struct ThreadCtx {
public:
- ThreadCtx(cv::Size windows_size, uint cell_size, uint num_of_feats, uint num_of_scales = 1,
- ComplexMat *model_xf = nullptr, ComplexMat *yf = nullptr, bool zero_index = false)
+ ThreadCtx(cv::Size windows_size, uint cell_size, uint num_of_feats, uint num_of_scales = 1)
{
-#ifdef CUFFT
- if (zero_index) {
- cudaSetDeviceFlags(cudaDeviceMapHost);
- this->zero_index = true;
- }
-
-#if defined(ASYNC) || defined(OPENMP)
- CudaSafeCall(cudaStreamCreate(&this->stream));
-#endif
-
+ this->xf_sqr_norm = DynMem(num_of_scales * sizeof(float));
+ this->yf_sqr_norm = DynMem(sizeof(float));
this->patch_feats.reserve(uint(num_of_feats));
- // Size of cufftReal == float
+
uint cells_size =
((uint(windows_size.width) / cell_size) * (uint(windows_size.height) / cell_size)) * sizeof(float);
- this->data_i_1ch = DynMem(cells_size * num_of_scales);
- this->data_i_features = DynMem(cells_size * num_of_feats);
-
- this->ifft2_res = cv::Mat(windows_size.height / int(cell_size), windows_size.width / int(cell_size),
- CV_32FC(int(num_of_feats)), this->data_i_features.hostMem());
- this->response = cv::Mat(windows_size.height / int(cell_size), windows_size.width / int(cell_size),
- CV_32FC(int(num_of_scales)), this->data_i_1ch.hostMem());
+#if defined(CUFFT) && (defined(ASYNC) || defined(OPENMP))
+ CudaSafeCall(cudaStreamCreate(&this->stream));
+#endif
- this->zf.create(uint(windows_size.height) / cell_size, (uint(windows_size.width) / cell_size) / 2 + 1,
- num_of_feats, num_of_scales, this->stream);
- this->kzf.create(uint(windows_size.height) / cell_size, (uint(windows_size.width) / cell_size) / 2 + 1,
- num_of_scales, this->stream);
- this->kf.create(uint(windows_size.height) / cell_size, (uint(windows_size.width) / cell_size) / 2 + 1,
- num_of_scales, this->stream);
+#if defined(CUFFT) || defined(FFTW)
+ this->gauss_corr_res = DynMem(cells_size * num_of_scales);
+ this->data_features = DynMem(cells_size * num_of_feats);
- this->xf_sqr_norm = DynMem(num_of_scales * sizeof(float));
- this->yf_sqr_norm = DynMem(sizeof(float));
+ uint width_freq = (uint(windows_size.width) / cell_size) / 2 + 1;
- this->gauss_corr_res = DynMem(cells_size * num_of_scales);
this->in_all = cv::Mat(windows_size.height / int(cell_size) * int(num_of_scales),
windows_size.width / int(cell_size), CV_32F, this->gauss_corr_res.hostMem());
- if (zero_index) {
- this->rot_labels_data = DynMem(cells_size);
- this->rot_labels = cv::Mat(windows_size.height / int(cell_size), windows_size.width / int(cell_size),
- CV_32FC1, this->rot_labels_data.hostMem());
- }
-
- this->data_features = DynMem(cells_size * num_of_feats);
this->fw_all = cv::Mat((windows_size.height / int(cell_size)) * int(num_of_feats),
windows_size.width / int(cell_size), CV_32F, this->data_features.hostMem());
#else
+ uint width_freq = uint(windows_size.width) / cell_size;
- this->xf_sqr_norm = DynMem(num_of_scales * sizeof(float));
- this->yf_sqr_norm = DynMem(sizeof (float));
+ this->in_all = cv::Mat((windows_size.height / int(cell_size)), windows_size.width / int(cell_size), CV_32F);
+#endif
- this->patch_feats.reserve(num_of_feats);
+ this->data_i_features = DynMem(cells_size * num_of_feats);
+ this->data_i_1ch = DynMem(cells_size * num_of_scales);
- uint height = uint(windows_size.height) / cell_size;
-#ifdef FFTW
- uint width = (uint(windows_size.width) / cell_size) / 2 + 1;
-#else
- int width = windows_size.width / cell_size;
-#endif
+ this->ifft2_res = cv::Mat(windows_size.height / int(cell_size), windows_size.width / int(cell_size),
