Adding OpenCV's GPU GFTT/ OpticalFlow and CudaSift support (#1330)

* Adding GFTT and SIFT Cuda support

* Working CudaSift

* Disable cudasift option when not available

* Added check to avoid re-allocating gpu memory everytime parseParameters is called. Added workaround of to detect/ignore invalid descriptors

* Added SIFT/PreciseUpscale and SIFT/Upscale parameters. Adjusted max octave to behave more like opencv

* Refactored how maximum features are thresholded, to be more similar to OpenCV version

* Updated loop closure benchmark scripts

* Cuda optical flow tmp commit

* Added Stereo/Gpu Vis/CorFlowGpu parameters (optical flow gpu integration for F2F odom and stereo correspondences)

* Fixed build without opencv cuda

* Fixed build with Opencv 4.10

* ZED: updated parameters to match zed sdk 4

* MRPT requires C++17

* updated max octave limit CudaSift

archive/2010-LoopClosure/ShowLogs/precisionRecallAllDetectors.m

@@ -0,0 +1,56 @@
+
+#set(0,'defaultAxesFontName', 'Times')
+#set(0,'defaultTextFontName', 'Times')
+
+Prefix = 'loop_closure_detection_datasets';
+Dataset= 'CityCentre'
+Detectors = {'Surf'; 'Sift'; 'CudaSift'; 'GfttBrief'};
+
+% The Ground Truth is a squared bmp file (size must match the log files 
+% length) where white dots mean loop closures.
+% Grey dots mean 'loop closures to ignore', this happens when the rehearsal
+% doesn't match consecutive images together.
+GroundTruthFile = [Prefix '/' Dataset '.png'];
+
+colors = 'kbgrcm';
+figure
+xlabel('Recall (%)')
+ylabel('Precision (%)')
+hold on;
+
+Results = {};
+TimeResults = {};
+
+for i=1:length(Detectors)
+    LogI = importfile([Prefix '/' Dataset '/' Detectors{i} 'LogI.txt']);
+    LogF = importfile([Prefix '/' Dataset '/' Detectors{i} 'LogF.txt']);
+
+    PR = getPrecisionRecall(LogI, LogF, GroundTruthFile, 0.07);
+    plot(100*PR(:,2), 100*PR(:,1), colors(mod(i,6)+1));
+   % hold on;
+   Results{i} = PR;
+   time = sum(LogF(:,2:7),2)+LogF(:,17);%LogF(:,1)
+   TimeResults{i} = time;
+   meanTime = mean(time)
+   meanWm = mean(LogI(:,7))
+   meanDict = mean(LogI(:,6))
+   maxTime = max(time)
+   maxWm = max(LogI(:,7))
+   maxDict = max(LogI(:,6))
+    
+    %figure(2)
+    %plot(PR(:,4), PR(:,3), colors(mod(i,6)+1));
+    %hold on;
+end
+legend(Detectors)
+title(Dataset)
+
+figure
+rows=floor(length(Detectors)/2 )+ mod(length(Detectors),  2)
+for i=1:length(TimeResults)
+    subplot(rows, 2, i)
+    plot(TimeResults{i})
+    ylabel('Time (s)')
+    title([Detectors{i} ' (' num2str(mean(TimeResults{i})) 's)'])
+end
+xlabel('Location indexes')