Python Opencv实践 - 人体姿态检测

本文仍然使用mediapipe做练手项目，封装一个PoseDetector类用作基础姿态检测类。

mediapipe中人体姿态检测的结果和手部跟踪检测的结果是类似的，都是输出一些定位点，各个定位点的id和对应人体的位置如下图所示：

关于mediapipe的pose解决方案类更详细的说明，可自行百度或参考这里：

MediaPipe基础（5）Pose(姿势)_mediapipe pose-CSDN博客文章浏览阅读1.5w次，点赞9次，收藏110次。1.摘要从视频中估计人体姿势在各种应用中起着至关重要的作用，例如量化体育锻炼、手语识别和全身手势控制。例如，它可以构成瑜伽、舞蹈和健身应用的基础。它还可以在增强现实中将数字内容和信息叠加在物理世界之上。MediaPipe Pose 是一种用于高保真身体姿势跟踪的 ML 解决方案，利用我们的 BlazePose 研究从 RGB 视频帧推断整个身体上的 33 个 3D 地标和背景分割掩码，该研究也为 ML Kit 姿势检测 API 提供支持。当前最先进的方法主要依赖于强大的桌面环境进行推理，而我们的方法在大_mediapipe posehttps://blog.csdn.net/weixin_43229348/article/details/120541448 和前面的手部检测代码类似，封装一个PoseDetector类，代码如下：

import cv2 as cv
import mediapipe as mp
import time#mediapipe的pose用于检测人体姿态
#参考资料：https://blog.csdn.net/weixin_43229348/article/details/120541448
class PoseDetector():def __init__(self,mode = False,modelComplexity = 1,upperBodyOnly = False,smoothLandmarks = True,minDetectionConfidence = 0.5,minTrackConfidence = 0.5):self.mpPose = mp.solutions.poseself.pose = self.mpPose.Pose(mode, modelComplexity, upperBodyOnly, smoothLandmarks, minDetectionConfidence, minTrackConfidence)self.mpDraw = mp.solutions.drawing_utilsdef Detect(self, img, drawOnImage = True):#mediapipe需要RGB，opencv默认的格式为BGR，进行转换imgRGB = cv.cvtColor(img, cv.COLOR_BGR2RGB)self.results = self.pose.process(imgRGB)if (self.results.pose_landmarks):#print(results.pose_landmarks)if drawOnImage:self.mpDraw.draw_landmarks(img, self.results.pose_landmarks, self.mpPose.POSE_CONNECTIONS)return imgdef GetPosition(self, img, drawOnImage = True):landmarkList = []if self.results.pose_landmarks:for id, landmark in enumerate(self.results.pose_landmarks.landmark):h,w,c = img.shapex = int(landmark.x * w)y = int(landmark.y * h)landmarkList.append([id, x, y])if (drawOnImage):#cv.circle(img, (x,y), 5, (0,255,0))cv.putText(img, str(id), (x,y), cv.FONT_HERSHEY_PLAIN, 1, (0,255,0), 1)return landmarkListdef DisplayFPS(img, preTime):curTime = time.time()if (curTime - preTime == 0):return curTime;fps = 1 / (curTime - preTime)cv.putText(img, "FPS:" + str(int(fps)), (10,70), cv.FONT_HERSHEY_PLAIN,3, (0,255,0), 3)return curTimedef main():poseDetector = PoseDetector()video = cv.VideoCapture('../../SampleVideos/acts.mp4')#FPS显示preTime = 0while True:ret,frame = video.read()if ret == False:break;frame = poseDetector.Detect(frame)poseDetector.GetPosition(frame)preTime = DisplayFPS(frame, preTime)cv.imshow('Real Time Hand Detection', frame)if cv.waitKey(10) & 0xFF == ord('q'):break;video.release()cv.destroyAllWindows()if __name__ == "__main__":main()

运行结果：