Взлом старой каптчи сайта Хабрахабр

function [ rects ] = segmentator( aImg, nRect, lightMode ) %find all symbols on habrahabr login captcha %use:  rects = segmentator( aImg, nRect ) %where: %       rects       - rects coordinates %       aImg        - resized image data %       nRect       - count of rect to find %       lightMode   - find all rects without imOpen  %Много кода, из которого большая часть предназначена для случая когда символы склеены. if nargin < 4     fSRects = 0; end if nargin < 3     lightMode = 0; end      minX =  8;      if lightMode minX = 11; end     %px  minY = 16;      if lightMode minY = 18; end     %px  %% Change color mode to 8-bit gray if(size(size(aImg),2) > 2)     aImg = imadjust(rgb2gray(aImg)); end  %Save aImg aImgCopy = aImg;  %structuring element for imopen se = strel('disk', 2);  %Remove some noise  aImg(aImg > 0.92) = 1; aImg = imopen(imadjust(aImg), se);  if lightMode     aImg = aImgCopy; end  imBW3 = adaptivethreshold(aImg,50,0.2,0);  if ~lightMode     imBW3 = imopen(imBW3, se); end  %% find rects imBin = 1 - imBW3; CC = bwconncomp(imBin); numPixels = cellfun(@numel,CC.PixelIdxList); [biggest, idx] = sort(numPixels, 'descend'); bb = regionprops(CC, 'BoundingBox');  if lightMode     imshow(aImgCopy); end  %Primitive filter %copy only good rects bbCounter = 1; for i = 1 : length(bb)     curRect = bb(i).BoundingBox;     if (curRect(3) < minX || curRect(4) < minY)         continue;     end     bbNew(bbCounter) = bb(i);     bbCounter = bbCounter + 1; end  if bbCounter == 1     rects = {-1};     return; end  if DEBUG_MODE     for i = 1:length(bbNew)         rectangle('Position', bbNew(i).BoundingBox, 'EdgeColor', 'r');     end end  %analize count of rects %1: if rectC == nrect -> all rects find %2: else if rectC > nrect -> delete smallest %3: else -> find subrects  if nRect == length(bbNew) || fSRects == 1     rects = {bbNew(1:end).BoundingBox}; elseif nRect < length(bbNew)     rects = deleteSmallest( bbNew, nRect ) else      for i = 1 : length(bbNew)         curRect = bbNew(i).BoundingBox;         rectArea(i) = curRect(3) .* curRect(4);     end          needRect = nRect - length(bbNew);          aImg = aImgCopy;     [biggest, idx] = sort(rectArea, 'descend');                      switch(needRect) %@todo: Redesign (check constant)         case 1             subRects{1} = findSubRects( aImg, bbNew( idx(1)).BoundingBox, 2 );             subRectIdx = idx(1);         case 2             if( biggest(1) > 2 * biggest(2) )                 subRects{1} = findSubRects( aImg, bbNew(idx(1)).BoundingBox, 3 );                 subRectIdx = idx(1);             else                 subRects{1} = findSubRects( aImg, bbNew(idx(1)).BoundingBox, 2 );                 subRects{2} = findSubRects( aImg, bbNew(idx(2)).BoundingBox, 2 );                 subRectIdx = idx(1:2);             end         case 3             if( biggest(1)  > 3 * biggest(2) )                 subRects{1} = findSubRects( aImg, bbNew(idx(1)).BoundingBox, 4 );                 subRectIdx = idx(1);             elseif( biggest(1) > 1.5 * biggest(2) )                 subRects{1} = findSubRects( aImg, bbNew(idx(1)).BoundingBox, 3 );                 subRects{2} = findSubRects( aImg, bbNew(idx(2)).BoundingBox, 2 );                 subRectIdx = idx(1:2);             else                 subRects{1} = findSubRects( aImg, bbNew(idx(1)).BoundingBox, 2 );                 subRects{2} = findSubRects( aImg, bbNew(idx(2)).BoundingBox, 2 );                 subRects{3} = findSubRects( aImg, bbNew(idx(3)).BoundingBox, 2 );                 subRectIdx = idx(1:3);             end         otherwise             display('Not supported now'); %@todo: add more mode             rects = {-1};             return;     end          %create return value     rC = 1;     for srC = 1:length(bbNew)         if(sum(srC == subRectIdx))             curIdx = find(subRectIdx == srC);             for srC2 = 1 : length(subRects{curIdx})                 rects(rC) = subRects{curIdx}(srC2);                 rC = rC + 1;              end         else             