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a lot of refactoring

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pull/13383/head
Anatoly Baksheev 15 years ago
parent 35ebeb21bd
commit ef9a9d43a4
4 changed files with 282 additions and 319 deletions
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  1. 4
      modules/gpu/include/opencv2/gpu/gpu.hpp
  2. 2
      modules/gpu/src/beliefpropagation_gpu.cpp
  3. 178
      modules/gpu/src/constantspacebp_gpu.cpp
  4. 417
      modules/gpu/src/cuda/constantspacebp.cu

4
modules/gpu/include/opencv2/gpu/gpu.hpp
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@ -413,7 +413,7 @@ namespace cv
void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity);
//! Acync version
void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, const Stream& stream);
void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream);
int ndisp;
@ -462,7 +462,7 @@ namespace cv
void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity);
//! Acync version
void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, const Stream& stream);
void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream);
int ndisp;

2
modules/gpu/src/beliefpropagation_gpu.cpp
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@ -212,7 +212,7 @@ void cv::gpu::StereoBeliefPropagation::operator()(const GpuMat& left, const GpuM
::stereo_bp_gpu_operator(ndisp, iters, levels, max_data_term, data_weight, max_disc_term, disc_single_jump, msg_type, u, d, l, r, u2, d2, l2, r2, datas, out, left, right, disp, 0);
}
void cv::gpu::StereoBeliefPropagation::operator()(const GpuMat& left, const GpuMat& right, GpuMat& disp, const Stream& stream)
void cv::gpu::StereoBeliefPropagation::operator()(const GpuMat& left, const GpuMat& right, GpuMat& disp, Stream& stream)
{
::stereo_bp_gpu_operator(ndisp, iters, levels, max_data_term, data_weight, max_disc_term, disc_single_jump, msg_type, u, d, l, r, u2, d2, l2, r2, datas, out, left, right, disp, StreamAccessor::getStream(stream));
}

178
modules/gpu/src/constantspacebp_gpu.cpp
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@ -59,29 +59,42 @@ void cv::gpu::StereoConstantSpaceBP::operator()(const GpuMat&, const GpuMat&, Gp
namespace cv { namespace gpu { namespace csbp
{
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 DevMem2D& left, const DevMem2D& right, const DevMem2D& temp);
const DevMem2D& left, const DevMem2D& right, const DevMem2D& temp);
void init_data_cost(int rows, int cols, const DevMem2D& disp_selected_pyr, const DevMem2D& data_cost_selected,
size_t msg_step, int msg_type, int h, int w, int level, int nr_plane, int ndisp, int channels,
const cudaStream_t& stream);
void compute_data_cost(const DevMem2D& disp_selected_pyr, const DevMem2D& data_cost, size_t msg_step1, size_t msg_step2, int msg_type,
int rows, int cols, int h, int w, int h2, int level, int nr_plane, int channels, const cudaStream_t& stream);
void init_data_cost(int rows, int cols, short* disp_selected_pyr, short* data_cost_selected,
size_t msg_step, int h, int w, int level, int nr_plane, int ndisp, int channels, cudaStream_t stream);
void init_data_cost(int rows, int cols, float* disp_selected_pyr, float* data_cost_selected,
size_t msg_step, int h, int w, int level, int nr_plane, int ndisp, int channels, cudaStream_t stream);
void compute_data_cost(const short* disp_selected_pyr, short* data_cost, size_t msg_step1, size_t msg_step2,
int rows, int cols, int h, int w, int h2, int level, int nr_plane, int channels, cudaStream_t stream);
