evawilson asked . 2020-05-27

How to get the coordinates of each room in a floor plan image through object identification method?

function [bbox_loc,sign_objects,index1,st,furniture]=classify_objects_test1(I1)
%  clear all;
%  clc;
%  close all;
I_initial=imread("C:\\Users\\User\\Desktop\\tkinter_codes\\floorplans\\ROBIN\\Dataset_3roomsmall\\Cat1_1.jpg");

%I_initial = imread('room_4.png');
I=I_initial;
imshow(I);
SE = strel('square',10);
I = imdilate(I,SE);
SE = strel('square',10);
I = imerode(I,SE);
wall_image=I;

wall = I;
I=I_initial;
wall=im2bw(wall);
imshow(wall);

I=im2bw(I);
I=imcomplement(I);
wall = imcomplement(wall);
I=I-wall;
% imshow(I);
I=imcomplement(I);
SE = strel('square',1);
IM2 = imdilate(I,SE);

IM2 = I;
IM2 = imerode(IM2,SE);

imwrite(IM2,'fl_0sym.tif');


se1=strel('square',8);
intm1=imerode(IM2,se1);
se2=strel('square',4);
intm2=imdilate(intm1,se2);
intm3=imdilate(intm2,se2);
imwrite(intm3,'fl_0sym1.tif');
I = imread('fl_0sym1.tif');
I = imcomplement(I);

J = imfill(I);
J = ~J;

imwrite(J,'blb_0_1.jpg');


figure=I_initial;
[m,n] = size(figure);
figure1 = figure(:,:,[1 1 1]);
figure = im2bw(figure);
[m,n] = size(figure);
image = imread('blb_0_1.jpg');
BW = im2bw(image);
BW = imresize(BW,[m,n]);
BW = ~BW;


%for 4,1,9,8
 SE = strel('square',10);
 BW = imdilate(BW,SE);

%% figure;imshow(BW);
st = regionprops(BW,'BoundingBox');
 shape.Inserter = vision.ShapeInserter('LineWidth',4,'BorderColor','Custom','CustomBorderColor',uint8([255 0 0]));
 
str_ele=strel('disk',1,0);
 for k = 1:length(st)
%  k=1;       
%         for k = 1:1
thisBB = st(k).BoundingBox;
%figure1 = step(shape.Inserter,figure1,bbox_loc{k});
thisBBarea=thisBB(3)*thisBB(4);
if thisBB(3)>20 &&  thisBB(4)>20 
rectangle = int32([thisBB(1),thisBB(2),thisBB(3),thisBB(4)]);


end
 if(thisBBarea >870)
bbox_loc{k}=rectangle;
 
 crop_I_new=imcrop(figure1,rectangle);
 crop_I_new_gray=rgb2gray(crop_I_new);
 crop_I=im2bw(crop_I_new_gray,0.7);
%   figure;imshow(crop_I);
signature{k}=signature_find(crop_I);
if isempty(signature{k})
   
    signature{k}=[99999,99999,99999];
end
    
  figure1 = step(shape.Inserter,figure1,bbox_loc{k});
 end
end     
signature=signature(~cellfun('isempty',signature)); 

save('signature.mat','signature');
signature=load('signature.mat');
sign_objects=load('sign_object2');
for i=1:length(signature.signature)
    for j=1:length(sign_objects.sign_object2)

diff{i,j}=abs(signature.signature{1,i}-sign_objects.sign_object2{j,1}.count);

    
    end
       

end
for(i=1:size(diff,1))
    for(j=1:size(diff,2))
        if(sign_objects.sign_object2{j,1}.count(3)>1000)
            temp1(i,j)=diff{i,j}(1)+diff{i,j}(2);
        else
            temp1(i,j)=diff{i,j}(1)+diff{i,j}(2)+diff{i,j}(3);
        end
    end
end
for(i=1:size(temp1,1))
[temp1_min(i),index1(i)]=min(temp1(i,:));  
disp(sign_objects.sign_object2{index1(i),2});
  furniture{i,1}=sign_objects.sign_object2{index1(i),2}
  figure;imshow(figure1);
bbox_loc=bbox_loc(~cellfun('isempty',bbox_loc)); 
end

for k = 1:length(bbox_loc)
     H= text( double(bbox_loc{k}(1)),double(bbox_loc{k}(2)),sign_objects.sign_object2{index1(k),2});
           set(gcf,'DefaultTextColor','blue')
end
% for i=1:size(diff,1)
%      for j=1:size(diff,2)
% 
%         temp1(i,j)=(diff{i,j}(1));
%         temp2(i,j)=(diff{i,j}(2));
%         temp3(i,j)=(diff{i,j}(3));
% 
% 
%      end
%   [temp1_min(i),index1(i)]=min(temp1(i,:));  
%   disp(sign_objects.sign_object1{index1(i),2});
%   furniture{i,1}=sign_objects.sign_object1{index1(i),2}
% end

This is the image with only walls.

deep learning , matlab