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test.m
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test.m
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image_fl=getAllFiles('E:/ML PROJECT/Shoulder Pain dataset/cohn-kanade-images/');
imgNo=0;
auNo=0;
imageNo=1;
for idx = 1:4000
lmPath=[];
lmPath='E:\ML PROJECT\Shoulder Pain dataset\Landmarks';
facsPath='E:\ML PROJECT\Shoulder Pain dataset\FACS';
imgPath = image_fl{idx};
[imgPathstr,imgName,imgExt] = fileparts(imgPath) ;
facsName=strcat(imgName,'_facs.txt');
name=strcat(imgName,'_landmarks.txt');
path = strsplit(imgPathstr,'cohn-kanade-images');
facsPath=strcat(facsPath,path{2},'\',facsName);
lmPath=strcat(lmPath,path{2},'\',name);
if(imgExt=='.png')
if exist(facsPath, 'file') == 2
Seq{imageNo,1} = imread(imgPath);
auList=importdata(facsPath);
Seq{imageNo,8}=auList;
%lmPath=strcat(lmPath,path(2),'\',name);
Seq{imageNo,2} = importdata(lmPath);
lmPoints=Seq{imageNo,2};
Seq{imageNo,3} ={ (lmPoints(37,1)+lmPoints(40,1))/2 , (lmPoints(37,2)+lmPoints(40,2))/2};
Seq{imageNo,4} ={ (lmPoints(43,1)+lmPoints(46,1))/2 , (lmPoints(43,2)+lmPoints(46,2))/2};
leftEyeCenter=Seq{imageNo,3};
rightEyeCenter=Seq{imageNo,4};
eyeDist=norm([abs(leftEyeCenter{1,1}-rightEyeCenter{1,1}),abs(leftEyeCenter{1,2}-rightEyeCenter{1,2})]);
Seq{imageNo,5}=lmPoints*300/eyeDist;
normLM = Seq{imageNo,5};
for i = 1:68
for j = 1:68
if(i>j)
distPoints(i,j) = norm([abs(normLM(i,1)-normLM(j,1)),abs(normLM(i,2)-normLM(j,2))]);
end
end
end
Seq{imageNo,6}=distPoints;
tri = delaunayTriangulation(normLM(:,1),normLM(:,2));
%triplot(tri);
p = tri.Points;
triangles = tri.ConnectivityList;
for i = 1:68
angleAtLM{i,1}=[];
ti = vertexAttachments(tri,i);
x1=p(i,1);y1=p(i,2);
attachedTri=ti{1};
for j = 1:length(attachedTri)
for k = 1:length(triangles)
if(attachedTri(j) == k)
TI=triangles(k,:);
if(triangles(k,1)==i)
x2 = p(triangles(k,2),1);
y2 = p(triangles(k,2),2);
x3 = p(triangles(k,3),1);
y3 = p(triangles(k,3),2);
elseif(triangles(k,2)==i)
x2 = p(triangles(k,1),1);
y2 = p(triangles(k,1),2);
x3 = p(triangles(k,3),1);
y3 = p(triangles(k,3),2);
elseif(triangles(k,3)==i)
x2 = p(triangles(k,2),1);
y2 = p(triangles(k,2),2);
x3 = p(triangles(k,1),1);
y3 = p(triangles(k,1),2);
end
%Area = polyarea([x1,x2,x3],[y1,y2,y3])
A1 = atan2(abs((x2-x1)*(y3-y1)-(x3-x1)*(y2-y1)),(x2-x1)*(x3-x1)+(y2-y1)*(y3-y1));
A1 = A1*180/pi ;
P1 = [x1,y1];P2=[x2,y2];P3=[x3,y3];
angleAtLM{i,1}=[angleAtLM{i,1} A1];
%a1 = atan2(2*Area,dot(P2-P1,P3)-P1))
end
end
end
end
Seq{imageNo,7}=angleAtLM;
%angleAtLM(:,:)=[];
Xij=[];
j=0;
for i=1:68
for k=1:67
if(distPoints(i,k)~=0)
Xij=[Xij distPoints(i,k)];
j=j+1;
end
end
end
%gij(imageNo,:)=gabor_filter(imgPath,lmPath);
imageNo
XijAll(imageNo,:)=Xij;
imageNo=imageNo+1;
end
Xij=[];
end
Xij=[];
end
for p=1 : 68
for q=1:imageNo-1
a{q,1}=Seq{q,7}{p,1};
end
sz = cellfun(@(x)size(x,2), a);
minLength = min(sz);
b = cell2mat(cellfun(@(x)x(1:minLength), a, 'uniformoutput', false))';
b=b';
for q=1:imageNo-1
Seq{q,7}{p,1}=[];
Seq{q,7}{p,1}=b(q,:);
end
end
for q=1:imageNo-1
angleVect=[];
for p=1 : 68
angleVect=[angleVect Seq{q,7}{p,1}];
end
Zij(q,:)=[XijAll(q,:) angleVect];
%Zij(q,:)=[XijAll(q,:) angleVect gij(q,:)];
end
subplot(2,2,1),imshow(imread(imgPath));
subplot(2,2,2),hold on
subplot(2,2,2),axis ij;
subplot(2,2,2),triplot(tri);
subplot(2,2,2),triplot(tri(ti{:},:),normLM(:,1),normLM(:,2),'Color','r') % vertex 5 (in red)
subplot(2,2,2),hold off;
trainLabel=[];
facs2DArray=zeros(43,6);
facs=[];
sortedZij=[];
C=0;
maxAu=0;
maxInt=0;
classSamples=zeros(43,1);
for auNo=1:43
for intensityNo=0:5
for imageNo=1:size(Seq)
temp=Seq{imageNo,8};
for auPresent=1:size(temp)
if temp(auPresent,1)==auNo
if temp(auPresent,2)==intensityNo
sortedZij=[sortedZij;Zij(imageNo,:)];
facs2DArray(auNo,intensityNo+1)=facs2DArray(auNo,intensityNo+1)+1;
classSamples(auNo,1)=classSamples(auNo,1)+1;
if temp(auPresent,1)>maxAu
maxAu=temp(auPresent,1);
end
if temp(auPresent,2)>maxInt
maxInt=temp(auPresent,2);
end
end
end
end
end
end
facs=[facs facs2DArray(auNo,:)];
end