void compute_data_cost(const float* disp_selected_pyr, float* data_cost, size_t msg_step1, size_t msg_step2,
int rows, int cols, int h, int w, int h2, int level, int nr_plane, int channels, cudaStream_t stream);
void init_message(short* u_new, short* d_new, short* l_new, short* r_new,
const short* u_cur, const short* d_cur, const short* l_cur, const short* r_cur,
short* selected_disp_pyr_new, const short* selected_disp_pyr_cur,
short* data_cost_selected, const short* data_cost, size_t msg_step1, size_t msg_step2,
int h, int w, int nr_plane, int h2, int w2, int nr_plane2, cudaStream_t stream);
void init_message(float* u_new, float* d_new, float* l_new, float* r_new,
const float* u_cur, const float* d_cur, const float* l_cur, const float* r_cur,
float* selected_disp_pyr_new, const float* selected_disp_pyr_cur,
float* data_cost_selected, const float* data_cost, size_t msg_step1, size_t msg_step2,
int h, int w, int nr_plane, int h2, int w2, int nr_plane2, cudaStream_t stream);
void init_message(const DevMem2D& u_new, const DevMem2D& d_new, const DevMem2D& l_new, const DevMem2D& r_new,
const DevMem2D& u_cur, const DevMem2D& d_cur, const DevMem2D& l_cur, const DevMem2D& r_cur,
const DevMem2D& selected_disp_pyr_new, const DevMem2D& selected_disp_pyr_cur,
const DevMem2D& data_cost_selected, const DevMem2D& data_cost, size_t msg_step1, size_t msg_step2, int msg_type,
int h, int w, int nr_plane, int h2, int w2, int nr_plane2, const cudaStream_t& stream);
void calc_all_iterations(short* u, short* d, short* l, short* r, short* data_cost_selected,
const short* selected_disp_pyr_cur, size_t msg_step, int h, int w, int nr_plane, int iters, cudaStream_t stream);
void calc_all_iterations(const DevMem2D& u, const DevMem2D& d, const DevMem2D& l, const DevMem2D& r, const DevMem2D& data_cost_selected,
const DevMem2D& selected_disp_pyr_cur, size_t msg_step, int msg_type, int h, int w, int nr_plane, int iters,
const cudaStream_t& stream);
void calc_all_iterations(float*u, float* d, float* l, float* r, float* data_cost_selected,
const float* selected_disp_pyr_cur, size_t msg_step, int h, int w, int nr_plane, int iters, cudaStream_t stream);
void compute_disp(const DevMem2D& u, const DevMem2D& d, const DevMem2D& l, const DevMem2D& r, const DevMem2D& data_cost_selected,
const DevMem2D& disp_selected, size_t msg_step, int msg_type, const DevMem2D& disp, int nr_plane,
const cudaStream_t& stream);
void compute_disp(const short* u, const short* d, const short* l, const short* r, const short* data_cost_selected, const short* disp_selected, size_t msg_step,
DevMem2D_<short> disp, int nr_plane, cudaStream_t stream);
void compute_disp(const float* u, const float* d, const float* l, const float* r, const float* data_cost_selected, const float* disp_selected, size_t msg_step,
DevMem2D_<short> disp, int nr_plane, cudaStream_t stream);
}}}
namespace
@ -94,53 +107,48 @@ namespace
cv::gpu::StereoConstantSpaceBP::StereoConstantSpaceBP(int ndisp_, int iters_, int levels_, int nr_plane_,
int msg_type_)
: ndisp(ndisp_), iters(iters_), levels(levels_), nr_plane(nr_plane_),
max_data_term(DEFAULT_MAX_DATA_TERM), data_weight(DEFAULT_DATA_WEIGHT),
max_disc_term(DEFAULT_MAX_DISC_TERM), disc_single_jump(DEFAULT_DISC_SINGLE_JUMP), min_disp_th(0),
msg_type(msg_type_)
{
CV_Assert(msg_type_ == CV_32F || msg_type_ == CV_16S);
}
cv::gpu::StereoConstantSpaceBP::StereoConstantSpaceBP(int ndisp_, int iters_, int levels_, int nr_plane_,
float max_data_term_, float data_weight_, float max_disc_term_, float disc_single_jump_,
int min_disp_th_,
int msg_type_)
