Problem using "addSample" while compiling

[hadarszostak]

Hi,

background:
I followed the build workflow in this Link to compile on Linux, I'm using a Raspberry pi. The Build was applied with Shared Library option.

I had a problem after Build that libgrt.so wasn't located at "/usr/lib/arm-linux-gnueabihf" so I wasn't be able to run the GRT examples. I found the libgrt.so at "/usr/local/lib" and copied it to "/usr/lib/arm-linux-gnueabihf", then I was able to run some examples with databases like IrisData.grt

The GRT library is located at /usr/local/include/GRT.
End of background

while compiling the below lines I encountered a problem: (Short version of the code with only necessary code lines for understanding)

#include "GRT/GRT.h"
#include <vector>
using manespace GRT;
int main(){

        ClassificationData trainingData;																		
	GestureRecognitionPipeline pipeline;
	pipeline.addPreProcessingModule(MovingAverageFilter(5,1));
	pipeline.addFeatureExtractionModule(FFT(512));
	pipeline.setClassifier(ANBC());
	pipeline.addPostProcessingModule( ClassLabelTimeoutFilter(1000) );
	trainingData.setNumDimensions( 1 );
	UINT gestureLabel = 1;
	std::vector< double > DataToRecognize (1)={1,2,3,4,5,6};
        
       trainingData.addSample( gestureLabel, DataToRecognize );
       bool saveResult = trainingData.save( "TrainingData.grt" );
       bool loadResult = trainingData.load( "TrainingData.grt" );
}

Building this using g++ -g -Wall -std=c++11 -o "main" "Main.cpp" -l grt

Removing the Lines :

trainingData.addSample( gestureLabel, DataToRecognize );
bool saveResult = trainingData.save( "TrainingData.grt" );
bool loadResult = trainingData.load( "TrainingData.grt" );

Results with a good Compiling and Building session.

But adding these lines, results with the following compilation errors :

Main.cpp: In function ‘int main()’:
Main.cpp:94:56: error: no matching function for call to ‘GRT::ClassificationData::addSample(GRT::UINT&, std::vector<double>&)’
  trainingData.addSample( gestureLabel, DataToRecognize );
                                                        ^
Main.cpp:94:56: note: candidate is:
In file included from /usr/local/include/GRT/CoreModules/MLBase.h:33:0,
                 from /usr/local/include/GRT/CoreModules/PreProcessing.h:34,
                 from /usr/local/include/GRT/PreProcessingModules/DoubleMovingAverageFilter.h:31,
                 from /usr/local/include/GRT/Util/PeakDetection.h:13,
                 from /usr/local/include/GRT/GRT.h:60,
                 from Main.cpp:14:
/usr/local/include/GRT/DataStructures/ClassificationData.h:163:10: note: bool GRT::ClassificationData::addSample(GRT::UINT, const GRT::VectorFloat&)
     bool addSample(const UINT classLabel,const VectorFloat &sample);
          ^
/usr/local/include/GRT/DataStructures/ClassificationData.h:163:10: note:   no known conversion for argument 2 from ‘std::vector<double>’ to ‘const GRT::VectorFloat&’
Main.cpp:96:7: warning: unused variable ‘saveResult’ [-Wunused-variable]
  bool saveResult = trainingData.save( "TrainingData.grt" );
       ^
Main.cpp:98:7: warning: unused variable ‘loadResult’ [-Wunused-variable]
  bool loadResult = trainingData.load( "TrainingData.grt" );
       ^
Compilation failed.

Need help here please. multiple candidates are detected to "addSample" and I have no idea how to solve this.

Nick,
Thanks for sharing the GRT, great "Getting Started" page.
Edit:
After I solved the problem, Please consider changing "Getting Started" page with the solution:
std::vector< double > sample(1);
To
VectorFloat sample(1);

[hadarszostak]

Solved,

Reading the compiling error, there was a problem with input parameters of "addSample":
no matching function for call to ‘GRT::ClassificationData::addSample(GRT::UINT&, std::vector<double>&)
Vs.
bool GRT::ClassificationData::addSample(GRT::UINT, const GRT::VectorFloat&)

Changing:
std::vector< double > DataToRecognize (1)={1,2,3,4,5,6};
To:
VectorFloat DataToRecognize(1);

As for GRT::UINT& vs GRT::UINT, I did nothing to solve that. To be more accurate I passed (UINT)1 and then get back to gestureLabel parameter.