/normxcorr/trunk

function [validx, validy, displx, disply]=RTCorrCode(grid_x,grid_y,Firstimagename,ImageFolder)

% Real time Correlation Code

%

% Written by Chris

% OPTIMIZE parameter is controlling which optimizations should be used. 

% <3 - The original version, no optimizations

%  3 - Most of computations are performed on NVidia card

%  4 - Optimize FFT sizes for better performance (affects precision)

%  5 - Load images in C code

OPTIMIZE = 4;

CORRSIZE = 15;	

PRECISION = 1000;

warning off Images:initSize:adjustingMag

if OPTIMIZE > 2

    hwid = normxcorr_hw();

    if hwid > 0

    else

	OPTIMIZE = 0;

    end

else

    hwid = 0;

end

if OPTIMIZE > 2

    RTselection = menu(sprintf('End processing by end.txt or by last image?'),...

	'Stop with end.txt','Stop with image check','Exit');

    if RTselection==1

    end

    if RTselection==2

    end

    if RTselection==3

        if hwid > 0

	    normxcorr_hw(hwid);

	end

	return

    end

end

% Filename

if exist('Firstimagename')==0

    [Firstimagename ImageFolder]=uigetfile('*.tif','Open First Image');

end

if ~isempty(Firstimagename)

% Get the number of image name

letters=isletter(Firstimagename);

Pointposition=findstr(Firstimagename,'.');

Firstimagenamesize=size(Firstimagename);

counter=Pointposition-1;

counterpos=1;

letterstest=0;

while letterstest==0

    letterstest=letters(counter);

    if letterstest==1

        break

    end

    Numberpos(counterpos)=counter;

    counter=counter-1;

    counterpos=counterpos+1;

    if counter==0

        break

    end

end

Filename_first = Firstimagename(1:min(Numberpos)-1);

Firstfilenumber=Firstimagename(min(Numberpos):max(Numberpos));

Lastname_first = Firstimagename(max(Numberpos)+1:Firstimagenamesize(1,2));

Firstfilenumbersize=size(Firstfilenumber);

onemore=10^(Firstfilenumbersize(1,2));

filenamelist(1,:)=Firstimagename;

h=figure;

if exist('grid_x')==0

    fpstest=1;

    Filelist=[Firstimagename;Firstimagename];

    while fpstest==1

        [grid_x,grid_y]=grid_generator(Firstimagename,ImageFolder);

	if OPTIMIZE > 2

	    ncp = prod(size(grid_x));

	    err = normxcorr_hw(hwid, 1, ncp, CORRSIZE, PRECISION, OPTIMIZE);

	else

	    err = 0;

	end

	if err == 0

	    if OPTIMIZE > 2

		base_points_x=single(grid_x);

		base_points_y=single(grid_y);

		normxcorr_hw(hwid, 3, base_points_x, base_points_y);

		if OPTIMIZE > 4

		    normxcorr_hw(hwid, 4, strcat(imagedir, Firstimagename));

		else

		    base = uint8(mean(double(imread([ImageFolder, Firstimagename])),3));

		    normxcorr_hw(hwid, 4, base);

		end	

		normxcorr_hw(hwid, 12, base_points_x, base_points_y);

	    end

	    [processingtime]=fpstestfunc(hwid,OPTIMIZE,grid_x,grid_y,Filelist,ImageFolder);

    	    fpstest = menu(sprintf(['Processing the selected grid will allow ' , num2str(1/processingtime),' frames per second' ]),'Try again','Use the grid');

    	    if fpstest==1

        	clear grid_x; clear grid_y;

    	    end

	else

	    ASelection = menu(sprintf('CUDA initialization failed?'),...

