【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

 cd ~/opencv
 mkdir build
 cd build
 cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/usr/local ..
 make
 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

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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 PiRGBArray
from picamera import PiCamera
from functools import partial
 
import multiprocessing as mp
import cv2
import os
import time
 
### Setup #####################################################################
 
os.putenv( 'SDL_FBDEV', '/dev/fb0' )
 
resX = 320
resY = 240
 
# Setup the camera
camera = PiCamera()
camera.resolution = ( resX, resY )
camera.framerate = 90
 
t_start = time.time()
fps = 0
 
# Use this as our output
rawCapture = PiRGBArray( camera, size=( resX, resY ) )
 
# The face cascade file to be used
face_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 )