Python+OpenCV学习（7）---模板匹配

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利用python学习OpenCV，个人感觉比较方便。函数的形式与C++基本相同，所以切换过来还是比较好的，对于像我这种对python不太熟练的人，使用python的集成开发环境PyCharm进行学习，可以设置断点调试，有助于我这类初学者理解掌握。

下面是利用python语言结合OpenCV的模板匹配代码：

# -*- coding:utf-8 -*-__author__ = 'Microcosm'import cv2import numpy as npfrom matplotlib import pyplot as pltimg = cv2.imread("lena.jpg",0)img2 = img.copy()template = cv2.imread("eye.png",0)w,h = template.shape[::-1]# 6 中匹配效果对比算法methods = ['cv2.TM_CCOEFF', 'cv2.TM_CCOEFF_NORMED', 'cv2.TM_CCORR',           'cv2.TM_CCORR_NORMED', 'cv2.TM_SQDIFF', 'cv2.TM_SQDIFF_NORMED']for meth in methods:    img = img2.copy()    method = eval(meth)    res = cv2.matchTemplate(img,template,method)    min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)    if method in [cv2.TM_SQDIFF, cv2.TM_SQDIFF_NORMED]:        top_left = min_loc    else:        top_left = max_loc    bottom_right = (top_left[0] + w, top_left[1] + h)    cv2.rectangle(img,top_left, bottom_right, 255, 2)    print meth    plt.subplot(221), plt.imshow(img2,cmap= "gray")    plt.title('Original Image'), plt.xticks([]),plt.yticks([])    plt.subplot(222), plt.imshow(template,cmap= "gray")    plt.title('template Image'),plt.xticks([]),plt.yticks([])    plt.subplot(223), plt.imshow(res,cmap= "gray")    plt.title('Matching Result'), plt.xticks([]),plt.yticks([])    plt.subplot(224), plt.imshow(img,cmap= "gray")    plt.title('Detected Point'),plt.xticks([]),plt.yticks([])    plt.show()

各种对比方法的结果图如下所示：

1 cv2.TM_CCOEFF

2 cv2.TM_CCOEFF_NORMED

3 cv2.TM_CCORR

4 cv2.TM_CCORR_NORMED

5 cv2.TM_SQDIFF

6 cv2.TM_SQDIFF_NORMED

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