src/threadctx.hpp

   1 #ifndef SCALE_VARS_HPP
   2 #define SCALE_VARS_HPP
   3
   4 #include <future>
   5 #include "dynmem.hpp"
   6 #include "kcf.h"
   7
   8 #ifdef CUFFT
   9 #include "complexmat.cuh"
  10 #else
  11 #include "complexmat.hpp"
  12 #endif
  13
  14 class KCF_Tracker;
  15
  16 struct ThreadCtx {
  17   public:
  18     ThreadCtx(cv::Size roi, uint num_of_feats, double scale, uint num_of_scales)
  19         : scale(scale)
  20         , gc(num_of_scales)
  21     {
  22         uint cells_size = roi.width * roi.height * sizeof(float);
  23
  24 #if defined(CUFFT) || defined(FFTW)
  25         this->gauss_corr_res = DynMem(cells_size * num_of_scales);
  26         this->data_features = DynMem(cells_size * num_of_feats);
  27
  28         uint width_freq = roi.width / 2 + 1;
  29
  30         this->in_all = cv::Mat(roi.height * num_of_scales, roi.width, CV_32F, this->gauss_corr_res.hostMem());
  31         this->fw_all = cv::Mat(roi.height * num_of_feats, roi.width, CV_32F, this->data_features.hostMem());
  32 #else
  33         uint width_freq = roi.width;
  34
  35         this->in_all = cv::Mat(roi, CV_32F);
  36 #endif
  37
  38         this->data_i_features = DynMem(cells_size * num_of_feats);
  39         this->data_i_1ch = DynMem(cells_size * num_of_scales);
  40
  41         this->ifft2_res = cv::Mat(roi, CV_32FC(num_of_feats), this->data_i_features.hostMem());
  42         this->response = cv::Mat(roi, CV_32FC(num_of_scales), this->data_i_1ch.hostMem());
  43
  44 #ifdef CUFFT
  45         this->zf.create(roi.height, width_freq, num_of_feats, num_of_scales);
  46         this->kzf.create(roi.height, width_freq, num_of_scales);
  47         this->kf.create(roi.height, width_freq, num_of_scales);
  48 #else
  49         this->zf.create(roi.height, width_freq, num_of_feats, num_of_scales);
  50         this->kzf.create(roi.height, width_freq, num_of_scales);
  51         this->kf.create(roi.height, width_freq, num_of_scales);
  52 #endif
  53
  54 #ifdef BIG_BATCH
  55         if (num_of_scales > 1) {
  56             this->max_responses.reserve(num_of_scales);
  57             this->max_locs.reserve(num_of_scales);
  58             this->response_maps.reserve(num_of_scales);
  59         }
  60 #endif
  61     }
  62     ThreadCtx(ThreadCtx &&) = default;
  63
  64     const double scale;
  65 #ifdef ASYNC
  66     std::future<void> async_res;
  67 #endif
  68
  69     class gaussian_correlation_data {
  70         friend void KCF_Tracker::gaussian_correlation(struct ThreadCtx &vars, const ComplexMat &xf, const ComplexMat &yf, double sigma, bool auto_correlation);
  71         DynMem xf_sqr_norm;
  72         DynMem yf_sqr_norm{sizeof(float)};
  73
  74       public:
  75         gaussian_correlation_data(uint num_of_scales) : xf_sqr_norm(num_of_scales * sizeof(float)) {}
  76     } gc;
  77
  78     cv::Mat in_all, fw_all, ifft2_res, response;
  79     ComplexMat zf, kzf, kf, xyf;
  80
  81     DynMem data_i_features, data_i_1ch;
  82     // CuFFT and FFTW variables
  83     DynMem gauss_corr_res, data_features;
  84
  85     // CuFFT variables
  86     ComplexMat model_alphaf, model_xf;
  87
  88     // Variables used during non big batch mode and in big batch mode with ThreadCtx in p_threadctxs in kcf  on zero index.
  89     cv::Point2i max_loc;
  90     double max_val, max_response;
  91
  92 #ifdef BIG_BATCH
  93     // Stores value of responses, location of maximal response and response maps for each scale
  94     std::vector<double> max_responses;
  95     std::vector<cv::Point2i> max_locs;
  96     std::vector<cv::Mat> response_maps;
  97 #endif
  98 };
  99
 100 #endif // SCALE_VARS_HPP