int min_disp_th_, int msg_type_)
: ndisp(ndisp_), iters(iters_), levels(levels_), nr_plane(nr_plane_),
max_data_term(max_data_term_), data_weight(data_weight_),
max_disc_term(max_disc_term_), disc_single_jump(disc_single_jump_), min_disp_th(min_disp_th_),
msg_type(msg_type_)
{
}
CV_Assert(msg_type_ == CV_32F || msg_type_ == CV_16S);
}
static void stereo_csbp_gpu_operator(int& ndisp, int& iters, int& levels, int& nr_plane,
float& max_data_term, float& data_weight, float& max_disc_term, float& disc_single_jump,
int& min_disp_th,
int& msg_type,
GpuMat u[2], GpuMat d[2], GpuMat l[2], GpuMat r[2],
template<class T>
static void csbp_operator(StereoConstantSpaceBP& rthis, GpuMat u[2], GpuMat d[2], GpuMat l[2], GpuMat r[2],
GpuMat disp_selected_pyr[2], GpuMat& data_cost, GpuMat& data_cost_selected,
GpuMat& temp, GpuMat& out,
const GpuMat& left, const GpuMat& right, GpuMat& disp,
const cudaStream_t& stream)
GpuMat& temp, GpuMat& out, const GpuMat& left, const GpuMat& right, GpuMat& disp,
cudaStream_t stream)
{
CV_DbgAssert(0 < ndisp && 0 < iters && 0 < levels && 0 < nr_plane
&& (msg_type == CV_32F || msg_type == CV_16S)
CV_DbgAssert(0 < rthis.ndisp && 0 < rthis.iters && 0 < rthis.levels && 0 < rthis.nr_plane
&& left.rows == right.rows && left.cols == right.cols && left.type() == right.type());
CV_Assert(levels <= 8 && (left.type() == CV_8UC1 || left.type() == CV_8UC3));
CV_Assert(rthis.levels <= 8 && (left.type() == CV_8UC1 || left.type() == CV_8UC3));
const Scalar zero = Scalar::all(0);
const float scale = ((msg_type == CV_32F) ? 1.0f : 10.0f);
const size_t type_size = ((msg_type == CV_32F) ? sizeof(float) : sizeof(short));
const float scale = (rthis.msg_type == CV_32F) ? 1.0f : 10.0f;
////////////////////////////////////////////////////////////////////////////////////////////
// Init
int rows = left.rows;
int cols = left.cols;
levels = min(levels, int(log((double)ndisp) / log(2.0)));
rthis.levels = min(rthis.levels, int(log((double)rthis.ndisp) / log(2.0)));
int levels = rthis.levels;
AutoBuffer<int> buf(levels * 4);
@ -151,10 +159,10 @@ static void stereo_csbp_gpu_operator(int& ndisp, int& iters, int& levels, int& n
cols_pyr[0] = cols;
rows_pyr[0] = rows;
nr_plane_pyr[0] = nr_plane;
nr_plane_pyr[0] = rthis.nr_plane;
const int n = 64;
step_pyr[0] = alignSize(cols * type_size, n) / type_size;
step_pyr[0] = alignSize(cols * sizeof(T), n) / sizeof(T);
for (int i = 1; i < levels; i++)
{
cols_pyr[i] = (cols_pyr[i-1] + 1) / 2;
@ -162,43 +170,41 @@ static void stereo_csbp_gpu_operator(int& ndisp, int& iters, int& levels, int& n
nr_plane_pyr[i] = nr_plane_pyr[i-1] * 2;
step_pyr[i] = alignSize(cols_pyr[i] * type_size, n) / type_size;
step_pyr[i] = alignSize(cols_pyr[i] * sizeof(T), n) / sizeof(T);
}
Size msg_size(step_pyr[0], rows * nr_plane_pyr[0]);
Size data_cost_size(step_pyr[0], rows * nr_plane_pyr[0] * 2);
u[0].create(msg_size, msg_type);
d[0].create(msg_size, msg_type);
l[0].create(msg_size, msg_type);
r[0].create(msg_size, msg_type);
u[0].create(msg_size, DataType<T>::type);
d[0].create(msg_size, DataType<T>::type);
l[0].create(msg_size, DataType<T>::type);
r[0].create(msg_size, DataType<T>::type);
u[1].create(msg_size, msg_type);
d[1].create(msg_size, msg_type);
l[1].create(msg_size, msg_type);
r[1].create(msg_size, msg_type);
u[1].create(msg_size, DataType<T>::type);
d[1].create(msg_size, DataType<T>::type);
l[1].create(msg_size, DataType<T>::type);
r[1].create(msg_size, DataType<T>::type);
disp_selected_pyr[0].create(msg_size, msg_type);
disp_selected_pyr[1].create(msg_size, msg_type);
