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RF_Patches.m
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RF_Patches.m
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%KLT of confidence of patches. The patches is formed by their criteria of
%confidence(reliability)
%New way to evaluate the optical flow (global and local size)
%New way to propagate (expected to be faster than the previous
%propagation)
addpath(genpath('..\'))
%% Load image and GT
clear all;
add2='C:\Users\khoa\Dropbox\Database\optical flow\';
add3='C:\Users\khoa\Dropbox\Database\eval-data\';
add_movie='C:\Users\MAI\Dropbox\Database\optical flow\Dumptruck\';
addKITTI='C:\Users\MAI\Documents\KITI Flow\training\image_2\';
add='C:\Users\MAI\Dropbox\Database\other-data\GT\';
%add='D:\Dropbox\Database\other-data\GT\';
subPath = {'Venus', 'Dimetrodon', 'Hydrangea', 'RubberWhale',...
'Grove2', 'Grove3', 'Urban2', 'Urban3'};
% subPath = {'Army', 'Backyard', 'Basketball', 'Dumptruck',...
% 'Evergreen', 'Grove', 'Mequon', 'Schefflera','Teddy','Urban','Wooden','Yosemite'};
%% Parameters to run script
gt=1; % Load ground truth
%save = 0; % Save image to file
for seq=1:8
%% Loading images, groundtruth and convert to double
% str_idx1 = sprintf('%02d',seq);
% str_idx2= sprintf('%02d',seq+1);
% path1 = [add_movie 'frame' str_idx1 '.png'];
% path2 = [add_movie 'frame' str_idx2 '.png'];
% pathGT = '';
subPath{seq}
path1 = [add subPath{seq} '\frame10.png'];
path2 = [add subPath{seq} '\frame11.png'];
pathGT = [add subPath{seq} '\flow10.flo'];
[pyramid_images1c,pyramid_images2c,pyramid_levels,uvGT]=load_pyramidal_images_old(path1,path2,pathGT);
%% Main algorithm
median_filter_size = [5 5];
H_min = size(pyramid_images2c{pyramid_levels},1);
W_min = size(pyramid_images2c{pyramid_levels},2);
uvklt=zeros(H_min,W_min,2);
w = ones(H_min,W_min)*(1/(H_min*W_min));
nb_wrap=[12,12,12,12,12];
%nb_wrap=[1,1,1,1,1];
w_size=[5,5,5,5,5];
%w_size=[15,11,9,7,5];
v_size=[5,5,5,5,5];
tic
for lvl=pyramid_levels:-1:1
%fprintf('Pyr lvl: %d \n',lvl)
%pyr_image1 = pyramid_images1{lvl};
%pyr_image2 = pyramid_images2{lvl};
pyr_image1c = pyramid_images1c{lvl};
pyr_image2c = pyramid_images2c{lvl};
pyr_image1g = rgb2gray(pyr_image1c/255)*255;
pyr_image2g = rgb2gray(pyr_image2c/255)*255;
% pyr_image1g = normalize_image(pyr_image1c);
% pyr_image2g = normalize_image(pyr_image2c);
H = size(pyr_image1c, 1);
W = size(pyr_image1c, 2);
[x,y] = meshgrid(1:W,1:H);
if gt
tuv = resample_flow(uvGT,[H W]);
tup=tuv(:,:,1);
tvp=tuv(:,:,2);
end
uvklt = resample_flow(uvklt,[H W]);
uv_warp = uvklt;
% DO SOMETHING ? PROPAGATE FLOW ?
