#if !defined OFINDER
#define OFINDER

#include <opencv2\core\core.hpp>
#include <opencv2\imgproc\imgproc.hpp>

class ObjectFinder {

  private:

	float hranges[2];
    const float* ranges[3];
    int channels[3];

	float threshold;
	cv::MatND histogram;
	cv::SparseMat shistogram;
	bool isSparse;

  public:

	ObjectFinder() : threshold(0.1f), isSparse(false) {

		ranges[0]= hranges; // all channels have the same range 
		ranges[1]= hranges; 
		ranges[2]= hranges; 
	}
   
	// Sets the threshold on histogram values [0,1]
	void setThreshold(float t) {

		threshold= t;
	}

	// Gets the threshold
	float getThreshold() {

		return threshold;
	}

	// Sets the reference histogram
	void setHistogram(const cv::MatND& h) {

		isSparse= false;
		histogram= h;
		cv::normalize(histogram,histogram,1.0);
	}

	// Sets the reference histogram
	void setHistogram(const cv::SparseMat& h) {

		isSparse= true;
		shistogram= h;
		cv::normalize(shistogram,shistogram,1.0,cv::NORM_L2);
	}

	// Finds the pixels belonging to the histogram
	cv::Mat find(const cv::Mat& image) {

		cv::Mat result;

		hranges[0]= 0.0;	// range [0,255]
		hranges[1]= 255.0;
		channels[0]= 0;		// the three channels 
		channels[1]= 1; 
		channels[2]= 2; 

		if (isSparse) { // call the right function based on histogram type

		   cv::calcBackProject(&image,
                      1,            // one image
                      channels,     // vector specifying what histogram dimensions belong to what image channels
                      shistogram,   // the histogram we are using
                      result,       // the resulting back projection image
                      ranges,       // the range of values, for each dimension
                      255.0         // the scaling factor is chosen such that a histogram value of 1 maps to 255
		   );

		} else {

		   cv::calcBackProject(&image,
                      1,            // one image
                      channels,     // vector specifying what histogram dimensions belong to what image channels
                      histogram,    // the histogram we are using
                      result,       // the resulting back projection image
                      ranges,       // the range of values, for each dimension
                      255.0         // the scaling factor is chosen such that a histogram value of 1 maps to 255
		   );
		}


        // Threshold back projection to obtain a binary image
		if (threshold>0.0)
			cv::threshold(result, result, 255*threshold, 255, cv::THRESH_BINARY);

		return result;
	}

	cv::Mat find(const cv::Mat& image, float minValue, float maxValue, int *channels, int dim) {

		cv::Mat result;

		hranges[0]= minValue;
		hranges[1]= maxValue;

		for (int i=0; i<dim; i++)
			this->channels[i]= channels[i];

		if (isSparse) { // call the right function based on histogram type

		   cv::calcBackProject(&image,
                      1,            // we only use one image at a time
                      channels,     // vector specifying what histogram dimensions belong to what image channels
                      shistogram,   // the histogram we are using
                      result,       // the resulting back projection image
                      ranges,       // the range of values, for each dimension
                      255.0         // the scaling factor is chosen such that a histogram value of 1 maps to 255
		   );

		} else {

		   cv::calcBackProject(&image,
                      1,            // we only use one image at a time
                      channels,     // vector specifying what histogram dimensions belong to what image channels
                      histogram,    // the histogram we are using
                      result,       // the resulting back projection image
                      ranges,       // the range of values, for each dimension
                      255.0         // the scaling factor is chosen such that a histogram value of 1 maps to 255
		   );
		}

        // Threshold back projection to obtain a binary image
		if (threshold>0.0)
			cv::threshold(result, result, 255*threshold, 255, cv::THRESH_BINARY);

		return result;
	}

};


#endif