	'Retry another grid','Continue in software mode','Exit');

	    if Aselection==1

		fptest = 1;

	    end

	    if Aselection==2

		fptest = 0;

		normxcorr_hw(hwid);

		OPTIMIZE = 0;

	    end

	    if Aselection==3

		return

	    end

	end

    end

end

if OPTIMIZE < 3

    [validx, validy, displx, disply] = RTCorrCode_orig(grid_x, grid_y, Firstimagename, ImageFolder)

    return

end

Firstfilenumber=str2num(Firstfilenumber);

u=1+onemore+Firstfilenumber;

ustr=num2str(u);

filenamelist(2,:)=[Filename_first ustr(2:Firstfilenumbersize(1,2)+1) Lastname_first];

numberofimages=2;

counter=1;

input_points_x=single(grid_x);

input_points_y=single(grid_y);

normxcorr_hw(hwid, 12, input_points_x, input_points_y);

fit_options = optimset('Display', 'off');

numberofmarkers=max(size(grid_x))*min(size(grid_x));

validx(:,1)=reshape(grid_x,[],1);

displx=zeros(numberofmarkers,1);

validy(:,1)=reshape(grid_y,[],1);

disply=zeros(numberofmarkers,1);

tic;

while exist([ImageFolder, 'end.txt'],'file') ==0;

    pause(0.01);

    if exist([ImageFolder, filenamelist((counter+1),:)],'file') ==2;

%        warning(['# Processed Images: ', num2str(numberofimages-1),'; # markers:',num2str(numberofmarkers), '; Processing Image: ',filenamelist(counter+1,:)]);

	if OPTIMIZE > 4

	    normxcorr_hw(hwid, 13, strcat(ImageFolder, filenamelist((counter+1),:)));

	    input_correl = normxcorr_hw(hwid, 14);

	else

	    input = uint8(mean(double(imread([ImageFolder, filenamelist((counter+1),:)])),3));

	    normxcorr_hw(hwid, 13, input);

	    input_correl = normxcorr_hw(hwid, 14);

	end

	input_correl_x=double(input_correl(:,1));

        input_correl_y=double(input_correl(:,2));

        validx(:,counter+1)=input_correl_x;                                                     % lets save the data

        savelinex=input_correl_x';

    	dlmwrite([ImageFolder, 'resultsimcorrx.txt'], savelinex , 'delimiter', '\t', '-append');       % Here we save the result from each image; if you are desperately want to run this function with e.g. matlab 6.5 then you should comment this line out. If you do that the data will be saved at the end of the correlation step - good luck ;-)

    	validy(:,counter+1)=input_correl_y;

	saveliney=input_correl_y';

    	dlmwrite([ImageFolder, 'resultsimcorry.txt'], saveliney , 'delimiter', '\t', '-append');

        subplot(2,2,1);

        imshow([ImageFolder, filenamelist(counter+1,:)]);

        hold on;

        plot(grid_x,grid_y,'g+');

        plot(input_correl_x,input_correl_y,'r+');

        hold off;

        drawnow;

        displx(:,counter+1)=validx(:,counter+1)-validx(:,1);

        disply(:,counter+1)=validy(:,counter+1)-validy(:,1);

        subplot(2,2,2);

        xdata=validx(:,counter+1);

        ydata=displx(:,counter+1);

        if counter==1

            x(1)=0;

            x(2)=0;

        end

        [x,resnormx,residual,exitflagx,output]  = lsqcurvefit(@linearfit, [x(1) x(2)], xdata, ydata, [], [], fit_options);

        plot(xdata,ydata,'.');

        hold on;

        ydatafit=x(1)*xdata+x(2);

        plot(xdata,ydatafit,'r');

        hold off;

        xlabel('x-pos [pixel]');

        ylabel('x-displ [pixel]');

        title('x displ. versus x pos. in [pixel]');

        slopex(counter,:)=[i x(1) x(2)];

        subplot(2,2,4);

        xdata=validy(:,counter+1);

        ydata=disply(:,counter+1);

        if counter==1

            y(1)=0;

            y(2)=0;

        end

        [y,resnormx,residual,exitflagx,output]  = lsqcurvefit(@linearfit, [y(1) y(2)], xdata, ydata, [], [], fit_options);

