OpenCV中的图片模板匹配（6种方式，可以遍历找出最佳匹配）

import numpy as np
from cv2 import cv2

target = cv2.imread('messi5.jpg', 0)

template = cv2.imread('template.jpg', 0)
w, h = template.shape[::-1]
# 列表中所有的6种比较方法
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:
    method = eval(meth)
    # 应用模板匹配
    res = cv2.matchTemplate(target, template, method)
    min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(res)
    # 如果方法是TM_SQDIFF或TM_SQDIFF_NORMED，则取最小值
    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(target, top_left, bottom_right, 255, 2)
    # 显示结果,并将匹配值显示在标题栏上
    # cv2画图
    strmin_val = str(min_val)
    cv2.imshow("MatchResult----MatchingValue=" + strmin_val, target)
    cv2.waitKey()
    cv2.destroyAllWindows()
    
#  plt 画图
    plt.subplot(121),plt.imshow(res,cmap = 'gray')
    plt.title('Matching Result'), plt.xticks([]), plt.yticks([])
    plt.subplot(122),plt.imshow(img,cmap = 'gray')
    plt.title('Detected Point'), plt.xticks([]), plt.yticks([])
    plt.suptitle(meth)
    plt.show()