需求：当一个页面存在多个相同的按键，通过图像识别的方式点击指定的按键

思路：
1.每次匹配到按键的区域后将区域从源图像中去掉
2.根据按键与左上角 (0,0) 的长度对按键进行排序
（忽略长度相同的情况，可换其他角的坐标计算解决）

source.jpg

match.jpg

from PIL import Image
import numpy
from airtest.core.cv import Template
from airtest import aircv
from airtest.core.helper import G
from airtest.utils.transform import TargetPos
import time
from math import sqrt

class Template2(Template):
    def __int__(self,*args, **kwargs):
        super.__init__(*args, **kwargs)

    #重写match_in,return加上识别到的区域(match_result)
    def match_in(self, screen):
        match_result = self._cv_match(screen)
        G.LOGGING.debug("match result: %s", match_result)
        if not match_result:
            return None
        focus_pos = TargetPos().getXY(match_result, self.target_pos)
        return focus_pos,match_result

def p(search,source,total,index):
    """
    :param search: 匹配图像
    :param source: 源图像
    :param total: 相同图像总数
    :param index: 匹配索引
    :return: 匹配坐标
    """

    result = []
    source_array=numpy.array(Image.open(source))
    t = time.time()
    for i in range(total):
        im_search = Template2(search)
        im_source = aircv.imread(source)
        pos,match = im_search.match_in(im_source) #匹配坐标和匹配区域
        array = numpy.array(Image.open(source))#创建矩阵

        #将区域填充为白色
        for col in range(match['rectangle'][0][0],match['rectangle'][-1][0]):
            for row in range(match['rectangle'][0][1],match['rectangle'][1][1]):
                array[row,col] = [255,255,255]

        Image.fromarray(array).save(source)#更新源图像
        result.append(pos)

    result.sort(key= lambda x: sqrt(x[0]*x[0]+x[1]*x[1]))#根据距离(0,0)排序
    print(time.time() - t)
    print(result)
    Image.fromarray(source_array).save(source)
    return result[index]


print(p('./search.jpg','./source.jpg',10,0))

#输出
0.0870201587677002
[(112, 63), (112, 119), (160, 63), (160, 119), (208, 63), (208, 119), (256, 63), (256, 119), (304, 63), (304, 119)]
(112, 63)