X-lanni
57 lines
1.5 KiB
Matlab
57 lines
1.5 KiB
Matlab
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#set(0,'defaultAxesFontName', 'Times')
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#set(0,'defaultTextFontName', 'Times')
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Prefix = 'loop_closure_detection_datasets';
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Dataset= 'CityCentre'
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Detectors = {'Surf'; 'Sift'; 'CudaSift'; 'GfttBrief'};
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% The Ground Truth is a squared bmp file (size must match the log files
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% length) where white dots mean loop closures.
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% Grey dots mean 'loop closures to ignore', this happens when the rehearsal
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% doesn't match consecutive images together.
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GroundTruthFile = [Prefix '/' Dataset '.png'];
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colors = 'kbgrcm';
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figure
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xlabel('Recall (%)')
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ylabel('Precision (%)')
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hold on;
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Results = {};
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TimeResults = {};
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for i=1:length(Detectors)
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LogI = importfile([Prefix '/' Dataset '/' Detectors{i} 'LogI.txt']);
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LogF = importfile([Prefix '/' Dataset '/' Detectors{i} 'LogF.txt']);
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PR = getPrecisionRecall(LogI, LogF, GroundTruthFile, 0.07);
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plot(100*PR(:,2), 100*PR(:,1), colors(mod(i,6)+1));
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% hold on;
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Results{i} = PR;
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time = sum(LogF(:,2:7),2)+LogF(:,17);%LogF(:,1)
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TimeResults{i} = time;
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meanTime = mean(time)
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meanWm = mean(LogI(:,7))
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meanDict = mean(LogI(:,6))
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maxTime = max(time)
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maxWm = max(LogI(:,7))
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maxDict = max(LogI(:,6))
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%figure(2)
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%plot(PR(:,4), PR(:,3), colors(mod(i,6)+1));
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%hold on;
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end
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legend(Detectors)
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title(Dataset)
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figure
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rows=floor(length(Detectors)/2 )+ mod(length(Detectors), 2)
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for i=1:length(TimeResults)
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subplot(rows, 2, i)
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plot(TimeResults{i})
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ylabel('Time (s)')
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title([Detectors{i} ' (' num2str(mean(TimeResults{i})) 's)'])
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end
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xlabel('Location indexes')
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