#include <memory>
#include "fhog.hpp"
+#include "complexmat.hpp"
#ifdef CUFFT
-#include "complexmat.cuh"
-#include "cuda_functions.cuh"
-#include "cuda/cuda_error_check.cuh"
+#include "cuda_error_check.hpp"
#include <cuda_runtime.h>
-#else
-#include "complexmat.hpp"
#endif
#include "cnfeat.hpp"
#include "fft.h"
-#include "threadctx.hpp"
#include "pragmas.h"
-struct BBox_c {
+class Kcf_Tracker_Private;
+struct ThreadCtx;
+
+struct BBox_c
+{
double cx, cy, w, h, a;
+ inline cv::Point2d center() const { return cv::Point2d(cx, cy); }
+
inline void scale(double factor)
{
cx *= factor;
cy *= factor;
- w *= factor;
- h *= factor;
+ w *= factor;
+ h *= factor;
}
- inline void scale_x(double factor)
+ inline cv::Rect get_rect()
{
- cx *= factor;
- w *= factor;
- }
-
- inline void scale_y(double factor)
- {
- cy *= factor;
- h *= factor;
+ return cv::Rect(int(cx-w/2.), int(cy-h/2.), int(w), int(h));
}
- inline cv::Rect get_rect() { return cv::Rect(int(cx - w / 2.), int(cy - h / 2.), int(w), int(h)); }
};
-class KCF_Tracker {
- public:
- bool m_debug{false};
- bool m_visual_debug{false};
- bool m_use_scale{true};
- bool m_use_angle{false}; // Doesn't work with FFTW-BIG version
- bool m_use_color{true};
-#ifdef ASYNC
- bool m_use_multithreading{true};
-#else
- bool m_use_multithreading {false};
-#endif //ASYNC
- bool m_use_subpixel_localization {true};
- bool m_use_subgrid_scale {true};
- bool m_use_cnfeat {true};
- bool m_use_linearkernel {false};
-#ifdef CUFFT
- bool m_use_cuda{true};
-#else
- bool m_use_cuda{false};
-#endif
+class KCF_Tracker
+{
+ friend ThreadCtx;
+ friend Kcf_Tracker_Private;
+public:
+ bool m_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};
+ const bool m_use_subgrid_scale {true};
+ const bool m_use_subgrid_angle {true};
+ const bool m_use_cnfeat {true};
+ const bool m_use_linearkernel {false};
+ const int p_cell_size = 4; //4 for hog (= bin_size)
/*
padding ... extra area surrounding the target (1.5)
output_sigma_factor ... spatial bandwidth (proportional to target) (0.1)
cell_size ... hog cell size (4)
*/
- KCF_Tracker(double padding, double kernel_sigma, double lambda, double interp_factor, double output_sigma_factor,
- int cell_size);
+ KCF_Tracker(double padding, double kernel_sigma, double lambda, double interp_factor, double output_sigma_factor, int cell_size);
KCF_Tracker();
~KCF_Tracker();
// Init/re-init methods
- void init(cv::Mat &img, const cv::Rect &bbox, int fit_size_x, int fit_size_y);
- void setTrackerPose(BBox_c &bbox, cv::Mat &img, int fit_size_x, int fit_size_y);
- void updateTrackerPosition(BBox_c &bbox);
+ void init(cv::Mat & img, const cv::Rect & bbox, int fit_size_x = -1, int fit_size_y = -1);
+ void setTrackerPose(BBox_c & bbox, cv::Mat & img, int fit_size_x = -1, int fit_size_y = -1);
+ void updateTrackerPosition(BBox_c & bbox);
// frame-to-frame object tracking
- void track(cv::Mat &img);
+ void track(cv::Mat & img);
BBox_c getBBox();
double getFilterResponse() const; // Measure of tracking accuracy
- private:
+private:
Fft &fft;
- BBox_c p_pose;
+ // Initial pose of tracked object in internal image coordinates
+ // (scaled by p_downscale_factor if p_resize_image)
+ BBox_c p_init_pose;
+
+ // 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;
- bool p_fit_to_pw2 = false;
const double p_downscale_factor = 0.5;
- double p_scale_factor_x = 1;
- double p_scale_factor_y = 1;
const double p_floating_error = 0.0001;
- double p_padding = 1.5;
- double p_output_sigma_factor = 0.1;
+ const double p_padding = 1.5;
+ const double p_output_sigma_factor = 0.1;
double p_output_sigma;
- double p_kernel_sigma = 0.5; // def = 0.5
- double p_lambda = 1e-4; // regularization in learning step
- double p_interp_factor = 0.02; // def = 0.02, linear interpolation factor for adaptation
- int p_cell_size = 4; // 4 for hog (= bin_size)
- cv::Size p_windows_size;
- uint p_num_scales {7};
- double p_scale_step = 1.02;
- double p_current_scale = 1.;
+ const double p_kernel_sigma = 0.5; //def = 0.5
+ const double p_lambda = 1e-4; //regularization in learning step
+ const double p_interp_factor = 0.02; //def = 0.02, linear interpolation factor for adaptation
+ 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 ? 5 : 1;
+ const double p_scale_step = 1.03;
double p_min_max_scale[2];
std::vector<double> p_scales;
- int p_current_angle = 0;
- uint p_num_angles {5};
- int p_angle_min = -20, p_angle_max = 20;
- int p_angle_step = 10;
- std::vector<int> p_angles;
-
- // for visual debug
- int p_debug_image_size = 100;
- std::vector<cv::Mat> p_debug_scale_responses;
- std::vector<cv::Mat> p_debug_subwindows;
-
- //for big batch
- int p_num_of_feats = 31 + (m_use_color ? 3 : 0) + (m_use_cnfeat ? 10 : 0);
- cv::Size p_roi;
-
- std::vector<ThreadCtx> p_threadctxs;
-
- //CUDA compability
- cv::Mat p_rot_labels;
- DynMem p_rot_labels_data;
-
- // 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;
+
+ const uint p_num_angles = 3;
+ const 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);
+ cv::Size feature_size;
+
+ 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) {}
+ };
+
+ std::unique_ptr<Model> model;
+
+ class GaussianCorrelation {
+ public:
+ GaussianCorrelation(uint num_scales, uint num_feats, cv::Size size)
+ : xf_sqr_norm(num_scales)
+ , xyf(Fft::freq_size(size), num_feats, num_scales)
+ , ifft_res(num_scales, size)
+ , k(num_scales, size)
+ {}
+ void operator()(ComplexMat &result, const ComplexMat &xf, const ComplexMat &yf, double sigma, bool auto_correlation, const KCF_Tracker &kcf);
+
+ private:
+ DynMem xf_sqr_norm;
+ DynMem yf_sqr_norm{1};
+ ComplexMat xyf;
+ MatScales ifft_res;
+ 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);
+ 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, double angle) const;
cv::Mat gaussian_shaped_labels(double sigma, int dim1, int dim2);
- void gaussian_correlation(struct ThreadCtx &vars, const ComplexMat &xf, const ComplexMat &yf, double sigma,
- bool auto_correlation = false);
- cv::Mat circshift(const cv::Mat &patch, int x_rot, int y_rot);
+ 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);
- std::vector<cv::Mat> get_features(cv::Mat &patch_rgb, cv::Mat &patch_gray);
- void geometric_transformations(cv::Mat &patch, int size_x, int size_y, int angle = 0, bool allow_debug = true);
- cv::Point2f sub_pixel_peak(cv::Point &max_loc, cv::Mat &response);
+ 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
+#endif //KCF_HEADER_6565467831231
projects / hercules2020 / kcf.git / blobdiff