+ CV_32FC(int(num_of_feats)), this->data_i_features.hostMem());
+
+ this->response = cv::Mat(windows_size.height / int(cell_size), windows_size.width / int(cell_size),
+ CV_32FC(int(num_of_scales)), this->data_i_1ch.hostMem());
- this->ifft2_res = cv::Mat(int(height), windows_size.width / int(cell_size), CV_32FC(int(num_of_feats)));
- this->response = cv::Mat(int(height), windows_size.width / int(cell_size), CV_32FC(int(num_of_scales)));
+ this->patch_feats.reserve(num_of_feats);
- this->zf = ComplexMat(height, width, num_of_feats, num_of_scales);
- this->kzf = ComplexMat(height, width, num_of_scales);
- this->kf = ComplexMat(height, width, num_of_scales);
-#ifdef FFTW
- this->in_all = cv::Mat((windows_size.height / int(cell_size)) * int(num_of_scales),
- windows_size.width / int(cell_size), CV_32F);
- this->fw_all = cv::Mat((windows_size.height / int(cell_size)) * int(num_of_feats),
- windows_size.width / int(cell_size), CV_32F);
-#else
- this->in_all = cv::Mat((windows_size.height / int(cell_size)), windows_size.width / int(cell_size), CV_32F);
-#endif
-#endif
-#if defined(FFTW) || defined(CUFFT)
- if (zero_index) {
- model_xf->create(uint(windows_size.height) / cell_size, (uint(windows_size.width) / cell_size) / 2 + 1,
- num_of_feats);
- yf->create(uint(windows_size.height) / cell_size, (uint(windows_size.width) / cell_size) / 2 + 1, 1);
- // We use scale_vars[0] for updating the tracker, so we only allocate memory for its xf only.
#ifdef CUFFT
- this->xf.create(uint(windows_size.height) / cell_size, (uint(windows_size.width) / cell_size) / 2 + 1,
- num_of_feats, this->stream);
+ this->zf.create(uint(windows_size.height) / cell_size, width_freq, num_of_feats, num_of_scales, this->stream);
+ this->kzf.create(uint(windows_size.height) / cell_size, width_freq, num_of_scales, this->stream);
+ this->kf.create(uint(windows_size.height) / cell_size, width_freq, num_of_scales, this->stream);
#else
- this->xf.create(uint(windows_size.height) / cell_size, (uint(windows_size.width) / cell_size) / 2 + 1,
- num_of_feats);
+ this->zf.create(uint(windows_size.height) / cell_size, width_freq, num_of_feats, num_of_scales);
+ this->kzf.create(uint(windows_size.height) / cell_size, width_freq, num_of_scales);
+ this->kf.create(uint(windows_size.height) / cell_size, width_freq, num_of_scales);
#endif
- } else if (num_of_scales > 1) {
+
+ if (num_of_scales > 1) {
this->max_responses.reserve(uint(num_of_scales));
this->max_locs.reserve(uint(num_of_scales));
this->response_maps.reserve(uint(num_of_scales));
}
-#else
- if (zero_index) {
- model_xf->create(windows_size.height / cell_size, windows_size.width / cell_size, num_of_feats);
- yf->create(windows_size.height / cell_size, windows_size.width / cell_size, 1);
- this->xf.create(windows_size.height / cell_size, windows_size.width / cell_size, num_of_feats);
- }
-#endif
}
~ThreadCtx()
std::vector<cv::Mat> patch_feats;
cv::Mat in_all, fw_all, ifft2_res, response;
- ComplexMat zf, kzf, kf, xyf, xf;
+ ComplexMat zf, kzf, kf, xyf;
- // CuFFT variables
- cv::Mat rot_labels;
- DynMem gauss_corr_res, rot_labels_data, data_features, data_f, data_i_features, data_i_1ch;
+ DynMem data_i_features, data_i_1ch;
+ // CuFFT and FFTW variables
+ DynMem gauss_corr_res, data_features;
+ // CuFFT variables
cudaStream_t stream = nullptr;
ComplexMat model_alphaf, model_xf;
std::vector<double> max_responses;
std::vector<cv::Point2i> max_locs;
std::vector<cv::Mat> response_maps;
- bool zero_index = false;
};
#endif // SCALE_VARS_HPP
projects / hercules2020 / kcf.git / blobdiff