rects{rC} = bbNew(srC).BoundingBox;             rC = rC + 1;         end     end end end  function [ subRects ] = findSubRects( aImg, curRect, nSubRect )     coord{1} = [0];                 pr(1) = 100;     coord{2} = [0 40];              pr(2) = 60;     coord{3} = [0 30 56];           pr(3) = 44;     coord{4} = [0 23 46 70];        pr(4) = 30;      MIN_AREA = 250;      if DEBUG_MODE         imshow(aImg);     end      wide = curRect(3);      for i = 1 : nSubRect         subRects{i}(1) = curRect(1) + coord{nSubRect}(i) * wide / 100;         subRects{i}(2) = curRect(2);         subRects{i}(3) = wide * pr(nSubRect) / 100;         subRects{i}(4) = curRect(4);          rect{i} = imcrop(aImg, subRects{i});          tmpRect = rect{i};         lvl = graythresh(tmpRect);         tmpRect = imadjust(tmpRect);         tmpRect(tmpRect > lvl + 0.3) = 1;imshow(tmpRect);         tmpRect(tmpRect < lvl - 0.3) = 0;imshow(tmpRect);         imbw3 = multiScaleBin(tmpRect,  0.22, 1.4, 30, 1);imshow(imbw3);         imbin = 1 - imbw3;         %imBin = binBlur(tmpRect, 13, 1); imshow(imBin); %other method of         %adaptive binarization          cc = bwconncomp(imbin);         numpixels = cellfun(@numel,cc.PixelIdxList);         [biggest, idx] = sort(numpixels, 'descend');         bb = regionprops(cc, 'Boundingbox');         imshow(rect{i});          %find biggest rect         clear rectArea;         for j = 1 : length(bb)             rectArea(j) = bb(j).BoundingBox(3) .* bb(j).BoundingBox(4);         end          [biggest, idx] = sort(rectArea, 'descend');          newRect = bb(idx(1)).BoundingBox;           rectangle('Position', newRect, 'EdgeColor', 'r');          if newRect(3) * newRect(4) > MIN_AREA             subRects{i}(1) = subRects{i}(1) + newRect(1) - 1;             subRects{i}(2) = subRects{i}(2) + newRect(2) - 1;             subRects{i}(3) = newRect(3);             subRects{i}(4) = newRect(4);         end     end end  function [ retValue ] = deleteSmallest( bbRects, nRects )     %1: calc area     for i = 1 : length(bbRects)         curRect = bbRects(i).BoundingBox;         rectArea(i) = curRect(3) .* curRect(4);     end          %2: sort area     [~, idx] = sort(rectArea, 'descend');     idx = idx(1:nRects);     idx = sort(idx);          %copy biggest     retValue = {bbRects(idx).BoundingBox}; end  function [ imBIN ] = sauvola( X, k )     h = fspecial('average');     local_mean = imfilter(X, h, 'symmetric');     local_std = sqrt(imfilter(X .^ 2, h, 'symmetric'));     imBIN = X >= (local_mean + k * local_std); end   

%CreateTrainSet.m  clear; clc;  workDir = '.\captch'; fileList = dir([workDir '\*.png']);  N_SYMB = 6;  SYMB_W = 18; %px SYMB_H = 28; %px  WIDTH = 166; %px HIGH  =  75; %px  SAVE_DIR = [workDir '\Alphabet'];  %process data for CC = 1 : length(fileList)     imName = fileList(CC).name;          recognizedRes = imName(1:N_SYMB);     %open image     [cdata, map] = imread( [workDir '\' imName] );         %change color mode     if ~isempty( map )         cdata = ind2rgb( cdata, map );                       end     %resize image     cdata = imresize(cdata, [HIGH WIDTH], 'lanczos3');           %find all symbols on image     rects = segmentator(cdata, N_SYMB, 1);     if rects{1} == -1         continue;     end          %imcrop and save     if length(rects) == N_SYMB         if ~exist(SAVE_DIR)             mkdir(SAVE_DIR);         end         for j = 1 : N_SYMB             if ~exist([SAVE_DIR '\' recognizedRes(j)])                 mkdir([SAVE_DIR '\' recognizedRes(j)]);             end                          imList = dir([SAVE_DIR '\' recognizedRes(j) '\*.jpg']);                        newname = num2str(length(imList) + 1);             nameS = floor(log10(length(imList) + 1)) + 1;             for z = nameS : 4                 newname = ['0' newname];             end                          tim = imcrop(cdata, rects{j});                          if (  size( size(tim), 2 ) > 2  )                 tim = imadjust(rgb2gray(tim));             end                          tim = imresize(tim, [SYMB_H SYMB_W], 'lanczos3');              imwrite(tim, [SAVE_DIR '\' recognizedRes(j) '\' newname '.jpg']);         end     end end 

