Algorithm/test.py at master · CaptchaLess/Algorithm · GitHub

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# -*- coding: utf-8 -*-
"""
Created on Wed Jan  6 16:57:58 2016

@author: Junfu Pu, pjh@mail.ustc.edu.cn

Algorithm for CaptchaLess
"""


import Image
import numpy as np
from CL_algorithm import YJS_EPC
from CL_algorithm import MIS

#def getTemplate_yjs():
#    im1 = Image.open('Template1/0130')
#    im2 = Image.open('Template1/3214')
#    im3 = Image.open('Template1/7564')
#    im4 = Image.open('Template1/7849')
#    bw_im1 = np.array(im1.convert('L'))>128
#    bw_im2 = np.array(im2.convert('L'))>128
#    bw_im3 = np.array(im3.convert('L'))>128
#    bw_im4 = np.array(im4.convert('L'))>128
#
#    dic_0 = bw_im1[:,0:10].copy()
#    dic_1 = bw_im1[:,10:20].copy()
#    dic_2 = bw_im2[:,10:20].copy()
#    dic_3 = bw_im2[:,0:10].copy()
#    dic_4 = bw_im2[:,30:40].copy()
#    dic_5 = bw_im3[:,10:20].copy()
#    dic_6 = bw_im3[:,20:30].copy()
#    dic_7 = bw_im3[:,0:10].copy()
#    dic_8 = bw_im4[:,10:20].copy()
#    dic_9 = bw_im4[:,30:40].copy()
#    Dict = [dic_0,dic_1,dic_2,dic_3,dic_4,dic_5,dic_6,dic_7,dic_8,dic_9]
#    return Dict
#
#def makePrediction_yjs(img_test):
#    Dict = getTemplate_yjs()
#    dist = np.zeros((10,4))
#    img_test = np.array(img_test.convert('L'))>128
#    for i in range(4):
#        subImg = img_test[:,i*10:(i+1)*10]
#        j = 0
#        for dic in Dict:
#            dist[j,i] = (dic^subImg).sum()
#            j += 1
#    result = dist.argmin(axis=0)
#    checkcode = repr(result)
#    return checkcode

#def getTemplate_mis():
#    Names_num = ['2.jpg','3.jpg','4.jpg','5.jpg','6.jpg', \
#                '7.jpg','8.jpg','9.jpg']
#    Names_alp = []
#    for i in range(65,91):
#        Names_alp.append(chr(i)+'.jpg')
#    Names_alp.remove('I.jpg')
#    Dict = []
#    label = []
#
#    i = 1
#    for name in Names_num:
#        img = Image.open('Template_mis/'+name)
#        bw_img = np.array(img.convert('L'))>128
#        Dict.append(bw_img)
#        label.append(str(i))
#        i += 1
#
#    for i in range(65,91):
#        label.append(chr(i))
#    label.remove('I')
#
#    for name in Names_alp:
#        img = Image.open('Template_mis/'+name)
#        bw_img = np.array(img.convert('L'))>128
#        Dict.append(bw_img)
#    return (Dict,label)
#
#def makePrediction_mis(img_test):
#    (Dict,label) = getTemplate_mis()
#    dist = np.zeros((10,4))
#    img_test = np.array(img_test.convert("L"))>128
#
#    for i in range(4):
#        subImage = img_test[i]
#        j = 0
#        for dict in Dict:
#            d = np.zeros(10)
#            for k in range(10):
#                subTemplate = dict[k:20+k,:]
#                d[k] = (subTemplate^subImage).sum()
#            dist[j,i] = d.min()
#            j += 1
#
#    result = dist.argmin(axis=0)
#    checkcode = repr(result)
#    return checkcode


if __name__=="__main__":
    img_test = Image.open("test1")
    yjs_epc = YJS_EPC()
    checkcode = yjs_epc.makePrediction_yjs(img_test)
#    checkcode = makePrediction_yjs(img_test)
    print(checkcode)

#    im = np.zeros((20,20))>1
#    test = [im,im,im,im]
    img_test_mis = Image.open('test_mis.jpg')
    mis = MIS()

    a = np.zeros((30,20))
    test = [a,a,a,a]

#    test = mis.split_codes(img_test_mis)
    print mis.makePrediction_mis_test(test)

#    getTemplate_mis()