安装好Python与树莓派外置硬件GPIO库文件

sudo apt-get install python-rpi.gpio

在python中使用GPIO示例：

import RPi.GPIO as GPIO

#### gpio init

GPIO.setmode(GPIO.BCM)

GPIO.setup(7, GPIO.OUT) #LED2

GPIO.setup(8, GPIO.OUT) #LED1

GPIO.output(7, GPIO.LOW) #LED2 ON

GPIO.output(8, GPIO.HIGH)#LED1 OFF

fswebcam，这是一款小型摄像头程序，可以直接通过Raspbian的仓库来安装，

sudo apt-get install fswebcam

fswebcam --help

以下运行的示例：

pi@raspberrypi:~ $ fswebcam --no-banner --device /dev/video0 -r 1600x1200 b.jpg

--- Opening /dev/video0...

Trying source module v4l2...

/dev/video0 opened.

No input was specified, using the first.

--- Capturing frame...

Captured frame in 0.00 seconds.

--- Processing captured image...

Disabling banner.

Writing JPEG image to 'b.jpg'.

使用opencv自带的VideoCapture()函数定义摄像头对象，其参数0表示第一个摄像头，保存一张照片：

#-*- coding=utf-8 -*-

import cv2

import numpy as np

import time

cap = cv2.VideoCapture(1)

ret,frame = cap.read()

#cv2.imshow('frame',frame)#一个窗口用以显示原视频

filename = "/home/pi/" + time.strftime('%Y%m%d-%H%M%S') + ".jpg"

cv2.imwrite(filename, frame)

cap.release()

cv2.destroyAllWindows()

以下实例通过USB摄像头拍摄一张图片，并通过载入特征文件对图片进行人脸识别，取出对应的人脸部分并保存为小图。

特征文件可以通过在命令行中用find命令来查找：

sudo find / -iname "*haarcascades*" > /home/pi/opencv_find.txt

完整的代码如下：

#-*- coding=utf-8 -*-

import os

from PIL import Image, ImageDraw

import cv2.cv as cv

import cv2

#OPCV_PATH = "/opt/Wolfram/WolframEngine/11.2/SystemFiles"

def detect_object(image):

'''检测图片，获取人脸在图片中的坐标'''

grayscale = cv.CreateImage((image.width, image.height), 8, 1)

cv.CvtColor(image, grayscale, cv.CV_BGR2GRAY)

#cascade = cv.Load(OPCV_PATH+"/Data/haarcascades/frontalface.xml")

cascade = cv.Load("/opt/Wolfram/WolframEngine/11.2/SystemFiles/Data/Haarcascades/frontalface.xml")

rect = cv.HaarDetectObjects(grayscale, cascade, cv.CreateMemStorage(), 1.1, 2,

cv.CV_HAAR_DO_CANNY_PRUNING, (20,20))

result = []

for r in rect:

result.append((r[0][0], r[0][1], r[0][0]+r[0][2], r[0][1]+r[0][3]))

return result

def process(infile):

'''在原图上框出头像并且截取每个头像到单独文件夹'''

image = cv.LoadImage(infile);

if image:

faces = detect_object(image)

im = Image.open(infile)

path = os.path.abspath(infile)

save_path = os.path.splitext(path)[0]+"_face"

#save_path = "/home/pi" + "_face"

try:

os.mkdir(save_path)

except:

pass

if faces:

draw = ImageDraw.Draw(im)

count = 0

for f in faces:

count += 1

draw.rectangle(f, outline=(255, 0, 0))

a = im.crop(f)

file_name = os.path.join(save_path,str(count)+".jpg")

# print file_name

a.save(file_name)

drow_save_path = os.path.join(save_path,"out.jpg")

im.save(drow_save_path, "JPEG", quality=80)

else:

print "Error: cannot detect faces on %s" % infile

if __name__ == "__main__":

os.system("fswebcam --no-banner --device /dev/video0 -r 1600x1200 b.jpg")

process("b.jpg")

拍到的照片如下：

通过以上程序的运行，框出了脸所在区域，

并将这些部分区域截取出来，存成小文件。