%taux= makemtrx_prop(H,W,pyr_image1c);
maxh = w_size(lvl);
maxw =w_size(lvl);
Patches=zeros(H,W);
abs_ures=zeros(H,W);
abs_vres=zeros(H,W);
c_ures=zeros(H,W);
c_vres=zeros(H,W);
%[I1x,I1y,I2x,I2y]=partial_derivation_origin(pyr_image1c,pyr_image2c);
% minEig=eigen_extract(I1x,I1y);
%conv_eig = eval_eig(minEig,5);
for k=1:nb_wrap(lvl)
%% Warping Image
[Ix,Iy,It,warpImc]=partial_derivation(pyr_image1c,pyr_image2c,uvklt,1);
%[Ix,Iy,It,warpImc]=partial_derivation_ex(I1x,I1y,I2x,I2y,pyr_image1c,pyr_image2c,uvklt,1);
%% KLT Flow
%fprintf('KLT ... ')
[ures,vres,minEig,iD]=LKT_res_color(Ix,Iy,It,maxh,maxw,~mod(k,4));
%[ures,vres,minEig,iD]=LKT_res_color_uv0(Ix,Iy,It,0,maxh,maxw,1);
% [ures,vres,null,iD]=LKT_res_color(Ix,Iy,It,maxh,maxw,0);
ures(ures > 1 ) = 1;
vres(vres > 1 ) = 1;
ures(ures < -1 ) = -1;
vres(vres < -1 ) = -1;
abs_ures=abs_ures+abs(ures);
abs_vres=abs_vres+abs(vres);
c_ures=c_ures+ures;
v_ures=c_vres+vres;
uvklt = uvklt+cat(3,ures,vres);
if (k==1) %First estimation
uvklt_old=uvklt; % Stock the first estimation
ures_old=ures;
vres_old=vres;
Patches_old = zeros(H,W);
end
if (~mod(k,4))
x2 = x + uvklt(:,:,1);
y2 = y + uvklt(:,:,2);
B = (x2>W) | (x2<1) | (y2>H) | (y2<1);
conv_eig = eval_eig(minEig,5);
% conv_var = eval_var(cat(3,c_ures,c_vres),5);
conv_var = eval_var(uvklt,5);
% conv_res = (1./(abs(ures)+0.00001)).*(1./(abs(vres)+0.00001));
[conv_res,mat_stable]=eval_res(ures_old,vres_old,ures,vres,abs_ures,abs_vres);
w= min(conv_var,min(conv_eig,conv_res));
%w = conv_eig;
w(iD)=0;
w(B)=0;
maxval = max(w(:));
w = w*100./maxval;
w= max(w,0.1);
% if(sum(Patches(:))) %Remove and add patches
% [Patches,check_mat]=Re_evaluate_patches(uvklt_old,uvklt,Patches,w);
% else %Create patches
% [Patches, check_mat,ind_p,index] = create_patch(w,5);
[Patches, check_mat,ind_p] = create_patch_grid(w,5);
%end
%Propagation
% if ((lvl ==1) && (k==12))
% figure (4)
% valueew = push_valuee(uvklt,w,tup,tvp,'');
% plot(valueew,'b','LineWidth',2);
% hold on
% %Check_error of patches
% error=[];
% for i =1:H
% for j=1:W
% if Patches(i,j)
% error = [error; sqrt((uvklt(i,j,1)-tup(i,j))^2+(uvklt(i,j,2)-tvp(i,j))^2)];
% %w(i,j)
% end
% end
% end
% mean(error,'omitnan')
% % imgflowcolor = uint8(flowToColor(uvklt));
% % figure(5)
% % imshow(imgflowcolor);
% % set(gca,'units','normalized','position',[0 0 1 1]);
% % print([subPath{seq} '_before'],'-depsc','-r0')
% end
[uvklt,w,~] = propagation_patch( uvklt,w,Patches,ind_p,pyr_image1c );
[uvklt,~] = propagation(uvklt,w,Patches,check_mat,pyr_image1c) ;
%[uvklt,~] = propagation_sort(uvklt,w,Patches,check_mat,pyr_image1c,index) ;
%Check_error of patches
uvklt_old = uvklt;
abs_ures=zeros(H,W);
abs_vres=zeros(H,W);
c_ures=zeros(H,W);
c_vres=zeros(H,W);
%ures_old = ures;
%vres_old = vres;
w_old=w;
% figure(99)
% imshow((Patches |Patches_old));
% Patches_old=Patches;
end
uvklt(:,:,1) = medfilt2(uvklt(:,:,1), median_filter_size, 'symmetric');
uvklt(:,:,2) = medfilt2(uvklt(:,:,2), median_filter_size, 'symmetric');
% if ((lvl ==1) && (k==12))
% figure (4)
% valueew = push_valuee(uvklt,w,tup,tvp,'');
% plot(valueew,'r','LineWidth',2);
% hold off
% set(gca,'fontsize',20)
% ylabel('AEPE') % y-axis label
% xlabel('% of most reliable point') % y-axis label
% %print(['pre_pos_pro_grid_eigRFmin_' subPath{seq}],'-depsc','-r0')
% %print(['pre_pos_pro_grid_eigRFmin_' subPath{seq}],'-dpng','-r0')
% %print(['C:\Users\MAI\Dropbox\Rapport\Optical_Flow\grid\pre_pos_pro_grid_varRFmin_' subPath{seq}],'-dpng','-r0');
