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Commit 561f86d

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‎src/+helper/adjustBBoxCoordinates.m‎

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function boxes = adjustBBoxCoordinates(boxes, imageScale)
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% This function gives final coordinates of bounding boxes.
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% Copyright 2021 The Mathworks, Inc.
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scale = 2 * (1/imageScale);
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if isempty(boxes)
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boxes = [0 0 0 0 0 0 0 0];
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else
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num_boxes = size(boxes,1);
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for k = 1:num_boxes
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if ~isnan(boxes(k,:))
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boxes(k,:) = boxes(k,:) * scale;
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end
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end
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end
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end

‎src/+helper/connectedComponents.m‎

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function [nLabels, labels, stats] = connectedComponents(textScoreComb,connectivity)
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% This function computes the connected components labeled image and
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% statistics output for each label.
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% Copyright 2021 The MathWorks, Inc.
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% compute connected components
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CC = bwconncomp(textScoreComb,connectivity);
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% number of connected components in image
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nLabels = CC.NumObjects;
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% compute label matrix to label connected components in the image
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labels = labelmatrix(CC);
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% compute a set of properties like area, boundingbox for each connected component
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stats = regionprops(CC,'Area','BoundingBox','Centroid');
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end
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function model = downloadPretrainedCRAFT()
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% The downloadPretrainedEfficientDetD0 function downloads the pretrained
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% CRAFT network.
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%
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% Copyright 2021 The MathWorks, Inc.
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dataPath = 'model';
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modelName = 'craftModel';
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netFileFullPath = fullfile(dataPath, modelName);
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% Add '.zip' extension to the data.
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netFileFull = [netFileFullPath,'.zip'];
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if ~exist(netFileFull,'file')
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fprintf(['Downloading pretrained', modelName ,'network.\n']);
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fprintf('This can take several minutes to download...\n');
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url = 'https://ssd.mathworks.com/supportfiles/vision/deeplearning/models/TextDetection/craftModel.zip';
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websave (netFileFullPath,url);
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unzip(netFileFullPath, dataPath);
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model = load([dataPath, '/craftNet.mat']);
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else
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fprintf('Pretrained EfficientDet-D0 network already exists.\n\n');
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unzip(netFileFullPath, dataPath);
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model = load([dataPath, '/craftNet.mat']);
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end
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end

