[人工智能]树莓派自制人脸识别考勤机

一、硬件准备

? ? ? ? 1，树莓派3B

? ? ? ? 2，pi camera

? ? ? ? 3，工具：键盘、鼠标、显示器、SD卡读写器

二、SD卡烧录操作系统

? ? ? ? 1，U盘格式化软件?SDFormatterv4

? ? ? ? 2，系统烧写工具?Win32DiskImager

? ? ? ? 3，系统镜像文件?ubuntu-mate-16.04.2-desktop-armhf-raspberry-pi.img

三、软件系统安装

? ? ? ?1，测试相机

? ? ? ? ? 打开摄像头，预览几秒后保存一张图片。

#新建终端
raspistill -o mytest.jpg

? ? ? ? ? ?或者终端输入：返回检测到的相机数量。

vcgencmd get_camera

???????2，python3安装

? ? ? ? ? ? ? ? 参考CSDN教程安装，完成后查看版本号：

python3 -V

? ? ? ? 3，opencv安装

sudo apt-get install libopencv-dev
sudo apt-get install python-opencv

??????????????完成后查看版本号：

pkg-config opencv --modversion

? ? ? ? ? ?在python中添加cv2，并查看版本号：

python
import cv2
cv2.__version__

四、源码编写

? ? ? ? 1，人脸检测

import numpy as np
import cv2

# multiple cascades: https://github.com/Itseez/opencv/tree/master/data/haarcascades
faceCascade = cv2.CascadeClassifier('Cascades/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()

? ? ? ? 2，人脸识别

? ? ? ? 数据库采集：

import cv2
import os

cam = cv2.VideoCapture(0)
cam.set(3, 640) # set video width
cam.set(4, 480) # set video height

face_detector = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

# For each person, enter one numeric face id
face_id = input('\n enter user id end press <return> ==>  ')

print("\n [INFO] Initializing face capture. Look the camera and wait ...")
# Initialize individual sampling face count
count = 0

while(True):

    ret, img = cam.read()
    img = cv2.flip(img, -1) # flip video image vertically
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    faces = face_detector.detectMultiScale(gray, 1.3, 5)

    for (x,y,w,h) in faces:

        cv2.rectangle(img, (x,y), (x+w,y+h), (255,0,0), 2)     
        count += 1

        # Save the captured image into the datasets folder
        cv2.imwrite("dataset/User." + str(face_id) + '.' + str(count) + ".jpg", gray[y:y+h,x:x+w])

        cv2.imshow('image', img)

    k = cv2.waitKey(100) & 0xff # Press 'ESC' for exiting video
    if k == 27:
        break
    elif count >= 30: # Take 30 face sample and stop video
         break

# Do a bit of cleanup
print("\n [INFO] Exiting Program and cleanup stuff")
cam.release()
cv2.destroyAllWindows()

? ? ? ? ? 训练模型：?

pip install opencv-contrib-python

import cv2
import numpy as np
from PIL import Image
import os

# Path for face image database
path = 'dataset'

recognizer = cv2.face.LBPHFaceRecognizer_create()
detector = cv2.CascadeClassifier("haarcascade_frontalface_default.xml");

# function to get the images and label data
def getImagesAndLabels(path):

    imagePaths = [os.path.join(path,f) for f in os.listdir(path)]     
    faceSamples=[]
    ids = []

    for imagePath in imagePaths:

        PIL_img = Image.open(imagePath).convert('L') # convert it to grayscale
        img_numpy = np.array(PIL_img,'uint8')

        id = int(os.path.split(imagePath)[-1].split(".")[1])
        faces = detector.detectMultiScale(img_numpy)

        for (x,y,w,h) in faces:
            faceSamples.append(img_numpy[y:y+h,x:x+w])
            ids.append(id)

    return faceSamples,ids

print ("\n [INFO] Training faces. It will take a few seconds. Wait ...")
faces,ids = getImagesAndLabels(path)
recognizer.train(faces, np.array(ids))

# Save the model into trainer/trainer.yml
recognizer.write('trainer/trainer.yml') # recognizer.save() worked on Mac, but not on Pi

# Print the numer of faces trained and end program
print("\n [INFO] {0} faces trained. Exiting Program".format(len(np.unique(ids))))

? ? ? ? 后台开发：使用IDEA软件开发后台，接收树莓派上传的数据存储在mySQL数据库。

?????????

五、成果展示