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Copy pathVOCevaldet_IOUplot (复件).m
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VOCevaldet_IOUplot (复件).m
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%function [rec,prec,ap] = VOCevaldet(VOCopts,id,cls,draw)
clc,clear
close all
clss = {'Insulator';
'Rotary_double_ear';
'Binaural_sleeve';
'Brace_sleeve';
'Steady_arm_base';
'Bracing_wire_hook';
'Double_sleeve_connector';
'Messenger_wire_base';
'Windproof_wire_ring';
'Insulator_base';
'Isoelectric_line';
'Brace_sleeve_screw'};
draw = true;
VOCopts = VOCinit();
aplist=zeros(length(clss),1);
dos(['mkdir ./output'])
dos(['chmod -R 777 *'])
confi_thresh = 0.5;
clsin={'030538767_K1222355_T047_1_15';
'030540998_K1222452_425_1_14';
'025811861_K1213204_101_1_28';
'025742861_K1212606_75_1_14'};
for clsini=1:length(clsin)
flag=1;
for clsn=1:length(clss)
%clsn=1;
cls = clss{clsn};
% load test set
fid = fopen(sprintf(VOCopts.imgsetpath,VOCopts.testset),'r');
[gtids,t]=textscan(fid,'%s');
gtids = cellstr(char(gtids{1}));
% load ground truth objects
tic;
npos=0;
gt=struct('BB',[],'diff',[],'det',[]);
% for i=1:length(gtids)
% % display progress
% if toc>1
% fprintf('%s: pr: load: %d/%d\n',cls,i,length(gtids));
% drawnow;
% tic;
% end
% read annotation
rec=PASreadrecord(sprintf(VOCopts.annopath,clsin{clsini})); % zhen shi kuang
% extract objects of class
clsinds=strmatch(cls,{rec.objects(:).class},'exact');
gt.BB=cat(1,rec.objects(clsinds).bbox)';
gt.diff=[rec.objects(clsinds).difficult];
gt.det=false(length(clsinds),1);
% end
% load results
fid = fopen(sprintf(VOCopts.detrespath,strcat('voc.txt',cls)),'r'); %ce shi kuang
fid = fopen(sprintf(VOCopts.detrespath,cls),'r'); %ce shi kuang
%fid = fopen(sprintf('wangliyou/%s.txt',cls));
[content,t]=textscan(fid,'%s %f %f %f %f %f');
ids = cellstr(char(content{1}));
confidence = double(content{2});
b1 = double(content{3});
b2 = double(content{4});
b3 = double(content{5});
b4 = double(content{6});
VOCopts.detrespath
BB=[b1 b2 b3 b4]';
% sort detections by decreasing confidence
%[sc,si]=sort(-confidence);
%ids=ids(si);
%BB=BB(:,si);
% assign detections to ground truth objects
nd=length(confidence);
tp=zeros(nd,1);
fp=zeros(nd,1);
tic;
for d=1:nd % ceshi suoyin
% display progress
if strcmp(ids{d}, clsin{clsini}) && confidence(d)>confi_thresh
if toc>1
fprintf('%s: pr: compute: %d/%d\n',cls,d,nd);
drawnow;
tic;
end
% find ground truth image
i=strmatch(ids{d},gtids,'exact'); % zhenshi suoyin
if isempty(i)
error('unrecognized image "%s"',ids{d});
elseif length(i)>1
error('multiple image "%s"',ids{d});
end
% assign detection to ground truth object if any
bb=BB(:,d); % ceshi kuang
ovmax=-inf;
for j=1:size(gt(i).BB,2)
bbgt=gt(i).BB(:,j); % zhenshi kuang
bi=[max(bb(1),bbgt(1)) ; max(bb(2),bbgt(2)) ; min(bb(3),bbgt(3)) ; min(bb(4),bbgt(4))];
iw=bi(3)-bi(1)+1;
ih=bi(4)-bi(2)+1;
if iw>0 && ih>0
% compute overlap as area of intersection / area of union
ua=(bb(3)-bb(1)+1)*(bb(4)-bb(2)+1)+...
(bbgt(3)-bbgt(1)+1)*(bbgt(4)-bbgt(2)+1)-...
iw*ih;
ov=iw*ih/ua; % I O U
% if ov>ovmax
% ovmax=ov; % MAX I O U
% jmax=j;
% end
figname=sprintf(VOCopts.imgpath,ids{d});
if flag==1
h1=figure,
imshow(figname),
flag=0;
end
hold on
rectangle('position',[bb(1),bb(2),bb(3)-bb(1),bb(4)-bb(2)],'LineWidth',2,'edgecolor','y')
rectangle('position',[bbgt(1),bbgt(2),bbgt(3)-bbgt(1),bbgt(4)-bbgt(2)],'LineWidth',2,'edgecolor','r')
%rectangle('position',[bb(1),bb(2)-100,350,100],'LineWidth',0.1,'facecolor','b')
text(bb(1),bb(2)-50,num2str(confidence(d)),'BackgroundColor','yellow')
%legend('forecast box','ground true box')
%plot([0,0],'r')
%plot([0,0],'b')
hold on
end
end
end
end
% assign detection as true positive/don't care/false positive
% if ovmax>=VOCopts.minoverlap %I O U gtyuzhi
% if ~gt(i).diff(jmax)
% if ~gt(i).det(jmax)
% tp(d)=1; % true positive
% gt(i).det(jmax)=true;
% else
% fp(d)=1; % false positive (multiple detection)
% end
% end
% else
% fp(d)=1; % false positive 对于同一个gt,找到多个目标,则后续目标设为fp
% end
% end
%
% end
% % compute precision/recall
% fp=cumsum(fp);
% tp=cumsum(tp);
% rec=tp/npos;
% prec=tp./(fp+tp);
%
% % compute average precision
%
% ap=0;
% for t=0:0.01:1 % THRESH *
% p=max(prec(rec>=t)); % dayu yuzhide prec
% if isempty(p)
% p=0;
% end
% ap=ap+p/110; % average precision
% end
%
% if ~draw
% % plot precision/recall
% h = figure,
% plot(rec,prec,'-');
% grid;
% xlabel 'recall'
% ylabel 'precision'
% title(sprintf('class: %s, subset: %s, AP = %.3f',cls,VOCopts.testset,ap));
% saveas(h,strcat('output/',cls,'IOU.jpg'))
% end
%
% % record average precision
% %aplist(clsn) = ap;
% %save(sprintf('output/%s_P-R.mat',cls),'rec','prec','ap');
end
end
saveas(h1,strcat('output/','IOU.jpg'))
%saveas(h,strcat('output/','P-R.jpg'))
%map = sum(aplist)/length(clss)
dos('cd output/')
dos('chmod -R 777 *')