vs2022 + python实现人脸识别简单练手

vs2022需要安装python,c++

python环境：3.7

需要安装的包：cmake,boost,opencv-python，按顺序安装

 

代码

import cv2
import dlib
import os
import sys
import random
#存储位置
output_dir = 'D:/No1WorkSpace/JupyterNotebook/Facetrainset/Num&Name' #这里填编号+人名  
size = 256 #图片边长  

if not os.path.exists(output_dir):
os.makedirs(output_dir)
#改变图片的亮度与对比度  

def relight(img, light=1, bias=0):
w = img.shape[1]
h = img.shape[0]
#image = []
for i in range(0,w):
for j in range(0,h):
for c in range(3):
tmp = int(img[j,i,c]*light + bias)
if tmp > 255:
tmp = 255
elif tmp < 0:
tmp = 0
img[j,i,c] = tmp
return img

#使用dlib自带的frontal_face_detector作为我们的特征提取器  
detector = dlib.get_frontal_face_detector()
# 打开摄像头 参数为输入流，可以为摄像头或视频文件  
#camera = cv2.VideoCapture(0)
camera = cv2.VideoCapture('D:/视频/2.wmv')

index = 1
while True:
if (index <= 20):#存储15张人脸特征图像  
print('Being processed picture %s' % index)
# 从摄像头读取照片  
success, img = camera.read()
# 转为灰度图片  
gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# 使用detector进行人脸检测  
dets = detector(gray_img, 1)

for i, d in enumerate(dets):
x1 = d.top() if d.top() > 0 else 0
y1 = d.bottom() if d.bottom() > 0 else 0
x2 = d.left() if d.left() > 0 else 0
y2 = d.right() if d.right() > 0 else 0

face = img[x1:y1,x2:y2]
# 调整图片的对比度与亮度， 对比度与亮度值都取随机数，这样能增加样本的多样性  
face = relight(face, random.uniform(0.5, 1.5), random.randint(-50, 50))

face = cv2.resize(face, (size,size))

cv2.imshow('image', face)

cv2.imwrite(output_dir+'/'+str(index)+'.jpg', face)

index += 1
key = cv2.waitKey(30) & 0xff
if key == 27:
break
else:
print('Finished!')
# 释放摄像头 release camera  
camera.release()
# 删除建立的窗口 delete all the windows  
cv2.destroyAllWindows()
break