1 #ifndef KCF_HEADER_6565467831231
2 #define KCF_HEADER_6565467831231
4 #include <opencv2/opencv.hpp>
9 #include "complexmat.cuh"
10 #include "cuda_functions.cuh"
11 #include "cuda/cuda_error_check.cuh"
12 #include <cuda_runtime.h>
14 #include "complexmat.hpp"
24 inline void scale(double factor)
32 inline void scale_x(double factor)
38 inline void scale_y(double factor)
44 inline cv::Rect get_rect()
46 return cv::Rect(cx-w/2., cy-h/2., w, h);
55 bool m_use_scale {true};
56 bool m_use_color {true};
58 bool m_use_multithreading {true};
60 bool m_use_multithreading {false};
62 bool m_use_subpixel_localization {true};
63 bool m_use_subgrid_scale {true};
64 bool m_use_cnfeat {true};
65 bool m_use_linearkernel {false};
67 bool m_use_big_batch {true};
69 bool m_use_big_batch {false};
72 bool m_use_cuda {true};
74 bool m_use_cuda {false};
78 padding ... extra area surrounding the target (1.5)
79 kernel_sigma ... gaussian kernel bandwidth (0.5)
80 lambda ... regularization (1e-4)
81 interp_factor ... linear interpolation factor for adaptation (0.02)
82 output_sigma_factor ... spatial bandwidth (proportional to target) (0.1)
83 cell_size ... hog cell size (4)
85 KCF_Tracker(double padding, double kernel_sigma, double lambda, double interp_factor, double output_sigma_factor, int cell_size);
89 // Init/re-init methods
90 void init(cv::Mat & img, const cv::Rect & bbox, int fit_size_x, int fit_size_y);
91 void setTrackerPose(BBox_c & bbox, cv::Mat & img, int fit_size_x, int fit_size_y);
92 void updateTrackerPosition(BBox_c & bbox);
94 // frame-to-frame object tracking
95 void track(cv::Mat & img);
102 bool p_resize_image = false;
103 bool p_fit_to_pw2 = false;
107 const double p_downscale_factor = 0.5;
108 double p_scale_factor_x = 1;
109 double p_scale_factor_y = 1;
111 double p_padding = 1.5;
112 double p_output_sigma_factor = 0.1;
113 double p_output_sigma;
114 double p_kernel_sigma = 0.5; //def = 0.5
115 double p_lambda = 1e-4; //regularization in learning step
116 double p_interp_factor = 0.02; //def = 0.02, linear interpolation factor for adaptation
117 int p_cell_size = 4; //4 for hog (= bin_size)
118 int p_windows_size[2];
119 int p_num_scales {7};
120 double p_scale_step = 1.02;
121 double p_current_scale = 1.;
122 double p_min_max_scale[2];
123 std::vector<double> p_scales;
127 int p_roi_height, p_roi_width;
129 float *xf_sqr_norm = nullptr, *yf_sqr_norm = nullptr;
131 float *xf_sqr_norm_d = nullptr, *yf_sqr_norm_d = nullptr, *gauss_corr_res = nullptr;
137 ComplexMat p_model_alphaf;
138 ComplexMat p_model_alphaf_num;
139 ComplexMat p_model_alphaf_den;
140 ComplexMat p_model_xf;
142 cv::Mat get_subwindow(const cv::Mat & input, int cx, int cy, int size_x, int size_y);
143 cv::Mat gaussian_shaped_labels(double sigma, int dim1, int dim2);
144 ComplexMat gaussian_correlation(const ComplexMat & xf, const ComplexMat & yf, double sigma, bool auto_correlation = false);
145 cv::Mat circshift(const cv::Mat & patch, int x_rot, int y_rot);
146 cv::Mat cosine_window_function(int dim1, int dim2);
147 std::vector<cv::Mat> get_features(cv::Mat & input_rgb, cv::Mat & input_gray, int cx, int cy, int size_x, int size_y, double scale = 1.);
148 cv::Point2f sub_pixel_peak(cv::Point & max_loc, cv::Mat & response);
149 double sub_grid_scale(std::vector<double> & responses, int index = -1);
153 #endif //KCF_HEADER_6565467831231