#include <memory>
#include "fhog.hpp"
+#include "complexmat.hpp"
#ifdef CUFFT
-#include "complexmat.cuh"
-#include "cuda_functions.cuh"
#include "cuda_error_check.hpp"
#include <cuda_runtime.h>
-#else
-#include "complexmat.hpp"
#endif
#include "cnfeat.hpp"
-#include "fft.h"
+#ifdef FFTW
+#include "fft_fftw.h"
+#define FFT Fftw
+#elif defined(CUFFT)
+#include "fft_cufft.h"
+#define FFT cuFFT
+#else
+#include "fft_opencv.h"
+#define FFT FftOpencv
+#endif
#include "pragmas.h"
class Kcf_Tracker_Private;
struct BBox_c
{
- double cx, cy, w, h;
+ double cx, cy, w, h, a;
inline cv::Point2d center() const { return cv::Point2d(cx, cy); }
class KCF_Tracker
{
friend ThreadCtx;
+ friend Kcf_Tracker_Private;
public:
bool m_debug {false};
- bool m_visual_debug {false};
- const bool m_use_scale {true};
- const bool m_use_color {true};
- const bool m_use_subpixel_localization {true};
- const bool m_use_subgrid_scale {true};
- const bool m_use_cnfeat {true};
- const bool m_use_linearkernel {false};
+ enum class vd {NONE, PATCH, RESPONSE} m_visual_debug {vd::NONE};
+ constexpr static bool m_use_scale {true};
+ constexpr static bool m_use_color {true};
+ constexpr static bool m_use_subpixel_localization {true};
+ constexpr static bool m_use_subgrid_scale {true};
+ constexpr static bool m_use_subgrid_angle {true};
+ constexpr static bool m_use_cnfeat {true};
+ constexpr static bool m_use_linearkernel {false};
const int p_cell_size = 4; //4 for hog (= bin_size)
/*
double getFilterResponse() const; // Measure of tracking accuracy
private:
- Fft &fft;
+ FFT &fft;
// Initial pose of tracked object in internal image coordinates
// (scaled by p_downscale_factor if p_resize_image)
// Information to calculate current pose of the tracked object
cv::Point2d p_current_center;
double p_current_scale = 1.;
+ double p_current_angle = 0.;
double max_response = -1.;
bool p_resize_image = false;
- const double p_downscale_factor = 0.5;
- const double p_floating_error = 0.0001;
+ constexpr static double p_downscale_factor = 0.5;
+ constexpr static double p_floating_error = 0.0001;
const double p_padding = 1.5;
const double p_output_sigma_factor = 0.1;
cv::Size p_windows_size; // size of the patch to find the tracked object in
cv::Size fit_size; // size to which rescale the patch for better FFT performance
- const uint p_num_scales = m_use_scale ? 7 : 1;
- const double p_scale_step = 1.02;
+ constexpr static uint p_num_scales = m_use_scale ? 5 : 1;
+ constexpr static double p_scale_step = 1.03;
double p_min_max_scale[2];
std::vector<double> p_scales;
- const uint p_num_angles = 1;
- const int p_angle_step = 10;
- std::vector<double> p_angles = {0};
+ constexpr static uint p_num_angles = 3;
+ constexpr static int p_angle_step = 10;
+ std::vector<double> p_angles;
- const int p_num_of_feats = 31 + (m_use_color ? 3 : 0) + (m_use_cnfeat ? 10 : 0);
+ constexpr static int p_num_of_feats = 31 + (m_use_color ? 3 : 0) + (m_use_cnfeat ? 10 : 0);
cv::Size feature_size;
- Kcf_Tracker_Private &d;
+ std::unique_ptr<Kcf_Tracker_Private> d;
class Model {
+ cv::Size feature_size;
uint height, width, n_feats;
public:
ComplexMat yf {height, width, 1};
ComplexMat model_xf {height, width, n_feats};
ComplexMat xf {height, width, n_feats};
- Model(cv::Size freq_size, uint _n_feats) : height(freq_size.height), width(freq_size.width), n_feats(_n_feats) {}
+ // Temporary variables for trainig
+ MatScaleFeats patch_feats{1, n_feats, feature_size};
+ MatScaleFeats temp{1, n_feats, feature_size};
+
+
+
+ Model(cv::Size feature_size, uint _n_feats)
+ : feature_size(feature_size)
+ , height(Fft::freq_size(feature_size).height)
+ , width(Fft::freq_size(feature_size).width)
+ , n_feats(_n_feats) {}
};
std::unique_ptr<Model> model;
MatScales k;
};
-
//helping functions
void scale_track(ThreadCtx &vars, cv::Mat &input_rgb, cv::Mat &input_gray);
- cv::Mat get_subwindow(const cv::Mat &input, int cx, int cy, int size_x, int size_y) const;
+ cv::Mat get_subwindow(const cv::Mat &input, int cx, int cy, int size_x, int size_y, double angle) const;
cv::Mat gaussian_shaped_labels(double sigma, int dim1, int dim2);
std::unique_ptr<GaussianCorrelation> gaussian_correlation;
cv::Mat circshift(const cv::Mat &patch, int x_rot, int y_rot) const;
cv::Mat cosine_window_function(int dim1, int dim2);
- cv::Mat get_features(cv::Mat &input_rgb, cv::Mat &input_gray, int cx, int cy, int size_x, int size_y, double scale) const;
+ cv::Mat get_features(cv::Mat &input_rgb, cv::Mat &input_gray, cv::Mat *dbg_patch, int cx, int cy, int size_x, int size_y, double scale, double angle) const;
cv::Point2f sub_pixel_peak(cv::Point &max_loc, cv::Mat &response) const;
double sub_grid_scale(uint index);
void resizeImgs(cv::Mat &input_rgb, cv::Mat &input_gray);
void train(cv::Mat input_rgb, cv::Mat input_gray, double interp_factor);
double findMaxReponse(uint &max_idx, cv::Point2d &new_location) const;
+ double sub_grid_angle(uint max_index);
};
#endif //KCF_HEADER_6565467831231