evaluation/UAV-benchmark-MOTD_v1.0/utils/CalculateDetectionPR_seq.m

function CalculateDetectionPR_seq(detection)

gtDataDir = '.\GT\';
resDateDir = '.\RES_DET\';
seqDirs = {'M0203','M0205','M0208','M0209','M0403','M0601','M0602','M0606','M0701','M0801','M0802','M1001','M1004','M1007','M1009','M1101','M1301','M1302','M1303','M1401'};
seqLens = [1007,646,265,1576,514,372,480,1374,1308,298,1101,1859,269,659,604,864,1182,719,445,1050];

attribute.name = [];
attribute.rec = [];
attribute.prec = [];

seqDirs_day = [3,4,5,6,7,8,10,11,17,18,19,20];
seqDirs_night = [1,2,12,14,16];
seqDirs_fog = [9,13,15];
seqDirs_low = [1,2,4,10,11,16,19,20];
seqDirs_media = [3,5,7,8,12,13,14,15,17,18];
seqDirs_high = [6,9];
seqDirs_front = [3,4,5,6,7,8,12,13,14,16,17,20];
seqDirs_side = [2,4,5,6,8,11,16,18,19];
seqDirs_bird = [1,9,10,15];
seqDirs_long = [4,12];

%% for the evaluation of sequence attribute
detectorSet = {'day','night','fog','low','medium','high','front','side','bird','long'};
seqSet = {seqDirs_day,seqDirs_night,seqDirs_fog,seqDirs_low,seqDirs_media,seqDirs_high,seqDirs_front,seqDirs_side,seqDirs_bird, seqDirs_long};

for idDet = 1:length(detectorSet)

    detectorName = detectorSet{idDet};
    %% detection threshold configuration

    idSeq = 0;
    allgtMatch = [];
    alldetMatch = [];
    allFrames = 0;
    
    while(idSeq<21)
        idSeq = idSeq + 1;

        curSeq = seqSet{idDet};
        if(ismember(idSeq, curSeq))
            numFrames = seqLens(idSeq);
            sequenceName = seqDirs{idSeq};
            
            gt = load(sprintf('%s%s%s',gtDataDir,sequenceName,'_gt_whole.txt'));

            detections = load(sprintf('%s\\%s\\%s%s',resDateDir,detection,sequenceName,'.txt'));
            file_gt_ign = sprintf('%s%s%s',gtDataDir,sequenceName,'_gt_ignore.txt');
            pass = {'M0203','M0205','M0208','M0403','M0601','M0602','M0606','M0701','M0802','M1001','M1004','M1007','M1009','M1101','M1301','M1302','M1303','M1401'};
            % ignore the detections in the ignored regions
            if ismember(sequenceName, pass)
                gt_ign = dlmread(file_gt_ign);
                for gt_i = 1:length(gt_ign(:,1))
                    detections(detections(:,1) == gt_ign(gt_i,1) & detections(:,3)>gt_ign(gt_i,3) & detections(:,4)>gt_ign(gt_i,4) & detections(:,3)+detections(:,5)<gt_ign(gt_i,3)+gt_ign(gt_i,5) & detections(:,4)+detections(:,6)<gt_ign(gt_i,4)+gt_ign(gt_i,6),:) = [];
                end
            end
            
            gtMatch = [];
            detMatch = [];
            for fr = 1:numFrames
                curLineGt = gt(:,1) == fr;
                curLineDet = detections(:,1) == fr;
                gt0 = gt(curLineGt,3:6);
                
                gt0 = cat(2,gt0,zeros(size(gt0,1),1));
                dt0 = detections(curLineDet,3:7);
                
                [gt1, dt1] = evalRes(gt0, dt0);
                gtMatch = cat(1, gtMatch, gt1(:,5));
                detMatch = cat(1, detMatch, dt1(:,5:6)); % modify here
            end
            allgtMatch = cat(1, allgtMatch, gtMatch);
            alldetMatch = cat(1, alldetMatch, detMatch);
            allFrames = allFrames + numFrames;
        end
    end
    
    [~,idrank] = sort(-alldetMatch(:,1));
    fp=cumsum(alldetMatch(idrank,2)==0);
    tp=cumsum(alldetMatch(idrank,2)==1);
    rec=tp/max(1,numel(allgtMatch));
    prec=tp./max(1,(fp+tp));
    AP = roundn(VOCap(rec,prec)*100,-2);
    figure(),plot(rec,prec,'LineWidth',4);
    axis([0 1 0 1]);

    xlabel('recall'),ylabel('precision'),title([detectorName ' AP = ' num2str(AP)]);
    
    attribute.name{idDet} = [detectorName]; %
    attribute.rec{idDet} = rec;
    attribute.prec{idDet} = prec;
end

save(sprintf('.\\det_EVA\\%s_seq.mat',detection),'attribute')