python调用OpenCV实现人脸识别 python调用OpenCV实现人脸识别功能
jgw2008 人气:0Python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 cv2.destroyWindow("test")
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