【opencv】树莓派picamera+opencv人脸识别

所需硬件

需要：

• 树莓派2
• 树莓派摄像头

• 云台+舵机（非必须）

d

在树莓派上搭建opencv环境

1.下载opencv-3.3.0
https://opencv.org/releases.html

2.安装opencv

   2.1    解压安装包 并复制到树莓派根目录   /home/pi

   2.2    编译并安装

1. cd ~/opencv  
2. mkdir build 
3. cd build
4. cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local .. 
5. make
6. sudo make install

大概20分钟后安装完成，下列代码可以查看opencv版本

pkg-config --modversion opencv

安装PiCamera

我使用树莓派官方摄像头2.0  800W像素

安装PiCamera:

官方镜像集成了此库，用官方镜像的小伙伴不必担心。

没有安装的可以用下列代码安装

sudo apt-get install python-pip sudo apt-get install python-dev sudo pip install picamera
1
2
3

此演示代码最高能达到22帧，在树莓派3B上测试，稍微有些延迟。

### Imports ################################################################### from picamera.array import PiRGBArrayfrom picamera import PiCamerafrom functools import partial import multiprocessing as mpimport cv2import osimport time ### Setup ##################################################################### os.putenv( 'SDL_FBDEV', '/dev/fb0' ) resX = 320resY = 240 # Setup the cameracamera = PiCamera()camera.resolution = ( resX, resY )camera.framerate = 90 t_start = time.time()fps = 0 # Use this as our outputrawCapture = PiRGBArray( camera, size=( resX, resY ) ) # The face cascade file to be usedface_cascade = cv2.CascadeClassifier( '/home/pi/opencv-3.3.0/data/lbpcascades/lbpcascade_frontalface.xml' )  ### Helper Functions ########################################################## def get_faces( img ):     gray = cv2.cvtColor( img, cv2.COLOR_BGR2GRAY )    return face_cascade.detectMultiScale( gray ), img def draw_frame( img, faces ):     global fps    global time_t     # Draw a rectangle around every face    for ( x, y, w, h ) in faces:        cv2.rectangle( img, ( x, y ),( x + w, y + h ), ( 200, 255, 0 ), 2 )     # Calculate and show the FPS    fps = fps + 1    sfps = fps / (time.time() - t_start)    cv2.putText(img, "FPS : " + str( int( sfps ) ), ( 10, 10 ), cv2.FONT_HERSHEY_SIMPLEX, 0.5, ( 0, 0, 255 ), 2 )     cv2.imshow( "Frame", img )    cv2.waitKey( 1 )  ### Main ###################################################################### if __name__ == '__main__':     pool = mp.Pool( processes=4 )     i = 0    rList = [None] * 17    fList = [None] * 17    iList = [None] * 17     camera.capture( rawCapture, format="bgr" )      for x in range ( 17 ):        rList[x] = pool.apply_async( get_faces, [ rawCapture.array ] )        fList[x], iList[x] = rList[x].get()        fList[x] = []     rawCapture.truncate( 0 )        for frame in camera.capture_continuous( rawCapture, format="bgr", use_video_port=True ):        image = frame.array         if   i == 1:            rList[1] = pool.apply_async( get_faces, [ image ] )            draw_frame( iList[2], fList[1] )         elif i == 2:            iList[2] = image            draw_frame( iList[3], fList[1] )         elif i == 3:            iList[3] = image            draw_frame( iList[4], fList[1] )         elif i == 4:            iList[4] = image            fList[5], iList[5] = rList[5].get()            draw_frame( iList[5], fList[5] )         elif i == 5:            rList[5] = pool.apply_async( get_faces, [ image ] )            draw_frame( iList[6], fList[5] )         elif i == 6:            iList[6] = image            draw_frame( iList[7], fList[5] )         elif i == 7:            iList[7] = image            draw_frame( iList[8], fList[5] )         elif i == 8:            iList[8] = image            fList[9], iList[9] = rList[9].get()            draw_frame( iList[9], fList[9] )         elif i == 9:            rList[9] = pool.apply_async( get_faces, [ image ] )            draw_frame( iList[10], fList[9] )         elif i == 10:            iList[10] = image            draw_frame( iList[11], fList[9] )         elif i == 11:            iList[11] = image            draw_frame( iList[12], fList[9] )         elif i == 12:            iList[12] = image            fList[13], iList[13] = rList[13].get()            draw_frame( iList[13], fList[13] )         elif i == 13:            rList[13] = pool.apply_async( get_faces, [ image ] )            draw_frame( iList[14], fList[13] )         elif i == 14:            iList[14] = image            draw_frame( iList[15], fList[13] )         elif i == 15:            iList[15] = image            draw_frame( iList[16], fList[13] )         elif i == 16:            iList[16] = image            fList[1], iList[1] = rList[1].get()            draw_frame( iList[1], fList[1] )             i = 0         i += 1         rawCapture.truncate( 0 )