// Copyright (C) 1999 Jean-Marc Valin
#include "BufferedNode.h"
#include "net_types.h"
#include "kmeans.h"
#include "Vector.h"
using namespace std;
namespace FD {
class VQTrain;
DECLARE_NODE(VQTrain)
/*Node
*
* @name VQTrain
* @category VQ
* @require VQ
* @description No description available
*
* @input_name FRAMES
* @input_description No description available
*
* @output_name OUTPUT
* @output_description No description available
*
* @parameter_name MEANS
* @parameter_description No description available
*
* @parameter_name BINARY
* @parameter_description No description available
*
END*/
class VQTrain : public BufferedNode {
protected:
int framesInputID;
int outputID;
int nbMeans;
public:
/**Constructor, takes the name of the node and a set of parameters*/
VQTrain(string nodeName, ParameterSet params)
: BufferedNode(nodeName, params)
{
outputID = addOutput("OUTPUT");
framesInputID = addInput("FRAMES");
nbMeans = dereference_cast<int> (parameters.get("MEANS"));
}
/**Ask for the node's output which ID (number) is output_id
and for the 'count' iteration */
virtual void calculate(int output_id, int count, Buffer &out)
{
bool binary = false;
if (parameters.exist("BINARY"))
binary = dereference_cast<bool> (parameters.get("BINARY"));
int i;
NodeInput framesInput = inputs[framesInputID];
cerr << "getting frames..." << endl;
ObjectRef matRef = framesInput.node->getOutput(framesInput.outputID,count);
cerr << "got frames..." << endl;
Vector<ObjectRef> &mat = object_cast<Vector<ObjectRef> > (matRef);
KMeans *vq = new KMeans;
vector <float *> data(mat.size());
for (i=0;i<mat.size();i++)
data[i]= &object_cast <Vector<float> > (mat[i])[0];
int length = object_cast <Vector<float> > (mat[0]).size();
cerr << "training..." << endl;
vq->train(nbMeans,data,length,binary);
cerr << "training complete." << endl;
out[count] = ObjectRef(vq);
}
};
}//namespace FD
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