基于stm32+opencv设计的人脸追踪系统（毕设/课设/竞赛/实训/项目开发）

import numpy as np import cv2 import ObjectDetectionModule2 as odm # face_detector = cv2.CascadeClassifier('../resource/haarcascade_frontalface_default.xml') # video = cv2.VideoCapture(1)#打开电脑上的摄像头 # mask = cv2.imread('../resource/glass.jpeg')#读取文件，速度慢 # while True: # flag,frame = video.read() # if flag == False: # break # gray = cv2.cvtColor(frame,code = cv2.COLOR_BGR2GRAY) # face_zones = face_detector.detectMultiScale(gray) # mask2 = mask.copy()#快 # for x,y,w,h in face_zones: # mask2 = cv2.resize(mask2,(w,h)) # #frame[y:y+h,x:x+w] = mask2 # for i in range(h):#高度 y # for j in range(w):#宽度 x # b,g,r = mask2[i,j] # if (b<180)&(g<180)&(r<180): # frame[y+i-10,x+j] = mask2[i,j] # cv2.imshow('ttnk',frame) # key = cv2.waitKey(41) # if key == ord('q'):#退出条件 # break # cv2.destroyAllWindows() # video.release() # cv2.imshow("ING",mask) # cv2.waitKey(0) def Mask(imgObjects,objects,mask): if len(objects)!=0 : mask2 = mask.copy()#快 x,y,w,h = objects[0][0] mask2 = cv2.resize(mask2,(w,h)) #frame[y:y+h,x:x+w] = mask2 for i in range(h):#高度 y for j in range(w):#宽度 x b,g,r = mask2[i,j] if (b<180)&(g<180)&(r<180): imgObjects[y+i-2,x+j] = mask2[i,j] return imgObjects def main(): faceCascade = cv2.CascadeClassifier('../resource/haarcascade_frontalface_default.xml') video = cv2.VideoCapture(1)#打开电脑上的摄像头 mask = cv2.imread('../resource/glass.jpeg')#读取文件，速度慢 while True: flag,imgObjects = video.read() if flag == False: break imgObjects = cv2.resize(imgObjects,(0,0),None,0.3,0.3) imgObjects,objects = odm.findObject(imgObjects,faceCascade) imgObjects = Mask(imgObjects,objects,mask) imgObjects = cv2.resize(imgObjects,(0,0),None,3,3) cv2.imshow('ttnk',imgObjects) key = cv2.waitKey(41) if key == ord('q'):#退出条件 break cv2.destroyAllWindows() video.release() if __name__== "__main__": main()