function newFilename = reorganizeVectors(filenameAbs, filenameRel);
% Version 0.1, Feb 2006.
% This code is copyrighted by Ashutosh Saxena, Stanford University
% It is available for non-commercial use only. For commericial use, please
% contact the authors.
% Any publication or report resulting from Use of this code, should cite:
% Learning Depth from Single Monocular Images, Ashutosh Saxena, Sung H. Chung, Andrew Y. Ng, NIPS 2005.
% 3-D Depth Reconstruction from a Single Still Image, Ashutosh Saxena, Sung H. Chung, Andrew Y. Ng, To appear in IJCV 2007.
% For more info and dataset, visit: http://ai.stanford.edu/~asaxena/learningdepth/
% For a better version of the algorithm, also visit: 
% http://ai.stanford.edu/~asaxena/reconstruction3d/

% For learning purposes, the features / depths are needed in the vector format; while
% for viewing they need to be in matrix (to see it as a image).
% This code converts between them.
% Used somewhere in the learnig code


load(filenameAbs);

global nThetaStep nGridRow nGridCol
configurationFile;

nImages = size(dumbDepthVector,1) / nThetaStep / nGridCol;


dumbDepthVector = reshape(dumbDepthVector, [nThetaStep nGridCol nImages nGridRow]);
dumbDepthVector = reshape(permute(dumbDepthVector(:,:,:,1:nThetaStep:nGridRow), [1 4 2 3]), ...
                                [2*ceil(nGridRow/2) nGridCol nImages]);
dumbDepthVector = dumbDepthVector(1:nGridRow,:,:);

predictedDepthVector = reshape(predictedDepthVector, [nThetaStep nGridCol nImages nGridRow]);
predictedDepthVector = reshape(permute(predictedDepthVector(:,:,:,1:nThetaStep:nGridRow), [1 4 2 3]), ...
                                [2*ceil(nGridRow/2) nGridCol nImages]);
predictedDepthVector = predictedDepthVector(1:nGridRow,:,:);

predictedAbsoluteVarianceVector = reshape(predictedAbsoluteVarianceVector, [nThetaStep nGridCol nImages nGridRow]);
predictedAbsoluteVarianceVector = reshape(permute(predictedAbsoluteVarianceVector(:,:,:,1:nThetaStep:nGridRow), [1 4 2 3]), ...
                                [2*ceil(nGridRow/2) nGridCol nImages]);
predictedAbsoluteVarianceVector = predictedAbsoluteVarianceVector(1:nGridRow,:,:);

dumbDepthVector = reshape( permute(dumbDepthVector, [2 3 1]), nGridCol*nImages,nGridRow);
predictedDepthVector = reshape( permute(predictedDepthVector, [2 3 1]), nGridCol*nImages,nGridRow);
predictedAbsoluteVarianceVector = reshape( permute(predictedAbsoluteVarianceVector, [2 3 1]), nGridCol*nImages,nGridRow);



if length(filenameRel) > 0
    load(filenameRel);
    predictedDepthVectorX = reshape(predictedDepthVectorX, [nThetaStep nGridCol nImages nGridRow]);
    predictedDepthVectorX = reshape(permute(predictedDepthVectorX(:,:,:,1:nThetaStep:nGridRow), [1 4 2 3]), ...
                                [2*ceil(nGridRow/2) nGridCol nImages]);
    predictedDepthVectorX = predictedDepthVectorX(1:nGridRow,:,:);

    predictedDepthVectorY = reshape(predictedDepthVectorY, [nThetaStep nGridCol nImages nGridRow]);
    predictedDepthVectorY = reshape(permute(predictedDepthVectorY(:,:,:,1:nThetaStep:nGridRow), [1 4 2 3]), ...
                                [2*ceil(nGridRow/2) nGridCol nImages]);
    predictedDepthVectorY = predictedDepthVectorY(1:nGridRow,:,:);