function [net, alphabet, inpD, tarD] = train_NN(alphabet_dir, IM_W, IM_H, neuronC) %inputs: %   alphabet_dir - path to directory with alphabet %   IM_W - image width %   IM_H - image height %   neuronC - count of neuron in hidden layer %outputs: %   net - trained net %   alphabet - net alphabet %   inpD - input data %   tarD - target data % %   Vadym Drozd drozdvadym@gmail.com      dirList = dir([alphabet_dir '\']);     dir_name = {dirList([dirList(:).isdir]).name};      alphabetSize = length(dir_name) - 2;      try         a =  load([alphabet_dir '\' 'trainData_' num2str(IM_W) 'x' num2str(IM_H) '_.dat'], '-mat');     catch     end      try         target = a.target;         inpData = a.inpData;         alphabet = a.alphabet;     catch         for i = 3 : length(dir_name)             alphabet(i - 2) = dir_name{i};              imgList = dir([alphabet_dir '\' alphabet(i - 2) '\*.jpg']);             t_tar = zeros(alphabetSize, length(imgList));             t_tar(i - 2,:) = 1;              for j = 1 : length(imgList)                 im = imread([alphabet_dir '\' dir_name{i} '\' imgList(j).name]);                 im = imresize(im, [IM_H IM_W], 'lanczos3');  %resize image                 im = imadjust(im);                 im = double(im) /255.0;                 im = im(:);                 if i == 3 && j == 1                     inpData = im;                 else                     inpData = [inpData im];                 end             end             if i == 3                 target = t_tar;             else                 target = [target t_tar ];             end         end     end      %create and train NN     toc     min_max = minmax(inpData);     habrNN = newff(min_max, [IM_H * IM_W neuronC 23], {'logsig', 'tansig','logsig'}, 'trainrp');     habrNN.trainParam.min_grad = 10E-12;     habrNN = train(habrNN, inpData, target);      display('Training time:');     timeE = toc;     display(timeE);      net = habrNN;     inpD = inpData;     tarD= target;      save([alphabet_dir '\' 'trainData_' num2str(IM_W) 'x' num2str(IM_H) '_.dat'], 'inpData', 'target', 'alphabet'); end 

%% captchReader.m clear; close all; clc; cdir = './captch/'; fileList = dir([ cdir '\*.png']); load('49_67_net.mat'); load('alphabet.mat'); N_SYMB = 6;  SYMB_W = 10; SYMB_H = 12;  WIDTH = 166; %px HIGH  =  75; %px  SHOW_RECT = 1; %1 - show rects, else - don't show  correct = 0; %correct recognized results correctSymbC = 0; allSymbC = 0;  for CC = 1 : length(fileList)     imName = fileList(CC).name;     %open image     [cdata, map] = imread( [cdir '\' imName] );     %change color mode     if ~isempty( map )         cdata = ind2rgb( cdata, map );     end     %resize image     cdata = imresize(cdata, [HIGH WIDTH], 'lanczos3');     display(CC);     if (  size( size(cdata), 2 ) > 2  )         cdata = imadjust(rgb2gray(cdata));     end     rects = segmentator(cdata, N_SYMB, 0);          if SHOW_RECT         imshow(cdata);         for i = 1:length(rects)             colors = {'r', 'y', 'b', 'g', 'c', 'm'};             rectangle('Position', rects{i}, 'EdgeColor', colors{i});         end     end     if rects{1} == -1         continue;     end          %recognize     recognized = zeros(1, N_SYMB);     if length(rects) == N_SYMB         for j = 1 : N_SYMB             tim = imcrop(cdata, rects{j});             %resize image             tim = imadjust(imresize(tim, [SYMB_H SYMB_W], 'lanczos3'));             res = net(tim(:));             [sort_res, idx] = sort(res, 'descend');             recognized(j) = alphabet(idx(1));         end     end     correctSymbC = sum( (recognized - imName(1:6)) == 0);      allSymbC = allSymbC + N_SYMB;     if strcmp(recognized, imName(1:6))         correct = correct + 1;     end     if SHOW_RECT         title(['Recognize: ' recognized]);     end      end  fprintf('CAPTCH precision is: %2.2f %%', 100 * correct / length(fileList)); fprintf('Symbol precision: %2.2f %%', 100 * correctSymbC / allSymbC);