树莓派制作人脸识别详细教程

1. 配置并更新树莓派系统

sudo raspi-config   // 进入后打开摄像头、SSH
sudo apt-get update
sudo apt-get upgrade
sudo rpi-update

2. 安装OpenCV的相关工具

sudo apt-get install build-essential cmake git pkg-config

3. 安装OpenCV的图像工具包

sudo apt-get install libjpeg8-dev 
sudo apt-get install libtiff5-dev 
sudo apt-get install libjasper-dev 
sudo apt-get install libpng12-dev 

4. 安装视频I/O包

sudo apt-get install libavcodec-dev libavformat-dev libswscale-dev libv4l-dev

5.安装gtk2.0和优化函数包

sudo apt-get install libgtk2.0-dev
sudo apt-get install libatlas-base-dev gfortran

6. 下载OpenCV源码

 wget -O opencv-3.4.1.zip https://github.com/Itseez/opencv/archive/3.4.1.zip

7.解压OpenCV

unzip opencv-3.4.1.zip

8. 安装OpenCV

// 根据下载的版本而定
cd opencv-3.2.0 
// 创建release文件夹
mkdir release
// 进入release目录下
cd release
// cmake读入所有源文件之后，自动生成makefile
cmake -D CMAKE_BUILD_TYPE=RELEASE \
-D CMAKE_INSTALL_PREFIX=/usr/local ..
// 编译
sudo make
// 安装
sudo make install
//更新动态链接库
sudo ldconfig

编译差不多7个小时，慢慢等…
9. 解决无法打开摄像头硬件问题

sudo nano /etc/modules
// 进入编辑界面后，在末尾添加输入
snd-bcm2835
bcm2835-v4l2

10. 测试用例Python代码

# -*- coding: utf-8 -*-
__author__ = "kyoRan"

import cv2

cap = cv2.VideoCapture(0)                                        # 打开摄像头
print("VideoCapture is opened?", cap.isOpened())

while(True):

    ret, frame = cap.read()                                      # 读取摄像头图像
    center = (frame.shape[1]//2, frame.shape[0]//2)              # 图像中心点位置

    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)               # 转灰度
    cv2.circle(gray, center=center, radius=100, color=(0,0,255)) # 画圆
    cv2.imshow("frame", gray)                                    # 显示图片

    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()            # 释放摄像头
cv2.destroyAllWindows()  # 关闭所有窗口

11.人脸识别代码

import numpy as np
import cv2
 
faceCascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
 
cap = cv2.VideoCapture(0)
cap.set(3,640) # set Width
cap.set(4,480) # set Height
 
while True:
    ret, img = cap.read()
    img = cv2.flip(img, -1)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    faces = faceCascade.detectMultiScale(
        gray,     
        scaleFactor=1.2,
        minNeighbors=5,     
        minSize=(20, 20)
    )
 
    for (x,y,w,h) in faces:
        cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
        roi_gray = gray[y:y+h, x:x+w]
        roi_color = img[y:y+h, x:x+w]  
 
    cv2.imshow('video',img)
 
    k = cv2.waitKey(30) & 0xff
    if k == 27: # press 'ESC' to quit
        break
 
cap.release()
cv2.destroyAllWindows()

haarcascade_frontalface_default.xml这个文件在网上下载到放到文件夹下就可以