% %print(['C:\Users\MAI\Dropbox\Rapport\Optical_Flow\strategy\strategy_RFmin_' subPath{seq}],'-dpng','-r0');
% % print(['C:\Obs\' 'KLT' int2str(ip(2)) int2str(ip(1)) ],'-dpng','-r0')
% error=[];
% for i =1:H
% for j=1:W
% if Patches(i,j)
% error = [error; sqrt((uvklt(i,j,1)-tup(i,j))^2+(uvklt(i,j,2)-tvp(i,j))^2)];
% %w(i,j)
% end
% end
% end
% mean(error,'omitnan')
% % imgflowcolor = uint8(flowToColor(uvklt));
% % figure(5)
% % imshow(imgflowcolor);
% % set(gca,'units','normalized','position',[0 0 1 1]);
% % print([subPath{seq} '_after'],'-depsc','-r0')
% end
% minu =min(min(min(uvklt(:,:,1))),min(tup(:)));
% maxu =max(max(max(uvklt(:,:,1))),max(tup(:)));
% minv =min(min(min(uvklt(:,:,2))),min(tvp(:)));
% maxv =max(max(max(uvklt(:,:,2))),max(tvp(:)));
% figure(11)
% subplot(2,2,1)
% surf(tup)
% axis([1 W 1 H minu maxu]);
% subplot(2,2,2)
% surf(uvklt(:,:,1))
% axis([1 W 1 H minu maxu]);
% subplot(2,2,3)
% surf(tvp)
% axis([1 W 1 H minv maxv]);
% subplot(2,2,4)
% surf(uvklt(:,:,2))
% axis([1 W 1 H minv maxv]);
% imgflowcolorP = uint8(flowToColor(uvklt.*repmat(Patches,[1,1,2])));
% figure(6)
% imshow(imgflowcolorP);
%res_pre=uv_res;
end
% Display after each pyramidal level
if gt
minu =min(min(min(uvklt(:,:,1))),min(tup(:)));
maxu =max(max(max(uvklt(:,:,1))),max(tup(:)));
minv =min(min(min(uvklt(:,:,2))),min(tvp(:)));
maxv =max(max(max(uvklt(:,:,2))),max(tvp(:)));
figure(11)
subplot(2,2,1)
surf(tup)
axis([1 W 1 H minu maxu]);
subplot(2,2,2)
surf(uvklt(:,:,1))
axis([1 W 1 H minu maxu]);
subplot(2,2,3)
surf(tvp)
axis([1 W 1 H minv maxv]);
subplot(2,2,4)
surf(uvklt(:,:,2))
axis([1 W 1 H minv maxv]);
% imgflowcolorP = uint8(flowToColor(uvklt.*repmat(Patches,[1,1,2])));
% figure(6)
% imshow(imgflowcolorP);
else
minu =min(min(uvklt(:,:,1)));
maxu =max(max(uvklt(:,:,1)));
minv =min(min(uvklt(:,:,2)));
maxv =max(max(uvklt(:,:,2)));
figure(12)
surf(uvklt(:,:,1))
axis([1 W 1 H minu maxu]);
figure(14)
surf(uvklt(:,:,2))
axis([1 W 1 H minv maxv]);
end
end
toc
% error_size = sum(Patches(:));
% error = zeros(error_size,1);
% count =1;
% for i=1:H
% for j=1:W
% if (Patches(i,j))
% error(count)=sqrt((uvklt(i,j,1)-tu(i,j))^2+(uvklt(i,j,2)-tv(i,j))^2);
% count=count+1;
% end
% end
% end
% mean(error,'omitnan')
%Display the final results
imgflowcolor = uint8(flowToColor(uvklt));
imgflowcolorP = uint8(flowToColor(uvklt.*repmat(Patches,[1,1,2])));
if gt
[aae stdae aepe] = flowAngErr(uvGT(:,:,1),uvGT(:,:,2), uvklt(:,:,1), uvklt(:,:,2), 0); % ignore 0 boundary pixels
fprintf('\nAAE %3.3f average EPE %3.3f \n', aae, aepe);
imgflowGT = uint8(flowToColor(uvGT));
figure(3)
subplot(1,2,1)
imshow(imgflowcolor);
subplot(1,2,2)
imshow(imgflowGT);
end
figure(6)
imshow(imgflowcolorP);
figure(5)
imshow(imgflowcolor);
% save(['C:\Users\MAI\Dropbox\Database\optical flow\Dumptruck\' str_idx1 '_uvklt.mat'],'uvklt','w');
%print(['C:\Users\MAI\Dropbox\Rapport\Optical_Flow\RF\' subPath{seq} '_n8np50'],'-dpng','-r0');
%print(['D:\Dropbox\Rapport\Optical_Flow\RF\' subPath{seq} '_n8np50'],'-dpng','-r0');
%print(['C:\Users\Khoa\Dropbox\Database\RF7\' subPath{seq} '_rf7b'],'-dpng','-r0')
%analyse_res(uvklt,w,tup,tvp,subPath{seq});
%print(['C:\New\RF\submit\' subPath{seq} '_res'],'-dpng','-r0')
%save(['C:\New\RF\submit\' subPath{seq} '_analyze.mat'],'uvklt','w','tu','tv')
%save(['C:\New\RF\submit\' subPath{seq} '_submit.mat'],'uvklt')
%save(['C:\Users\Khoa\Dropbox\Database\RF7\' subPath{seq} 'uvklt_rf7b.mat'],'uvklt')
end