    size(predictedDepthVectorX_2);
    predictedDepthVectorX_2 = reshape(predictedDepthVectorX_2, [nThetaStep nGridCol nImages nGridRow]);
    predictedDepthVectorX_2 = reshape(permute(predictedDepthVectorX_2(:,:,:,1:nThetaStep:nGridRow), [1 4 2 3]), ...
                                [2*ceil(nGridRow/2) nGridCol nImages]);
    predictedDepthVectorX_2 = predictedDepthVectorX_2(1:nGridRow,:,:);

    predictedDepthVectorY_2 = reshape(predictedDepthVectorY_2, [nThetaStep nGridCol nImages nGridRow]);
    predictedDepthVectorY_2 = reshape(permute(predictedDepthVectorY_2(:,:,:,1:nThetaStep:nGridRow), [1 4 2 3]), ...
                                [2*ceil(nGridRow/2) nGridCol nImages]);
    predictedDepthVectorY_2 = predictedDepthVectorY_2(1:nGridRow,:,:);


%predictedDepthVectorX_5 = reshape(predictedDepthVectorX_5, [nThetaStep nGridCol nImages nGridRow]);
%predictedDepthVectorX_5 = reshape(permute(predictedDepthVectorX_5(:,:,:,1:nThetaStep:nGridRow), [1 4 2 3]), ...
%                                [2*ceil(nGridRow/2) nGridCol nImages]);
%predictedDepthVectorX_5 = predictedDepthVectorX_5(1:nGridRow,:,:);

%predictedDepthVectorY_5 = reshape(predictedDepthVectorY_5, [nThetaStep nGridCol nImages nGridRow]);
%predictedDepthVectorY_5 = reshape(permute(predictedDepthVectorY_5(:,:,:,1:nThetaStep:nGridRow), [1 4 2 3]), ...
%                                [2*ceil(nGridRow/2) nGridCol nImages]);
%predictedDepthVectorY_5 = predictedDepthVectorY_5(1:nGridRow,:,:);


%residualAbsError;                   
%residualRelErrorX;                  
%residualRelErrorX_2;                
%residualRelErrorX_5;                
%residualRelErrorY;                  
%residualRelErrorY_2;                
%residualRelErrorY_5;
    predictedDepthVectorX = reshape( permute(predictedDepthVectorX, [2 3 1]), nGridCol*nImages,nGridRow);
    predictedDepthVectorY = reshape( permute(predictedDepthVectorY, [2 3 1]), nGridCol*nImages,nGridRow);

    predictedDepthVectorX_2 = reshape( permute(predictedDepthVectorX_2, [2 3 1]), nGridCol*nImages,nGridRow);
    predictedDepthVectorY_2 = reshape( permute(predictedDepthVectorY_2, [2 3 1]), nGridCol*nImages,nGridRow);

else
    predictedDepthVectorX = 0;    predictedDepthVectorY = 0;
    
    predictedDepthVectorX_2 = 0;  predictedDepthVectorY_2 = 0;
    residualRelErrorX = 0;        residualRelErrorY = 0;
    residualRelErrorX_2 = 0;      residualRelErrorY_2 = 0;
end
%predictedDepthVectorX_5 = reshape( permute(predictedDepthVectorX_5, [2 3 1]), nGridCol*nImages,nGridRow);
%predictedDepthVectorY_5 = reshape( permute(predictedDepthVectorY_5, [2 3 1]), nGridCol*nImages,nGridRow);


newFilename = ['reorganized_' filenameAbs];
save(newFilename, 'predictedDepthVector', 'predictedDepthVectorX', 'predictedDepthVectorY', ...
        'predictedDepthVectorX_2', 'predictedDepthVectorY_2', 'actualDepthMap', 'dumbDepthVector', ...
        'residualRelErrorX', 'residualRelErrorY', 'residualRelErrorX_2', 'residualRelErrorY_2', ...
        'residualAbsError', 'predictedAbsoluteVarianceVector');
disp('Reorganization done.......');