        plot(xdata,ydata,'.g');

        hold on;

        ydatafit=y(1)*xdata+y(2);

        plot(xdata,ydatafit,'r');

        hold off

        xlabel('y-pos [pixel]')

        ylabel('y-displ [pixel]')

        title('y displ. versus y pos. in [pixel]');

        slopey(counter,:)=[i y(1) y(2)];

        subplot(2,2,3);

        plot(slopex(:,2),'-b');

        hold on;

        plot(slopey(:,2),'-g');

        hold off;

        xlabel('Image # [ ]');

        ylabel('x- and y-strain [ ]');

        title('Strain in x and y direction versus Image #');

        counter=counter+1;

        u=1+u;

        ustr=num2str(u);

        filenamelist(counter+1,:)=[Filename_first ustr(2:Firstfilenumbersize(1,2)+1) Lastname_first];

        [numberofmarkers numberofimages]=size(validx);

        if RTselection==2

            if exist([ImageFolder, filenamelist((counter+1),:)],'file') ==0;

                save ([ImageFolder, 'validx.dat'], 'validx', '-ascii', '-tabs');

                save ([ImageFolder, 'validy.dat'], 'validy', '-ascii', '-tabs');

                %warning('Last image detected, RTCorrCode stopped');

		normxcorr_hw(hwid);

                return

            end

        end

        subplot(2,2,1),title(['# Processed Images: ', num2str(numberofimages-1),'; fps: ', num2str((numberofimages-1)/toc),'; # markers:',num2str(numberofmarkers), '; Waiting for Image: ',filenamelist(counter+1,:)]);

    end

end

normxcorr_hw(hwid);

save ([ImageFolder, 'validx.dat'], 'validx', '-ascii', '-tabs');

save ([ImageFolder, 'validy.dat'], 'validy', '-ascii', '-tabs');

msgboxwicon=msgbox('end.txt file detected, RTCorrCode stopped','Processing stopped!');

%warning('end.txt file detected, RTCorrCode stopped');

end

%----------------------------------

%

function [processingtime]=fpstestfunc(hwid, OPTIMIZE, grid_x, grid_y, filenamelist, ImageFolder)

tic;

if hwid > 0

    if OPTIMIZE > 4

	normxcorr_hw(hwid, 13, strcat(ImageFolder, filenamelist(2,:)));

	input_correl = normxcorr_hw(hwid, 14);

    else

	input = uint8(mean(double(imread([ImageFolder, filenamelist(2,:)])),3));

	normxcorr_hw(hwid, 13, input)

	input_correl = normxcorr_hw(hwid, 14);

    end

    input_correl_x=double(input_correl(:,1));

    input_correl_y=double(input_correl(:,2));

else

    input_points_x=grid_x;

    base_points_x=grid_x;

    input_points_y=grid_y;

    base_points_y=grid_y;

    base = uint8(mean(double(imread([ImageFolder, filenamelist(1,:)])),3));            % read in the base image ( which is always  image number one. You might want to change that to improve correlation results in case the light conditions are changing during the experiment

    input = uint8(mean(double(imread([ImageFolder, filenamelist(2,:)])),3));       % read in the image which has to be correlated

    input_points_for(:,1)=reshape(input_points_x,[],1);         % we reshape the input points to one row of values since this is the shape cpcorr will accept

    input_points_for(:,2)=reshape(input_points_y,[],1);

    base_points_for(:,1)=reshape(base_points_x,[],1);

    base_points_for(:,2)=reshape(base_points_y,[],1);

    input_correl(:,:)=cpcorr(input_points_for, base_points_for, input, base);           % here we go and give all the markers and images to process to cpcorr.m which ic a function provided by the matlab image processing toolbox

    input_correl_x=input_correl(:,1);                                       % the results we get from cpcorr for the x-direction

    input_correl_y=input_correl(:,2);                                       % the results we get from cpcorr for the y-direction

end

processingtime=toc;