Python调用OpenCV实现人脸识别，供大家参考，具体内容如下
硬件环境：
Win10 64位
软件环境：
Python版本：2.7.3
IDE：JetBrains PyCharm 2016.3.2
Python库：
1.1) opencv-python(3.2.0.6)
搭建过程：
OpenCV Python库：
1. PyCharm的插件源中选择opencv-python(3.2.0.6)库安装
题外话：Python入门Tips
PS1：如何安装whl文件
1.先安装PIP
2.CMD命令进入D:\Python27\Scripts里面后再执行PIP命令安装pip install wheel
如果提示'pip'不是内部或外部命令，也不是可运行的程序或批处理文件：
①将python安装目录下的scripts目录（例如D:\Python27\Scripts）添加到系统环境变量path里，注意前加分号。再执行该命令
pip install wheel
②在cmd下进入到D:\Python27\Scripts目录下执行该命令
pip install wheel
3.把文件最好放在\Script文件夹里面再pip install xxxx.whl
4.注意whl文件名不能改 必须一模一样和原名
PS2：到哪找.whl文件？
相关代码：
import cv2
import numpy as np
cv2.namedWindow("test") # Create a window
cap = cv2.VideoCapture(0) #Open camera one
success, frame = cap.read() #Read one frame
print("Camera open operation is: ", success);
color = (255,0,0) #Config the color
classfier = cv2.CascadeClassifier("Resources\haarcascade_frontalface_alt.xml")
#Make sure this xml file is in the same directory with py file
#Otherwise change it to absolute directory. This xml file can be found in D:\My
Documents\Downloads\opencv\sources\data\haarcascades
while success:
success, frame = cap.read()
size = frame.shape[:2] #
image = np.zeros(size, dtype = np.float16) #
image = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) #
cv2.equalizeHist(image, image) #
#Below three lines config the minimal image size
divisor = 8
h, w = size
minSize = ((int)(w/divisor), (int)(h/divisor))
faceRects = classfier.detectMultiScale(image, 1.2, 2, cv2.CASCADE_SCALE_IMAGE, minSize) #Face detect
if len(faceRects) > 0:#If face array length > 0
for faceRect in faceRects: #Draw a rectangle for every face
xf, yf, wf, hf = faceRect
x = int((float)(xf))
y = int((float)(yf))
w = int((float)(wf))
h = int((float)(hf))
cv2.rectangle(frame, (x, y), (x + w, y + h), color)
cv2.circle(frame, ((int)(x + 1.2 * w / 4), (int)(y + h / 3)), min((int)(w / 8), (int)(h / 8)), (255, 0, 0))
cv2.circle(frame, ((int)(x + 2.8 * w / 4), (int)(y + h / 3)), min((int)(w / 8), (int)(h / 8)), (255, 0, 0))
#cv2.rectangle(frame, ((int)(x + 3 * w / 8, (int)(y + 3 * h / 4))), ((int)(x + 5 * w / 8), (int)(y + 7 * h / 8)), (255, 0, 0))
cv2.imshow("test", frame) #Display image
key = cv2.waitKey(10)
c = chr(key & 255)
if c in ['q', 'Q', chr(27)]:
break
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