python调用opencv实现猫脸检测功能

Python  /  管理员 发布于 7年前   247

Python 小猫检测，通过调用opencv自带的猫脸检测的分类器进行检测。

分类器有两个：haarcascade_frontalcatface.xml和
haarcascade_frontalcatface_extended.xml。可以在opencv的安装目录下找到

D:\Program Files\OPENCV320\opencv\sources\data\haarcascades

小猫检测代码为：

1. 直接读取图片调用

import cv2image = cv2.imread("cat_04.png")gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)# load the cat detector Haar cascade, then detect cat faces# in the input imagedetector = cv2.CascadeClassifier("haarcascade_frontalcatface.xml")#haarcascade_frontalcatface_extended.xmlrects = detector.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=10, minSize=(100, 100))# loop over the cat faces and draw a rectangle surrounding eachprint (enumerate(rects))for (i, (x, y, w, h)) in enumerate(rects): cv2.rectangle(image, (x, y), (x + w, y + h), (0, 0, 255), 2) cv2.putText(image, "Cat #{}".format(i + 1), (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.55, (0, 0, 255), 2) print (i, x,y,w,h)# show the detected cat facescv2.imshow("Cat Faces", image)cv2.waitKey(1)

检测效果：

2. 通过命令控制符调用

也可以通过调用argparse库，进行整体调用

新建cat_detect.py文件

# import the necessary packagesimport argparseimport cv2# construct the argument parse and parse the argumentsap = argparse.ArgumentParser()ap.add_argument("-i", "--image", required=True, help="path to the input image")ap.add_argument("-c", "--cascade", default="haarcascade_frontalcatface_extended.xml",  help="path to cat detector haar cascade")args = vars(ap.parse_args())#"haarcascade_frontalcatface_extended.xml",# load the input image and convert it to grayscale#image = cv2.imread(args["image"])image = cv2.imread(args["image"])gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)# load the cat detector Haar cascade, then detect cat faces# in the input imagedetector = cv2.CascadeClassifier(args["cascade"])rects = detector.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=10, minSize=(120, 120)) # cat good# loop over the cat faces and draw a rectangle surrounding eachprint (enumerate(rects))for (i, (x, y, w, h)) in enumerate(rects): cv2.rectangle(image, (x, y), (x + w, y + h), (0, 0, 255), 2) cv2.putText(image, "cat #{}".format(i + 1), (x, y - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.55, (0, 0, 255), 2)# show the detected cat facescv2.imshow("Cat Faces", image)cv2.waitKey(0)

通过“命令控制符”调用

cmdcd E:\WORK\py\detectCatE:\WORK\py\detectCat>python cat_detector.py --image cat_07.png

以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持。