drwnFilterBankResponse.h

/*****************************************************************************
** DARWIN: A FRAMEWORK FOR MACHINE LEARNING RESEARCH AND DEVELOPMENT
** Distributed under the terms of the BSD license (see the LICENSE file)
** Copyright (c) 2007-2015, Stephen Gould
** All rights reserved.
**
******************************************************************************
** FILENAME:    drwnFilterBankResponse.h
** AUTHOR(S):   Stephen Gould <stephen.gould@anu.edu.au>
**
*****************************************************************************/

#pragma once

#include <list>
#include <vector>

#include "Eigen/Core"

#include "cv.h"

using namespace std;
using namespace Eigen;

// drwnFilterBankResponse ------------------------------------------------------

class drwnFilterBankResponse {
 protected:
    vector<cv::Mat> _responses;     
    vector<cv::Mat> _sum;           
    vector<cv::Mat> _sqSum;         

 public:
    drwnFilterBankResponse();
    drwnFilterBankResponse(const drwnFilterBankResponse& f);
    ~drwnFilterBankResponse();

    void clear();
    inline bool empty() const { return _responses.empty(); }
    inline int size() const { return (int)_responses.size(); }
    inline int width() const { return _responses.empty() ? 0 : _responses[0].cols; }
    inline int height() const { return _responses.empty() ? 0 : _responses[0].rows; }
    inline size_t memory() const { return size() * width() * height() * sizeof(float) +
            2 * size() * (width() + 1) * (height() + 1) * sizeof(double); }

    // add or copy 32-bit floating-point response images to the filter bank
    void addResponseImage(cv::Mat& r);
    void addResponseImages(vector<cv::Mat>& r);
    void copyResponseImage(const cv::Mat& r);
    void copyResponseImages(const vector<cv::Mat>& r);
    const cv::Mat& getResponseImage(int i) const;
    void deleteResponseImage(int i);

    void exponentiateResponses(double alpha = 1.0);
    void normalizeResponses();
    void expAndNormalizeResponses(double alpha = 1.0);

    VectorXd value(int x, int y) const;
    VectorXd mean(int x, int y, int w, int h) const;
    VectorXd energy(int x, int y, int w, int h) const;
    VectorXd variance(int x, int y, int w, int h) const;

    VectorXd mean(const list<cv::Point>& pixels) const;
    VectorXd energy(const list<cv::Point>& pixels) const;
    VectorXd variance(const list<cv::Point>& pixels) const;

    VectorXd mean(const cv::Mat& mask) const;
    VectorXd energy(const cv::Mat& mask) const;
    VectorXd variance(const cv::Mat& mask) const;

    inline VectorXd mean() const { return mean(0, 0, width(), height()); }
    inline VectorXd energy() const { return energy(0, 0, width(), height()); }
    inline VectorXd variance() const { return variance(0, 0, width(), height()); }

    cv::Mat visualize() const;
};