mc2-scripts-and-benchmarks.git - Benchmarks and execution scripts for testing spatial isolation and SMT interference in MC^2

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author	Joshua Bakita <jbakita@cs.unc.edu>	2020-10-24 02:42:55 -0400
committer	Joshua Bakita <jbakita@cs.unc.edu>	2020-10-24 02:42:55 -0400
commit	91ba319fffa36885abc777c54266860f947fed16 (patch)
tree	5c8bb65d040716f88170aa40494b387ca9706722 /SD-VBS/common/c/iTimes.c
parent	e0c5691110f38f63d1955a711fc7f786333bcaad (diff)

Alert to stderr on benchmark deadline miss

Diffstat (limited to 'SD-VBS/common/c/iTimes.c')

0 files changed, 0 insertions, 0 deletions

% Cleaned-up version of init_calib.m fprintf(1,'\nProcessing image %d...\n',kk); eval(['I = I_' num2str(kk) ';']); if exist(['wintx_' num2str(kk)]), eval(['wintxkk = wintx_' num2str(kk) ';']); if ~isempty(wintxkk) & ~isnan(wintxkk), eval(['wintx = wintx_' num2str(kk) ';']); eval(['winty = winty_' num2str(kk) ';']); end; end; fprintf(1,'Using (wintx,winty)=(%d,%d) - Window size = %dx%d\n',wintx,winty,2*wintx+1,2*winty+1); figure(2); image(I); colormap(map); title(['Click on the four extreme corners of the rectangular pattern... Image ' num2str(kk)]); disp('Click on the four extreme corners of the rectangular complete pattern...'); [x,y] = ginput3(4); [Xc,good,bad,type] = cornerfinder([x';y'],I,winty,wintx); % the four corners x = Xc(1,:)'; y = Xc(2,:)'; [y,indy] = sort(y); x = x(indy); if (x(2) > x(1)), x4 = x(1);y4 = y(1); x3 = x(2); y3 = y(2); else x4 = x(2);y4 = y(2); x3 = x(1); y3 = y(1); end; if (x(3) > x(4)), x2 = x(3);y2 = y(3); x1 = x(4); y1 = y(4); else x2 = x(4);y2 = y(4); x1 = x(3); y1 = y(3); end; x = [x1;x2;x3;x4]; y = [y1;y2;y3;y4]; figure(2); hold on; plot([x;x(1)],[y;y(1)],'g-'); plot(x,y,'og'); hx=text((x(4)+x(3))/2,(y(4)+y(3))/2 - 20,'X'); set(hx,'color','g','Fontsize',14); hy=text((x(4)+x(1))/2-20,(y(4)+y(1))/2,'Y'); set(hy,'color','g','Fontsize',14); hold off; % Try to automatically count the number of squares in the grid n_sq_x1 = count_squares(I,x1,y1,x2,y2,wintx); n_sq_x2 = count_squares(I,x3,y3,x4,y4,wintx); n_sq_y1 = count_squares(I,x2,y2,x3,y3,wintx); n_sq_y2 = count_squares(I,x4,y4,x1,y1,wintx); % If could not count the number of squares, enter manually if (n_sq_x1~=n_sq_x2)|(n_sq_y1~=n_sq_y2), disp('Could not count the number of squares in the grid. Enter manually.'); n_sq_x = input('Number of squares along the X direction ([]=10) = '); %6 if isempty(n_sq_x), n_sq_x = 10; end; n_sq_y = input('Number of squares along the Y direction ([]=10) = '); %6 if isempty(n_sq_y), n_sq_y = 10; end; else n_sq_x = n_sq_x1; n_sq_y = n_sq_y1; end; % Enter the size of each square dX = input(['Size dX of each square along the X direction ([]=' num2str(dX_default) 'mm) = ']); dY = input(['Size dY of each square along the Y direction ([]=' num2str(dY_default) 'mm) = ']); if isempty(dX), dX = dX_default; else dX_default = dX; end; if isempty(dY), dY = dY_default; else dY_default = dY; end; % Compute the inside points through computation of the planar homography (collineation) a00 = [x(1);y(1);1]; a10 = [x(2);y(2);1]; a11 = [x(3);y(3);1]; a01 = [x(4);y(4);1]; % Compute the planar collineation: (return the normalization matrix as well) [Homo,Hnorm,inv_Hnorm] = compute_homography ([a00 a10 a11 a01],[0 1 1 0;0 0 1 1;1 1 1 1]); % Build the grid using the planar collineation: x_l = ((0:n_sq_x)'*ones(1,n_sq_y+1))/n_sq_x; y_l = (ones(n_sq_x+1,1)*(0:n_sq_y))/n_sq_y; pts = [x_l(:) y_l(:) ones((n_sq_x+1)*(n_sq_y+1),1)]'; XX = Homo*pts; XX = XX(1:2,:) ./ (ones(2,1)*XX(3,:)); % Complete size of the rectangle W = n_sq_x*dX; L = n_sq_y*dY; %%%%%%%%%%%%%%%%%%%%%%%% ADDITIONAL STUFF IN THE CASE OF HIGHLY DISTORTED IMAGES %%%%%%%%%%%%% figure(2); hold on; plot(XX(1,:),XX(2,:),'r+'); title('The red crosses should be close to the image corners'); hold off; disp('If the guessed grid corners (red crosses on the image) are not close to the actual corners,'); disp('it is necessary to enter an initial guess for the radial distortion factor kc (useful for subpixel detection)'); quest_distort = input('Need of an initial guess for distortion? ([]=no, other=yes) '); quest_distort = ~isempty(quest_distort); if quest_distort, % Estimation of focal length: c_g = [size(I,2);size(I,1)]/2 + .5; f_g = Distor2Calib(0,[[x(1) x(2) x(4) x(3)] - c_g(1);[y(1) y(2) y(4) y(3)] - c_g(2)],1,1,4,W,L,[-W/2 W/2 W/2 -W/2;L/2 L/2 -L/2 -L/2; 0 0 0 0],100,1,1); f_g = mean(f_g); script_fit_distortion; end; %%%%%%%%%%%%%%%%%%%%% END ADDITIONAL STUFF IN THE CASE OF HIGHLY DISTORTED IMAGES %%%%%%%%%%%%% Np = (n_sq_x+1)*(n_sq_y+1); disp('Corner extraction...'); grid_pts = cornerfinder(XX,I,winty,wintx); %%% Finds the exact corners at every points! %save all_corners x y grid_pts grid_pts = grid_pts - 1; % subtract 1 to bring the origin to (0,0) instead of (1,1) in matlab (not necessary in C) ind_corners = [1 n_sq_x+1 (n_sq_x+1)*n_sq_y+1 (n_sq_x+1)*(n_sq_y+1)]; % index of the 4 corners ind_orig = (n_sq_x+1)*n_sq_y + 1; xorig = grid_pts(1,ind_orig); yorig = grid_pts(2,ind_orig); dxpos = mean([grid_pts(:,ind_orig) grid_pts(:,ind_orig+1)]'); dypos = mean([grid_pts(:,ind_orig) grid_pts(:,ind_orig-n_sq_x-1)]');


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