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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;
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