图片匹配 Python3

import cv2
#图片匹配
def pictureMatch(pic,pic1='D:/test/1.jpg',):
    # #读取目标图片
    target = cv2.imread(pic)

    #读取模板图片
    template = cv2.imread(pic1)

    # 获得模板图片的高宽尺寸
    theight, twidth = template.shape[:2]

    # 执行模板匹配，采用的匹配方式cv2.TM_SQDIFF_NORMED
    result = cv2.matchTemplate(target, template, cv2.TM_SQDIFF_NORMED)

    # 归一化处理
    cv2.normalize(result, result, 0, 1, cv2.NORM_MINMAX, -1)

    # 寻找矩阵（一维数组当做向量，用Mat定义）中的最大值和最小值的匹配结果及其位置
    min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result)

    # 匹配值转换为字符串
    # 对于cv2.TM_SQDIFF及cv2.TM_SQDIFF_NORMED方法min_val越趋近与0匹配度越好，匹配位置取min_loc

    # 对于其他方法max_val越趋近于1匹配度越好，匹配位置取max_loc
    strmin_val = str(min_val)

    # 绘制矩形边框，将匹配区域标注出来
    # min_loc：矩形定点
    # (min_loc[0]+twidth,min_loc[1]+theight)：矩形的宽高
    # (0,0,225)：矩形的边框颜色；2：矩形边框宽度

    cv2.rectangle(target, min_loc, (min_loc[0] + twidth, min_loc[1] + theight), (0, 0, 225), 2)

    # 显示结果,并将匹配值显示在标题栏上
    # cv2.imshow("MatchResult----MatchingValue=" + strmin_val, target)
    # cv2.waitKey()
    # cv2.destroyAllWindows()
    # print(strmin_val)
    return strmin_val