OpenPose 基于OpenCV DNN 的单人姿态估计

最新推荐文章于 2025-07-01 21:41:56 发布

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最新推荐文章于 2025-07-01 21:41:56 发布

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分类专栏：姿态估计

本文链接：https://blog.youkuaiyun.com/zziahgf/article/details/88900813

原文: OpenPose 基于OpenCV DNN 的单人姿态估计 - AIUAI

OpenCV4.0 版本以后可以直接读取 Caffe、TensorFlow、ONNX 等模型的 API，直接采用OpenCV 的 DNN 模块即可.

这里主要测试下基于 DNN 模块和 OpenPose 模型的单人人体姿态估计的具体实现.

Github 项目 - OpenPose 关键点输出格式 - AIUAI

Github 项目 - OpenPose Python API - AIUAI

Github 项目 - OpenPose 模型与Demos - AIUAI

OpenPose 人体姿态模型下载路径：

BODY25: http://posefs1.perception.cs.cmu.edu/OpenPose/models/pose/body_25/pose_iter_584000.caffemodel
COCO: http://posefs1.perception.cs.cmu.edu/OpenPose/models/pose/coco/pose_iter_440000.caffemodel
MPI: http://posefs1.perception.cs.cmu.edu/OpenPose/models/pose/mpi/pose_iter_160000.caffemodel

具体完整代码为：

#!/usr/bin/python3
#!--*-- coding: utf-8 --*--
from __future__ import division
import cv2
import time
import numpy as np
import matplotlib.pyplot as plt
import os


class general_pose_model(object):
    def __init__(self, modelpath, mode="BODY25"):
        # 指定采用的模型
        #   Body25: 25 points
        #   COCO:   18 points
        #   MPI:    15 points
        self.inWidth = 368
        self.inHeight = 368
        self.threshold = 0.1
        if mode == "BODY25":
            self.pose_net = self.general_body25_model(modelpath)
        elif mode == "COCO":
            self.pose_net = self.general_coco_model(modelpath)
        elif mode == "MPI":
            self.pose_net = self.get_mpi_model(modelpath)


    def get_mpi_model(self, modelpath):
        self.points_name = {
   
    
            "Head": 0, "Neck": 1, 
            "RShoulder": 2, "RElbow": 3, "RWrist": 4,
            "LShoulder": 5, "LElbow": 6, "LWrist": 
            7, "RHip": 8, "RKnee": 9, "RAnkle": 10, 
            "LHip": 11, "LKnee": 12, "LAnkle": 13, 
            "Chest": 14, "Background": 15 }
        self.num_points = 15
        self.point_pairs = [[0, 1], [1, 2], [2, 3], 
                            [3, 4], [1, 5], [5, 6], 
                            [6, 7], [1, 14],[14, 8], 
                            [8, 9], [9, 10], [14