Python調(diào)用OpenCV實現(xiàn)人臉識別，供大家參考，具體內(nèi)容如下

硬件環(huán)境：

Win10 64位

軟件環(huán)境：

Python版本：2.7.3

IDE：JetBrains PyCharm 2016.3.2

Python庫：

1.1) opencv-python(3.2.0.6)

搭建過程：

OpenCV Python庫：

1. PyCharm的插件源中選擇opencv-python(3.2.0.6)庫安裝

題外話：Python入門Tips

PS1：如何安裝whl文件

1.先安裝PIP

2.CMD命令進入D:/Python27/Scripts里面后再執(zhí)行PIP命令安裝pip install wheel
如果提示'pip'不是內(nèi)部或外部命令，也不是可運行的程序或批處理文件：
①將python安裝目錄下的scripts目錄（例如D:/Python27/Scripts）添加到系統(tǒng)環(huán)境變量path里，注意前加分號。再執(zhí)行該命令
pip install wheel
②在cmd下進入到D:/Python27/Scripts目錄下執(zhí)行該命令
pip install wheel

3.把文件最好放在/Script文件夾里面再pip install xxxx.whl

4.注意whl文件名不能改 必須一模一樣和原名

PS2：到哪找.whl文件？

相關(guān)代碼：

import cv2import numpy as npcv2.namedWindow("test") # Create a windowcap = cv2.VideoCapture(0) #Open camera onesuccess, frame = cap.read() #Read one frameprint("Camera open operation is: ", success);color = (255,0,0) #Config the colorclassfier = 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/haarcascadeswhile 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)]:    breakcv2.destroyWindow("test")

以上就是本文的全部內(nèi)容，希望對大家的學習有所幫助，也希望大家多多支持武林站長站。