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moved GpuMat and DevMem2D to core module, some code refactoring

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This commit is contained in:
Vladislav Vinogradov
2011-11-09 13:13:52 +00:00
parent 8a148e39f0
commit fcfa72081e
95 changed files with 18889 additions and 18485 deletions
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36
modules/gpu/src/stereocsbp.cpp
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@@ -57,7 +57,9 @@ void cv::gpu::StereoConstantSpaceBP::operator()(const GpuMat&, const GpuMat&, Gp
#else /* !defined (HAVE_CUDA) */
namespace cv { namespace gpu { namespace csbp
BEGIN_OPENCV_DEVICE_NAMESPACE
namespace stereocsbp
{
void load_constants(int ndisp, float max_data_term, float data_weight, float max_disc_term, float disc_single_jump, int min_disp_th,
const DevMem2Db& left, const DevMem2Db& right, const DevMem2Db& temp);
@@ -84,8 +86,11 @@ namespace cv { namespace gpu { namespace csbp
template<class T>
void compute_disp(const T* u, const T* d, const T* l, const T* r, const T* data_cost_selected, const T* disp_selected, size_t msg_step,
const DevMem2D_<short>& disp, int nr_plane, cudaStream_t stream);
}
}}}
END_OPENCV_DEVICE_NAMESPACE
using namespace OPENCV_DEVICE_NAMESPACE_ stereocsbp;
namespace
{
@@ -208,8 +213,7 @@ static void csbp_operator(StereoConstantSpaceBP& rthis, GpuMat u[2], GpuMat d[2]
////////////////////////////////////////////////////////////////////////////
// Compute
csbp::load_constants(rthis.ndisp, rthis.max_data_term, rthis.data_weight,
rthis.max_disc_term, rthis.disc_single_jump, rthis.min_disp_th, left, right, temp);
load_constants(rthis.ndisp, rthis.max_data_term, rthis.data_weight, rthis.max_disc_term, rthis.disc_single_jump, rthis.min_disp_th, left, right, temp);
if (stream)
{
@@ -248,28 +252,28 @@ static void csbp_operator(StereoConstantSpaceBP& rthis, GpuMat u[2], GpuMat d[2]
{
if (i == levels - 1)
{
csbp::init_data_cost(left.rows, left.cols, disp_selected_pyr[cur_idx].ptr<T>(), data_cost_selected.ptr<T>(),
init_data_cost(left.rows, left.cols, disp_selected_pyr[cur_idx].ptr<T>(), data_cost_selected.ptr<T>(),
step_pyr[i], rows_pyr[i], cols_pyr[i], i, nr_plane_pyr[i], rthis.ndisp, left.channels(), rthis.use_local_init_data_cost, cudaStream);
}
else
{
csbp::compute_data_cost(disp_selected_pyr[cur_idx].ptr<T>(), data_cost.ptr<T>(), step_pyr[i], step_pyr[i+1],
compute_data_cost(disp_selected_pyr[cur_idx].ptr<T>(), data_cost.ptr<T>(), step_pyr[i], step_pyr[i+1],
left.rows, left.cols, rows_pyr[i], cols_pyr[i], rows_pyr[i+1], i, nr_plane_pyr[i+1], left.channels(), cudaStream);
int new_idx = (cur_idx + 1) & 1;
csbp::init_message(u[new_idx].ptr<T>(), d[new_idx].ptr<T>(), l[new_idx].ptr<T>(), r[new_idx].ptr<T>(),
u[cur_idx].ptr<T>(), d[cur_idx].ptr<T>(), l[cur_idx].ptr<T>(), r[cur_idx].ptr<T>(),
disp_selected_pyr[new_idx].ptr<T>(), disp_selected_pyr[cur_idx].ptr<T>(),
data_cost_selected.ptr<T>(), data_cost.ptr<T>(), step_pyr[i], step_pyr[i+1], rows_pyr[i],
cols_pyr[i], nr_plane_pyr[i], rows_pyr[i+1], cols_pyr[i+1], nr_plane_pyr[i+1], cudaStream);
init_message(u[new_idx].ptr<T>(), d[new_idx].ptr<T>(), l[new_idx].ptr<T>(), r[new_idx].ptr<T>(),
u[cur_idx].ptr<T>(), d[cur_idx].ptr<T>(), l[cur_idx].ptr<T>(), r[cur_idx].ptr<T>(),
disp_selected_pyr[new_idx].ptr<T>(), disp_selected_pyr[cur_idx].ptr<T>(),
data_cost_selected.ptr<T>(), data_cost.ptr<T>(), step_pyr[i], step_pyr[i+1], rows_pyr[i],
cols_pyr[i], nr_plane_pyr[i], rows_pyr[i+1], cols_pyr[i+1], nr_plane_pyr[i+1], cudaStream);
cur_idx = new_idx;
}
csbp::calc_all_iterations(u[cur_idx].ptr<T>(), d[cur_idx].ptr<T>(), l[cur_idx].ptr<T>(), r[cur_idx].ptr<T>(),
data_cost_selected.ptr<T>(), disp_selected_pyr[cur_idx].ptr<T>(), step_pyr[i],
rows_pyr[i], cols_pyr[i], nr_plane_pyr[i], rthis.iters, cudaStream);
calc_all_iterations(u[cur_idx].ptr<T>(), d[cur_idx].ptr<T>(), l[cur_idx].ptr<T>(), r[cur_idx].ptr<T>(),
data_cost_selected.ptr<T>(), disp_selected_pyr[cur_idx].ptr<T>(), step_pyr[i],
rows_pyr[i], cols_pyr[i], nr_plane_pyr[i], rthis.iters, cudaStream);
}
if (disp.empty())
@@ -282,8 +286,8 @@ static void csbp_operator(StereoConstantSpaceBP& rthis, GpuMat u[2], GpuMat d[2]
else
out.setTo(zero);
csbp::compute_disp(u[cur_idx].ptr<T>(), d[cur_idx].ptr<T>(), l[cur_idx].ptr<T>(), r[cur_idx].ptr<T>(),
data_cost_selected.ptr<T>(), disp_selected_pyr[cur_idx].ptr<T>(), step_pyr[0], out, nr_plane_pyr[0], cudaStream);
compute_disp(u[cur_idx].ptr<T>(), d[cur_idx].ptr<T>(), l[cur_idx].ptr<T>(), r[cur_idx].ptr<T>(),
data_cost_selected.ptr<T>(), disp_selected_pyr[cur_idx].ptr<T>(), step_pyr[0], out, nr_plane_pyr[0], cudaStream);
if (disp.type() != CV_16S)
{