1 #ifndef KCF_HEADER_6565467831231
2 #define KCF_HEADER_6565467831231
4 #include <opencv2/opencv.hpp>
10 #include "complexmat.cuh"
11 #include "cuda_functions.cuh"
12 #include "cuda/cuda_error_check.cuh"
13 #include <cuda_runtime.h>
15 #include "complexmat.hpp"
20 #include "threadctx.hpp"
25 double cx, cy, w, h, a;
27 inline void scale(double factor)
35 inline void scale_x(double factor)
41 inline void scale_y(double factor)
47 inline cv::Rect get_rect()
49 return cv::Rect(int(cx-w/2.), int(cy-h/2.), int(w), int(h));
58 bool m_visual_debug {false};
59 bool m_use_scale {false};
60 bool m_use_angle {true};
61 bool m_use_color {true};
63 bool m_use_multithreading {true};
65 bool m_use_multithreading {false};
67 bool m_use_subpixel_localization {true};
68 bool m_use_subgrid_scale {true};
69 bool m_use_cnfeat {true};
70 bool m_use_linearkernel {false};
72 bool m_use_big_batch {true};
74 bool m_use_big_batch {false};
77 bool m_use_cuda {true};
79 bool m_use_cuda {false};
83 padding ... extra area surrounding the target (1.5)
84 kernel_sigma ... gaussian kernel bandwidth (0.5)
85 lambda ... regularization (1e-4)
86 interp_factor ... linear interpolation factor for adaptation (0.02)
87 output_sigma_factor ... spatial bandwidth (proportional to target) (0.1)
88 cell_size ... hog cell size (4)
90 KCF_Tracker(double padding, double kernel_sigma, double lambda, double interp_factor, double output_sigma_factor, int cell_size);
94 // Init/re-init methods
95 void init(cv::Mat & img, const cv::Rect & bbox, int fit_size_x, int fit_size_y);
96 void setTrackerPose(BBox_c & bbox, cv::Mat & img, int fit_size_x, int fit_size_y);
97 void updateTrackerPosition(BBox_c & bbox);
99 // frame-to-frame object tracking
100 void track(cv::Mat & img);
107 bool p_resize_image = false;
108 bool p_fit_to_pw2 = false;
110 const double p_downscale_factor = 0.5;
111 double p_scale_factor_x = 1;
112 double p_scale_factor_y = 1;
113 double p_floating_error = 0.0001;
115 double p_padding = 1.5;
116 double p_output_sigma_factor = 0.1;
117 double p_output_sigma;
118 double p_kernel_sigma = 0.5; //def = 0.5
119 double p_lambda = 1e-4; //regularization in learning step
120 double p_interp_factor = 0.02; //def = 0.02, linear interpolation factor for adaptation
121 int p_cell_size = 4; //4 for hog (= bin_size)
122 cv::Size p_windows_size;
123 int p_num_scales {7};
124 double p_scale_step = 1.02;
125 double p_current_scale = 1.;
126 double p_min_max_scale[2];
127 std::vector<double> p_scales;
128 int p_num_angles {5};
129 int p_current_angle = 0;
130 int p_angle_step = 10;
131 std::vector<double> p_angles;
135 int p_roi_height, p_roi_width;
137 std::list<std::unique_ptr<ThreadCtx>> p_threadctxs;
140 cv::Mat p_rot_labels;
141 DynMem p_rot_labels_data;
145 ComplexMat p_model_alphaf;
146 ComplexMat p_model_alphaf_num;
147 ComplexMat p_model_alphaf_den;
148 ComplexMat p_model_xf;
151 void scale_track(ThreadCtx & vars, cv::Mat & input_rgb, cv::Mat & input_gray, double scale);
152 cv::Mat get_subwindow(const cv::Mat & input, int cx, int cy, int size_x, int size_y, int angle);
153 cv::Mat gaussian_shaped_labels(double sigma, int dim1, int dim2);
154 void gaussian_correlation(struct ThreadCtx &vars, const ComplexMat & xf, const ComplexMat & yf, double sigma, bool auto_correlation = false);
155 cv::Mat circshift(const cv::Mat & patch, int x_rot, int y_rot);
156 cv::Mat cosine_window_function(int dim1, int dim2);
157 void get_features(cv::Mat & input_rgb, cv::Mat & input_gray, int cx, int cy, int size_x, int size_y, ThreadCtx & vars, double scale = 1., int angle = 0);
158 cv::Point2f sub_pixel_peak(cv::Point & max_loc, cv::Mat & response);
159 double sub_grid_scale(int index = -1);
163 #endif //KCF_HEADER_6565467831231