‎src/+helper/getPolygonBoxes.m‎

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function polys = getPolygonBoxes(boxes, labels, mapper)
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% This function generates polygon shape bounding boxes from quadrilateral
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% boxes.
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% Copyright 2021 The Mathworks, Inc.
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% configurations
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numCp = 5;
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maxLenRatio = 0.7;
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expandRatio = 1.45;
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rMax = 2.0;
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rStep = 0.2;
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polys = [];
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for i = 1:size(boxes,1)
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box = reshape(boxes(i,:,:),[2 4]);
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box = box';
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% size filter for small instance
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w = int32(norm(box(1,:)-box(2,:))+1);
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h = int32(norm(box(2,:)-box(3,:))+1);
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if w < 10 || h < 10
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polys = [polys; NaN([1 28])];
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continue;
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end
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% warp image
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tar = double([[1,1];[w,1];[w,h];[1,h]]);
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M = fitgeotrans(box,tar,'projective');
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wordLabel = imwarp(labels,M,'nearest','OutputView',imref2d([h w]));
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try
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Minv = inv(transpose(M.T));
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catch
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polys = [polys; NaN([1 28])];
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continue;
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end
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% binarization for selected label
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cur_label = mapper(i);
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wordLabel(wordLabel ~= cur_label) = 0;
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wordLabel(wordLabel > 0) = 1;
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% Polygon generation
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% find top/bottom contours
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cp = []; % stores the top and bottom location of the column in word label containing word
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maxLen = -1;
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for j = 1:w
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region = find(wordLabel(:,j)~=0);
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if size(region,1) < 2
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continue
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end
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cp = [cp; [j,region(1),region(end)]];
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lengths = region(end) - region(1) + 1;
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if lengths > maxLen
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maxLen = lengths;
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end
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end
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% pass if maxLen is similar to h
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if h * maxLenRatio < maxLen
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polys = [polys; NaN([1 28])];
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continue;
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end
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% get pivot points with fixed length
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totSeg = numCp * 2 + 1;
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segW = double(w)/totSeg; % segment_width
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pp = repmat([nan,nan],numCp,1); % init pivot points
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cpSection = repmat([0,0],totSeg,1); % stores center point of each section
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segHeight = zeros([1 numCp]);
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segNum = 1;
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numSec = 0;
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prevH = -1;
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for k = 1:length(cp)
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x = cp(k,1);
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sy = cp(k,2);
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ey = cp(k,3);
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if (segNum) * segW <= (x-1) && segNum <= totSeg
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% average previous segment
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if numSec == 0
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break;
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end
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cpSection(segNum,:) = [cpSection(segNum,1)/numSec cpSection(segNum,2)/numSec];
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numSec = 0;
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% reset variables
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segNum = segNum + 1;
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prevH = -1;
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end
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% accumulate center points
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cy = (sy + ey) * 0.5;
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curH = ey - sy + 1;
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cpSection(segNum,:) = [cpSection(segNum,1)+x cpSection(segNum,2)+cy];
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numSec = numSec + 1;
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if mod(segNum,2) ~= 0
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continue; % No polygon area
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end
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if prevH < curH
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pp(int32((segNum)/2),:) = [x cy];
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segHeight(int32((segNum)/2)) = curH;
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prevH = curH;
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end
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end
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% processing last segment
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if numSec ~=0
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cpSection(end,:) = [cpSection(end,1)/numSec cpSection(end,2)/numSec];
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end
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% pass if num of pivots is not sufficient or segment width i
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% smaller than character height
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if any(any(isnan(pp))) || (segW < max(segHeight)*0.25)
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polys = [polys;NaN([1 28])];
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continue;
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end
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%calc median maximum of pivot points
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halfCharH = median(segHeight)*(expandRatio/2);
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%calculate gradient and apply to make horizontal pivots
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newPivotPoint = [];
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for k = 1:size(pp,1)
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x = pp(k,1);
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cy = pp(k,2);
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dx = cpSection(k*2+1,1) - cpSection(k*2-1,1);
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dy = cpSection(k*2+1,2) - cpSection(k*2-1,2);
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if dx == 0
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newPivotPoint = [newPivotPoint; [x cy-halfCharH x cy+halfCharH]];
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continue;
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end
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rad = -atan2(dy,dx);
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c = halfCharH*cos(rad);
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s = halfCharH*sin(rad);
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newPivotPoint = [newPivotPoint; [x-s cy-c x+s cy+c]];
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end
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% get edge points to cover character heatmaps
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isSppFound = false;
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isEppFound = false;
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gradS = (pp(2,2)-pp(1,2))/(pp(2,1)-pp(1,1)) + (pp(3,2)-pp(2,2))/(pp(3,1)-pp(2,1));
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gradE = (pp(end-1,2)-pp(end,2))/(pp(end-1,1)-pp(end,1)) + (pp(end-2,2)-pp(end-1,2))/(pp(end-2,1)-pp(end-1,1));
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for r = 0.5:rStep:rMax
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dx = 2 * halfCharH * r;
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if ~isSppFound
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lineImg = uint8(zeros(size(wordLabel)));
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dy = gradS * dx;
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p = newPivotPoint(1,:) - [dx dy dx dy];
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lineImg = insertShape(lineImg,'Line',[p(1) p(2) p(3) p(4)]);
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if (sum(wordLabel & lineImg,'all') == 0) || r+2 * rStep >= rMax
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spp = p;
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isSppFound = true;
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end
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end
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if ~isEppFound
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lineImg = uint8(zeros(size(wordLabel)));
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dy = gradE * dx;
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p = newPivotPoint(end,:) + [dx dy dx dy];
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lineImg = insertShape(lineImg,'Line',[p(1) p(2) p(3) p(4)]);
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if (sum(wordLabel & lineImg,'all') == 0) || r+2 * rStep >= rMax
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epp = p;
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isEppFound = true;
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end
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end
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if isSppFound && isEppFound
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break;
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end
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end
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% pass if boundary of polygon is not found
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if ~(isSppFound&&isEppFound)
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polys = [polys;NaN([1 28])];
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continue;
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end
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% make final polygon
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poly = [];
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poly = [poly warpCoord(Minv,[spp(1),spp(2)])];
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for l = 1:size(newPivotPoint,1)
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p = newPivotPoint(l,:);
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poly = [poly warpCoord(Minv,[p(1),p(2)])];
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end
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poly = [poly warpCoord(Minv,[epp(1),epp(2)])];
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poly = [poly warpCoord(Minv,[epp(3),epp(4)])];
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for l = length(newPivotPoint):-1:1
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p = newPivotPoint(l,:);
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poly = [poly warpCoord(Minv,[p(3) p(4)])];
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end
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poly = [poly warpCoord(Minv,[spp(3) spp(4)])];
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% add to final result
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polys = [polys;poly];
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end
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end
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function res = warpCoord(Minv,pt)
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out = Minv * [pt(1) pt(2) 1]';
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res = [out(1)/out(3) out(2)/out(3)];
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end
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‎src/+helper/getQuadBoxes.m‎

