[img A g]= depth_examplea();
A1=mean(mean(img,3));
G=cast(g,'single');
size(g)

level=graythresh(g);
BW2 = edge(g,'Prewitt');

[L,Centers] = imsegkmeans(g,4);
B = labeloverlay(g,L);
imshow(B);
title('Labeled Image');
BW2 = bwareaopen(BW2, 20); % Remove blobs smaller than 40.

   Ibw1 = imfill(BW2,'holes');
binaryImage = bwareafilt(Ibw1, 1); % Extract largest blob only.

info = regionprops(binaryImage,'Boundingbox')
imshow(binaryImage)

hold on

for k = 1 : length(info)
     BB = info(k).BoundingBox; rectangle('Position', [BB(1),BB(2),BB(3),BB(4)],'EdgeColor','r','LineWidth',2) ;

     X1(:,k)=[BB(1)];
     X2(:,k)=[BB(2)];
     X3(:,k)=[BB(3)+10];
     X4(:,k)=[BB(4)+10];
     X=transpose([X1;X2;X3;X4]);

     
end

IExpandedBBoxes = insertShape(img,'Rectangle',X,'LineWidth',3);

overlapRatio = bboxOverlapRatio(X, X);
n = size(overlapRatio,1); 
overlapRatio(1:n+1:n^2) = 0;
g1 = graph(overlapRatio);
componentIndices = conncomp(g1);
% Merge the boxes based on the minimum and maximum dimensions.
xmin = accumarray(componentIndices', X1, [], @min);
ymin = accumarray(componentIndices', X2, [], @min);
xmax = accumarray(componentIndices', X3, [], @max);
ymax = accumarray(componentIndices', X4, [], @max);

textBBoxes = [xmin ymin xmax ymax];
xcor=[ textBBoxes(1) textBBoxes(3) textBBoxes(3) textBBoxes(1) textBBoxes(1)];
ycor=[ textBBoxes(2) textBBoxes(2) textBBoxes(4) textBBoxes(4) textBBoxes(2)];

ITextRegion = insertShape(img, 'Rectangle', textBBoxes,'LineWidth',3);
 s= [regionprops(ITextRegion,'centroid')];
 s1=reshape(cell2mat(struct2cell(s)),3,[])';
s1x=s1(:,1);
s1y=s1(:,2);

xcenter=round(xmin +(xmax/2))
ycenter=round(ymin+(ymax/2))
str = strcat('<HI,1,2,3,',num2str(xcenter),',',num2str(ycenter),'>') 

imshow(ITextRegion)


figure


%A2=mean(A1(1:424));
%A3=mean(A1(425:848));
%A4=[A2 A3];
function    [img A g]=depth_examplea();
    % Make Pipeline object to manage streaming
    pipe = realsense.pipeline();
    % Make Colorizer object to prettify depth output
    colorizer = realsense.colorizer();

    % Start streaming on an arbitrary camera with default settings
    profile = pipe.start();

    % Get streaming device's name
    dev = profile.get_device();
    name = dev.get_info(realsense.camera_info.name);

    % Get frames. We discard the first couple to allow
    % the camera time to settle
    for i = 1:5
        fs = pipe.wait_for_frames();
    end
    
    % Stop streaming
    pipe.stop();
    A=[];
    % Select depth frame
    depth = fs.get_depth_frame();
    % Colorize depth frame
    color = colorizer.colorize(depth);

    % Get actual data and convert into a format imshow can use
    % (Color data arrives as [R, G, B, R, G, B, ...] vector)
    data = color.get_data();
    img = permute(reshape(data',[3,color.get_width(),color.get_height()]),[3 2 1]);
    img(:,1:100,:)=[];
    img(:,840:end,:)=[];
    img(460:480,:,:)=[];
    % Display image
    imshow(img);
    title(sprintf("Colorized depth frame from %s", name));
    A(:,:,:)=img(:,:,:);
    g=rgb2gray(img);

end