#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"
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};
+ enum class vd {NONE, PATCH, RESPONSE} m_visual_debug {vd::NONE};
const bool m_use_scale {true};
const bool m_use_color {true};
const bool m_use_subpixel_localization {true};
// 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.;
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;
+ const uint p_num_scales = m_use_scale ? 5 : 1;
+ const double p_scale_step = 1.03;
double p_min_max_scale[2];
std::vector<double> p_scales;
- const uint p_num_angles = 1;
+ const uint p_num_angles = 3;
const int p_angle_step = 10;
- std::vector<double> p_angles = {0};
+ std::vector<double> p_angles;
const 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_alphaf {height, width, 1};
+ ComplexMat model_alphaf_num {height, width, 1};
+ ComplexMat model_alphaf_den {height, width, 1};
+ ComplexMat model_xf {height, width, n_feats};
+ ComplexMat xf {height, width, 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) {}
+ };
- //model
- ComplexMat p_yf;
- ComplexMat p_model_alphaf;
- ComplexMat p_model_alphaf_num;
- ComplexMat p_model_alphaf_den;
- ComplexMat p_model_xf;
- ComplexMat p_xf;
+ std::unique_ptr<Model> model;
class GaussianCorrelation {
public:
- GaussianCorrelation(uint num_scales, cv::Size size)
+ GaussianCorrelation(uint num_scales, uint num_feats, cv::Size size)
: xf_sqr_norm(num_scales)
- , xyf(Fft::freq_size(size), 1, num_scales)
+ , xyf(Fft::freq_size(size), num_feats, num_scales)
, ifft_res(num_scales, size)
, k(num_scales, size)
{}
//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);
+ 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);