【项目】Python人脸识别（GUI界面）—

这个我是通过pyqt来设计了一个简单的GUI界面，配置pyqt环境我在我之前的一篇博客介绍过了——pyqt的介绍

使用了两个简单的button来进行一个可视化。

项目代码

====

人脸采集

---

import numpy as np

import cv2

def b():

print(‘正在调用摄像头！’)

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()

#将彩色图转为灰度图

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 == ord(‘s’):

n = input(‘请输入编号：’)

cv2.imwrite(‘./data/jm/’+n+‘.jpg’,roi_gray)

if k == 27: # press ‘ESC’ to quit

break

cap.release()

cv2.destroyAllWindows()

b()

数据训练

---

import os

import cv2

import sys

from PIL import Image

import numpy as np

def getImageAndLabels(path):

facesSamples=[]

ids=[]

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

#检测人脸

face_detector = cv2.CascadeClassifier(‘haarcascade_frontalface_alt2.xml’)

#打印数组imagePaths

print(‘数据排列：’,imagePaths)

#遍历列表中的图片

for imagePa