# -*- coding: utf-8 -*-


#测试模板匹配灰度
__author__ = '上海色宁'

import os
import sys
import cv2
from cv2 import waitKey
import numpy as np
import uuid


def load_digits():
    # 加载数字模板文件夹
    path = './tm'    # 这个地方就是获取当前运行目录 获取函数在主函数里面
    #多加几个模板图片

   
    digits.append(cv2.imread(path + "/t_00.jpg"))
    digits.append(cv2.imread(path + "/t_01.jpg"))
    digits.append(cv2.imread(path + "/t_02.jpg"))
    digits.append(cv2.imread(path + "/t_03.jpg"))
    digits.append(cv2.imread(path + "/t_04.jpg"))
    digits.append(cv2.imread(path + "/t_05.jpg"))
    digits.append(cv2.imread(path + "/t_06.jpg"))
    digits.append(cv2.imread(path + "/t_07.jpg"))
    digits.append(cv2.imread(path + "/t_08.jpg"))
    digits.append(cv2.imread(path + "/t_09.jpg"))
        
        
def get_most_simmilar_digit(target_img):
    source = []
    for digitROI in digits:
        res = cv2.matchTemplate(target_img, digitROI, cv2.TM_CCOEFF_NORMED)
        max_val = cv2.minMaxLoc(res)[1]
        source.append(max_val)
    print(source.index(max(source)))
    #判断匹配度，大于0.5的选取
    if max(source) > 0.5 :
        return source.index(max(source))
    else:
        return '-'




digits = []
    
# 测试
if __name__ == '__main__':
    load_digits()
    path = "./images"
    filename = os.listdir(path)    # 获取文件夹文件
    for file in filename:
        img = cv2.imread(path + "/" + file)    # 读取图片
        cv2.imshow('a',img)
        waitKey(0)
        addtext =get_most_simmilar_digit(img)
        if not addtext=="-" :
            cv2.imwrite(path + "2/"+str(addtext)+"__"+file,img)
        if cv2.waitKey(1) & 0xFF == ord('q'):
        	break