0 介绍

目的：使用mediapipe库做手部的实时跟踪
检测流程：（1）手掌检测；（2）手掌特征检测
手掌特征分布：mediapipe手掌特征分布如下：

1.环境要求

后续代码运行环境（跟教程略有版本上的差异）：
opencv-python 4.7.0.72
mediapipe 0.10.14

2.代码

import cv2  			#图像处理库
import mediapipe as mp  #手部跟踪库
import time  
  
# 将手部检测封装成类
class handDetector():  
    def __init__(self, mode=False, maxHands=2, model_complexity=1,detectionCon=0.5, trackCon=0.5):
        self.mode = mode  
        self.maxHands = maxHands  
        self.model_complexity=model_complexity #注意此处，低版本无此参数
        self.detectionCon = detectionCon  
        self.trackCon = trackCon  
        
        self.mpHands = mp.solutions.hands  
        self.hands = self.mpHands.Hands(self.mode, self.maxHands, self.model_complexity,self.detectionCon, self.trackCon)# 注意多了一个模块参数
        self.mpDraw = mp.solutions.drawing_utils  
  	# 检测全部手掌并绘制相应的手部特征
    def findHands(self, img, draw=True):  
        imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)  
        self.results = self.hands.process(imgRGB)  
        if self.results.multi_hand_landmarks:  
            for handLms in self.results.multi_hand_landmarks:  
                if draw:  
                    self.mpDraw.draw_landmarks(img, handLms, self.mpHands.HAND_CONNECTIONS)  
        return img  
        
    # 对第handNo编号的手掌进行特殊绘制处理
    def findPosition(self, img, handNo=0, draw=True):  
        lmList = []  
        if self.results.multi_hand_landmarks:  
            myHand = self.results.multi_hand_landmarks[handNo]
            for id, lm in enumerate(myHand.landmark):  
                h, w, c = img.shape  
                cx, cy = int(lm.x * w), int(lm.y * h)
                lmList.append([id, cx, cy])
                if draw:
                    cv2.circle(img, (cx, cy), 5, (255, 0, 255), cv2.FILLED)
        return lmList

  
def test():
   
    pTime = 0  
    detector = handDetector()  
    cap = cv2.VideoCapture('test.mp4')  #可以替换为实时镜头
    cv2.namedWindow("Image", cv2.WINDOW_NORMAL)  
    cv2.resizeWindow("Image", 800, 600)  
    
  
    while True:  
        success, img = cap.read()  
        print(success)
        if not success:  
            break  
  
        img = detector.findHands(img)  
        lmList = detector.findPosition(img,draw=True)
  
        cTime = time.time()  
        fps = 1 / (cTime - pTime) if (cTime - pTime) != 0 else 0  
        pTime = cTime  
        cv2.putText(img, str(int(fps)), (10, 70), cv2.FONT_HERSHEY_PLAIN, 3, (255, 0, 255), 3)  
        cv2.imshow("Image", img)  
  
        if cv2.waitKey(1) & 0xFF == ord('q'):  
            break  
  
    cap.release()  
    cv2.destroyAllWindows()  
  
if __name__ == "__main__":  
    test()

4.参考

（1）B站视频-实时手部跟踪视频教程
（2）gitee代码仓库
（3）教程源地址cv zone（1）（2）均来自此正式教程。