 4], [3, 5], [4, 6], [5, 7]]
# 骨架颜色
pose_limb_color = palette[[9, 9, 9, 9, 7, 7, 7, 0, 0, 0, 0, 0, 16, 16, 16, 16, 16, 16, 16]]
# 关键点颜色
pose_kpt_color = palette[[16, 16, 16, 16, 16, 0, 0, 0, 0, 0, 0, 9, 9, 9, 9, 9, 9]]

def letterbox(im, new_shape=(640, 640), color=(114, 114, 114), scaleup=