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function [nLabels, labels, bboxes, mapper] = getQuadBoxes(textmap, linkmap, textThreshold, linkThreshold, lowText)
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% This function generates Quadrilateral shape bounding boxes.
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% Copyright 2021 The Mathworks, Inc.
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bboxes = [];
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[imgH, imgW] = size(textmap);
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mapper = [];
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% labeling method
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regionScore = imbinarize(textmap,lowText);
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affinityScore = imbinarize(linkmap, linkThreshold);
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textScoreComb = regionScore + affinityScore;
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textScoreComb(textScoreComb>1) = 1;
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textScoreComb(textScoreComb<0) = 0;
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[nLabels, labels, stats] = helper.connectedComponents(textScoreComb,4);
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for k = 1:nLabels
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% size filtering
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sizes = stats(k).Area;
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if sizes < 10
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continue
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end
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% thresholding
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if max(textmap(labels==k)) < textThreshold
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continue
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end
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% make segmentation map
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segmap = zeros(size(textmap));
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segmap(labels==k) = 255;
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segmap(affinityScore==1 & regionScore==0) = 0; % remove link area
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x = ceil(stats(k).BoundingBox(1)); y = ceil(stats(k).BoundingBox(2));
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w = stats(k).BoundingBox(3); h = stats(k).BoundingBox(4);
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niter = fix(sqrt(sizes * min(w, h) / (w * h)) * 2);
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sx = x - niter; ex = x + w + niter + 1;
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sy = y - niter; ey = y + h+ niter + 1;
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% boundary check
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if sx < 1
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sx = 1;
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end
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if sy < 1
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sy = 1;
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end
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if ex >= imgW
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ex = imgW;
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end
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if ey >= imgH
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ey = imgH;
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end
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kernel = strel('rectangle',[niter + 1, niter + 1]);
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segmap(sy:ey, sx:ex) = imdilate(segmap(sy:ey, sx:ex), kernel);
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% make box
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[i j] = find(segmap~=0);
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indices = [i j];
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npContours = transpose(circshift((indices'), 1, 1));
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bb = helper.minBoundingBox(npContours');
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% align diamond-shape
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w = norm(bb(:,1) - bb(:,2));
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h = norm(bb(:,2) - bb(:,3));
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boxRatio = max(w, h) / (min(w, h) + 1e-5);
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if abs(1 - boxRatio) <= 0.1
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l = min(npContours(:,1)); r = max(npContours(:,1));
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t = min(npContours(:,2)); b = max(npContours(:,2));
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bb = [l t; r t;r b; l b];
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bb = transpose(bb);
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end
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% make clock-wise order
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[~,startidx] = min(sum(bb,1));
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bb = circshift(bb, 4-(startidx-1), 2);
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boxes = reshape(bb,1,8);
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bboxes = [bboxes; boxes];
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mapper = [mapper k]; % list of connected components/labels for valid text areas
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end
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end

‎src/+helper/minBoundingBox.m‎

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function bb = minBoundingBox(X)
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% This function compute a rotated rectangle of the minimum area enclosing
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% the input 2D point set.
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% compute the convex hull (CH is a 2*k matrix subset of X)
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k = convhull(X(1,:),X(2,:));
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CH = X(:,k);
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% compute the angle to test, which are the angle of the CH edges as:
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% "one side of the bounding box contains an edge of the convex hull"
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E = diff(CH,1,2); % CH edges
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T = atan2(E(2,:),E(1,:)); % angle of CH edges (used for rotation)
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T = unique(mod(T,pi/2)); % reduced to the unique set of first quadrant angles
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% create rotation matrix which contains
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% the 2x2 rotation matrices for *all* angles in T
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% R is a 2n*2 matrix
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R = cos( reshape(repmat(T,2,2),2*length(T),2) ... % duplicate angles in T
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+ repmat([0 -pi ; pi 0]/2,length(T),1)); % shift angle to convert sine in cosine
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% rotate CH by all angles
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RCH = R*CH;
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% compute border size [w1;h1;w2;h2;....;wn;hn]
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% and area of bounding box for all possible edges
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bsize = max(RCH,[],2) - min(RCH,[],2);
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area = prod(reshape(bsize,2,length(bsize)/2));
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% find minimal area, thus the index of the angle in T
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[~,i] = min(area);
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% compute the bound (min and max) on the rotated frame
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Rf = R(2*i+[-1 0],:); % rotated frame
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bound = Rf * CH; % project CH on the rotated frame
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bmin = min(bound,[],2);
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bmax = max(bound,[],2);
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% compute the corner of the bounding box
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Rf = Rf';
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bb(:,4) = bmax(1)*Rf(:,1) + bmin(2)*Rf(:,2);
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bb(:,3) = bmin(1)*Rf(:,1) + bmin(2)*Rf(:,2);
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bb(:,2) = bmin(1)*Rf(:,1) + bmax(2)*Rf(:,2);
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bb(:,1) = bmax(1)*Rf(:,1) + bmax(2)*Rf(:,2);

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