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76 lines
2.1 KiB
Python
76 lines
2.1 KiB
Python
#coding=utf-8
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import os
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import numpy as np
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import cv2
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import json
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from hyperlpr import pipline as pp
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import sys
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from Levenshtein import StringMatcher as sm
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reload(sys)
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sys.setdefaultencoding("utf-8")
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parent= "you folder"
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def comparestring(a,b):
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g = 0
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if len(a) == len(b):
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for x,y in zip(a,b):
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if x!=y:
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g+=1
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return g
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count = 0 ;
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count_p = 0
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count_d = 0
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count_lev = 0
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count_undetected = 0
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roi = [470,400,650,580]
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for filename in os.listdir(parent):
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path = os.path.join(parent,filename)
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print path
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if path.endswith(".jpg") or path.endswith(".png"):
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ics,name = os.path.split(path)
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name,ext = name.split(".")
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image = cv2.imread(path)
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image = image[roi[1]:roi[1]+roi[3],roi[0]:roi[0]+roi[2]]
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# cv2.imshow("test",image)
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# cv2.waitKey(0)
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info,dataset = pp.SimpleRecognizePlate(image)
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ext = ext.strip()
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name = name.strip()
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if len(dataset)==0:
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count_undetected +=1
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# cv2.imwrite("./cache/bad2/" + name + ".png", image)
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for one in dataset:
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# p = sm.StringMatcher(seq1=one.encode("utf-8"),seq2=name.encode("utf-8"))
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A = one.decode("utf-8")
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B = name.decode("utf-8")
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print one.decode("utf-8"),"<->",name.decode("utf-8"),"编辑距离:",comparestring(A,B)
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if comparestring(A,B)<3:
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count_lev+=1
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else:
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cv2.imwrite("./cache/bad2/"+B+"->"+A+".png",image)
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if one.decode("utf-8") == name.decode("utf-8"):
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count_p+=1
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break
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else:
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print "error",one.decode("utf-8"), name.decode("utf-8")
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count_d+=1
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# cv2.imshow("image",image)
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# cv2.waitKey(0)
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# break
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count+=1
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print count_p / float(count),"编辑距离[1]:",count_lev/float(count),u"识出",count_p,u"总数",count,u"未识出",count_d,u"未检测出",count_undetected
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if count_p+count_d+count_undetected!=count:
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print dataset,len(dataset)
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# exit(0)
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