# -*- coding: utf-8 -*-
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#测试模板匹配灰度
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__author__ = '上海色宁'
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import os
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import sys
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import cv2
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from cv2 import waitKey
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import numpy as np
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import uuid
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def load_digits():
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# 加载数字模板文件夹
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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
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#多加几个模板图片
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digits.append(cv2.imread(path + "/t_00.jpg"))
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digits.append(cv2.imread(path + "/t_01.jpg"))
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digits.append(cv2.imread(path + "/t_02.jpg"))
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digits.append(cv2.imread(path + "/t_03.jpg"))
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digits.append(cv2.imread(path + "/t_04.jpg"))
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digits.append(cv2.imread(path + "/t_05.jpg"))
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digits.append(cv2.imread(path + "/t_06.jpg"))
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digits.append(cv2.imread(path + "/t_07.jpg"))
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digits.append(cv2.imread(path + "/t_08.jpg"))
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digits.append(cv2.imread(path + "/t_09.jpg"))
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def get_most_simmilar_digit(target_img):
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source = []
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for digitROI in digits:
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res = cv2.matchTemplate(target_img, digitROI, cv2.TM_CCOEFF_NORMED)
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max_val = cv2.minMaxLoc(res)[1]
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source.append(max_val)
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print(source.index(max(source)))
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#判断匹配度，大于0.5的选取
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if max(source) > 0.5 :
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return source.index(max(source))
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else:
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return '-'
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digits = []
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# 测试
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if __name__ == '__main__':
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load_digits()
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path = "./images"
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filename = os.listdir(path) # 获取文件夹文件
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for file in filename:
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img = cv2.imread(path + "/" + file) # 读取图片
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cv2.imshow('a',img)
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waitKey(0)
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addtext =get_most_simmilar_digit(img)
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if not addtext=="-" :
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cv2.imwrite(path + "2/"+str(addtext)+"__"+file,img)
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if cv2.waitKey(1) & 0xFF == ord('q'):
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break
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