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"
24 double cx, cy, w, h, a;
26 inline void scale(double factor)
34 inline void scale_x(double factor)
40 inline void scale_y(double factor)
46 inline cv::Rect get_rect() { return cv::Rect(int(cx - w / 2.), int(cy - h / 2.), int(w), int(h)); }
52 bool m_visual_debug{false};
53 bool m_use_scale{true};
54 bool m_use_angle{true}; // Doesn't work with FFTW-BIG version
55 bool m_use_color{true};
57 bool m_use_multithreading{true};
59 bool m_use_multithreading{false};
61 bool m_use_subpixel_localization{true};
62 bool m_use_subgrid_scale{true};
63 bool m_use_cnfeat{true};
64 bool m_use_linearkernel{false};
66 bool m_use_big_batch{true};
68 bool m_use_big_batch{false};
71 bool m_use_cuda{true};
73 bool m_use_cuda{false};
77 padding ... extra area surrounding the target (1.5)
78 kernel_sigma ... gaussian kernel bandwidth (0.5)
79 lambda ... regularization (1e-4)
80 interp_factor ... linear interpolation factor for adaptation (0.02)
81 output_sigma_factor ... spatial bandwidth (proportional to target) (0.1)
82 cell_size ... hog cell size (4)
84 KCF_Tracker(double padding, double kernel_sigma, double lambda, double interp_factor, double output_sigma_factor,
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;
105 const double p_downscale_factor = 0.5;
106 double p_scale_factor_x = 1;
107 double p_scale_factor_y = 1;
108 double p_floating_error = 0.0001;
110 double p_padding = 1.5;
111 double p_output_sigma_factor = 0.1;
112 double p_output_sigma;
113 double p_kernel_sigma = 0.5; // def = 0.5
114 double p_lambda = 1e-4; // regularization in learning step
115 double p_interp_factor = 0.02; // def = 0.02, linear interpolation factor for adaptation
116 int p_cell_size = 4; // 4 for hog (= bin_size)
117 cv::Size p_windows_size;
119 double p_scale_step = 1.02;
120 double p_current_scale = 1.;
121 double p_min_max_scale[2];
122 std::vector<double> p_scales;
124 int p_current_angle = 0;
125 int p_angle_min = -20, p_angle_max = 20;
126 int p_angle_step = 10;
127 std::vector<int> p_angles;
130 int p_debug_image_size = 100;
132 std::vector<cv::Mat> p_debug_scale_responses;
133 std::vector<cv::Mat> p_debug_subwindows;
136 int p_num_of_feats = 31 + (m_use_color ? 3 : 0) + (m_use_cnfeat ? 10 : 0);
139 int p_roi_height, p_roi_width;
141 std::list<std::unique_ptr<ThreadCtx>> p_threadctxs;
144 cv::Mat p_rot_labels;
145 DynMem p_rot_labels_data;
149 ComplexMat p_model_alphaf;
150 ComplexMat p_model_alphaf_num;
151 ComplexMat p_model_alphaf_den;
152 ComplexMat p_model_xf;
155 void scale_track(ThreadCtx &vars, cv::Mat &input_rgb, cv::Mat &input_gray, double scale, int angle = 0);
156 cv::Mat get_subwindow(const cv::Mat &input, int cx, int cy, int size_x, int size_y);
157 cv::Mat gaussian_shaped_labels(double sigma, int dim1, int dim2);
158 void gaussian_correlation(struct ThreadCtx &vars, const ComplexMat &xf, const ComplexMat &yf, double sigma,
159 bool auto_correlation = false);
160 cv::Mat circshift(const cv::Mat &patch, int x_rot, int y_rot);
161 cv::Mat cosine_window_function(int dim1, int dim2);
162 void get_features(cv::Mat &patch_rgb, cv::Mat &patch_gray, ThreadCtx &vars);
163 void geometric_transformations(cv::Mat &patch, int size_x, int size_y, double scale = 1, int angle = 0,
164 bool allow_debug = true);
165 cv::Point2f sub_pixel_peak(cv::Point &max_loc, cv::Mat &response);
166 double sub_grid_scale(int index = -1);
169 #endif // KCF_HEADER_6565467831231