src/threadctx.hpp

   1 #ifndef SCALE_VARS_HPP
   2 #define SCALE_VARS_HPP
   3
   4 #include "dynmem.hpp"
   5
   6 #ifdef CUFFT
   7 #include "complexmat.cuh"
   8 #else
   9 #include "complexmat.hpp"
  10 #ifndef CUFFTW
  11 // For compatibility reasons between CuFFT and FFTW, OpenCVfft versions.
  12 typedef int *cudaStream_t;
  13 #endif
  14 #endif
  15
  16 struct ThreadCtx {
  17   public:
  18     ThreadCtx(cv::Size windows_size, uint cell_size, uint num_of_feats, uint num_of_scales = 1)
  19     {
  20         this->xf_sqr_norm = DynMem(num_of_scales * sizeof(float));
  21         this->yf_sqr_norm = DynMem(sizeof(float));
  22         this->patch_feats.reserve(uint(num_of_feats));
  23
  24         uint cells_size =
  25             ((uint(windows_size.width) / cell_size) * (uint(windows_size.height) / cell_size)) * sizeof(float);
  26
  27 #if  !defined(BIG_BATCH) && defined(CUFFT) && (defined(ASYNC) || defined(OPENMP))
  28         CudaSafeCall(cudaStreamCreate(&this->stream));
  29 #endif
  30
  31 #if defined(CUFFT) || defined(FFTW)
  32         this->gauss_corr_res = DynMem(cells_size * num_of_scales);
  33         this->data_features = DynMem(cells_size * num_of_feats);
  34
  35         uint width_freq = (uint(windows_size.width) / cell_size) / 2 + 1;
  36
  37         this->in_all = cv::Mat(windows_size.height / int(cell_size) * int(num_of_scales),
  38                                windows_size.width / int(cell_size), CV_32F, this->gauss_corr_res.hostMem());
  39
  40         this->fw_all = cv::Mat((windows_size.height / int(cell_size)) * int(num_of_feats),
  41                                windows_size.width / int(cell_size), CV_32F, this->data_features.hostMem());
  42 #else
  43         uint width_freq = uint(windows_size.width) / cell_size;
  44
  45         this->in_all = cv::Mat((windows_size.height / int(cell_size)), windows_size.width / int(cell_size), CV_32F);
  46 #endif
  47
  48         this->data_i_features = DynMem(cells_size * num_of_feats);
  49         this->data_i_1ch = DynMem(cells_size * num_of_scales);
  50
  51         this->ifft2_res = cv::Mat(windows_size.height / int(cell_size), windows_size.width / int(cell_size),
  52                                   CV_32FC(int(num_of_feats)), this->data_i_features.hostMem());
  53
  54         this->response = cv::Mat(windows_size.height / int(cell_size), windows_size.width / int(cell_size),
  55                                  CV_32FC(int(num_of_scales)), this->data_i_1ch.hostMem());
  56
  57         this->patch_feats.reserve(num_of_feats);
  58
  59 #ifdef CUFFT
  60         this->zf.create(uint(windows_size.height) / cell_size, width_freq, num_of_feats, num_of_scales, this->stream);
  61         this->kzf.create(uint(windows_size.height) / cell_size, width_freq, num_of_scales, this->stream);
  62         this->kf.create(uint(windows_size.height) / cell_size, width_freq, num_of_scales, this->stream);
  63 #else
  64         this->zf.create(uint(windows_size.height) / cell_size, width_freq, num_of_feats, num_of_scales);
  65         this->kzf.create(uint(windows_size.height) / cell_size, width_freq, num_of_scales);
  66         this->kf.create(uint(windows_size.height) / cell_size, width_freq, num_of_scales);
  67 #endif
  68
  69         if (num_of_scales > 1) {
  70             this->max_responses.reserve(uint(num_of_scales));
  71             this->max_locs.reserve(uint(num_of_scales));
  72             this->response_maps.reserve(uint(num_of_scales));
  73         }
  74     }
  75
  76     ~ThreadCtx()
  77     {
  78 #if  !defined(BIG_BATCH) && defined(CUFFT) && (defined(ASYNC) || defined(OPENMP))
  79         CudaSafeCall(cudaStreamDestroy(this->stream));
  80 #endif
  81     }
  82
  83     DynMem xf_sqr_norm, yf_sqr_norm;
  84     std::vector<cv::Mat> patch_feats;
  85
  86     cv::Mat in_all, fw_all, ifft2_res, response;
  87     ComplexMat zf, kzf, kf, xyf;
  88
  89     DynMem data_i_features, data_i_1ch;
  90     // CuFFT and FFTW variables
  91     DynMem gauss_corr_res, data_features;
  92
  93     // CuFFT variables
  94     cudaStream_t stream = nullptr;
  95     ComplexMat model_alphaf, model_xf;
  96
  97     // Variables used during non big batch mode and in big batch mode with ThreadCtx in p_threadctxs in kcf  on zero index.
  98     cv::Point2i max_loc;
  99     double max_val, max_response;
 100
 101     // Big batch variables
 102     // Stores value of responses, location of maximal response and response maps for each scale
 103     std::vector<double> max_responses;
 104     std::vector<cv::Point2i> max_locs;
 105     std::vector<cv::Mat> response_maps;
 106 };
 107
 108 #endif // SCALE_VARS_HPP