disp_selected_pyr[0].create(msg_size, DataType<T>::type);
disp_selected_pyr[1].create(msg_size, DataType<T>::type);
data_cost.create(data_cost_size, msg_type);
data_cost_selected.create(msg_size, msg_type);
data_cost.create(data_cost_size, DataType<T>::type);
data_cost_selected.create(msg_size, DataType<T>::type);
step_pyr[0] = data_cost.step / type_size;
step_pyr[0] = data_cost.step / sizeof(T);
Size temp_size = data_cost_size;
if (data_cost_size.width * data_cost_size.height < static_cast<size_t>(step_pyr[levels - 1]) * rows_pyr[levels - 1] * ndisp)
{
temp_size = Size(step_pyr[levels - 1], rows_pyr[levels - 1] * ndisp);
}
if (data_cost_size.width * data_cost_size.height < step_pyr[levels - 1] * rows_pyr[levels - 1] * rthis.ndisp)
temp_size = Size(step_pyr[levels - 1], rows_pyr[levels - 1] * rthis.ndisp);
temp.create(temp_size, msg_type);
temp.create(temp_size, DataType<T>::type);
////////////////////////////////////////////////////////////////////////////
// Compute
csbp::load_constants(ndisp, max_data_term, scale * data_weight, scale * max_disc_term, scale * disc_single_jump, min_disp_th,
left, right, temp);
csbp::load_constants(rthis.ndisp, rthis.max_data_term, scale * rthis.data_weight,
scale * rthis.max_disc_term, scale * rthis.disc_single_jump, rthis.min_disp_th, left, right, temp);
l[0] = zero;
d[0] = zero;
@ -219,29 +225,28 @@ static void stereo_csbp_gpu_operator(int& ndisp, int& iters, int& levels, int& n
{
if (i == levels - 1)
{
csbp::init_data_cost(left.rows, left.cols, disp_selected_pyr[cur_idx], data_cost_selected,
step_pyr[i], msg_type, rows_pyr[i], cols_pyr[i], i, nr_plane_pyr[i], ndisp, left.channels(), stream);
csbp::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(), stream);
}
else
{
csbp::compute_data_cost(disp_selected_pyr[cur_idx], data_cost, step_pyr[i], step_pyr[i+1], msg_type,
csbp::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(), stream);
int new_idx = (cur_idx + 1) & 1;
csbp::init_message(u[new_idx], d[new_idx], l[new_idx], r[new_idx],
u[cur_idx], d[cur_idx], l[cur_idx], r[cur_idx],
disp_selected_pyr[new_idx], disp_selected_pyr[cur_idx],
data_cost_selected, data_cost, step_pyr[i], step_pyr[i+1], msg_type,
rows_pyr[i], cols_pyr[i], nr_plane_pyr[i],
rows_pyr[i+1], cols_pyr[i+1], nr_plane_pyr[i+1], stream);
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], stream);
cur_idx = new_idx;
}
csbp::calc_all_iterations(u[cur_idx], d[cur_idx], l[cur_idx], r[cur_idx],
data_cost_selected, disp_selected_pyr[cur_idx], step_pyr[i], msg_type,
rows_pyr[i], cols_pyr[i], nr_plane_pyr[i], iters, stream);
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, stream);
}
if (disp.empty())
@ -250,24 +255,31 @@ static void stereo_csbp_gpu_operator(int& ndisp, int& iters, int& levels, int& n
out = ((disp.type() == CV_16S) ? disp : GpuMat(rows, cols, CV_16S));
out = zero;
csbp::compute_disp(u[cur_idx], d[cur_idx], l[cur_idx], r[cur_idx],
data_cost_selected, disp_selected_pyr[cur_idx], step_pyr[0], msg_type, out, nr_plane_pyr[0], stream);
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], stream);
if (disp.type() != CV_16S)
out.convertTo(disp, disp.type());
}
typedef void (*csbp_operator_t)(StereoConstantSpaceBP& rthis, GpuMat u[2], GpuMat d[2], GpuMat l[2], GpuMat r[2],
GpuMat disp_selected_pyr[2], GpuMat& data_cost, GpuMat& data_cost_selected,
GpuMat& temp, GpuMat& out, const GpuMat& left, const GpuMat& right, GpuMat& disp,
cudaStream_t stream);
const static csbp_operator_t operators[] = {0, 0, 0, csbp_operator<short>, 0, csbp_operator<float>, 0, 0};
void cv::gpu::StereoConstantSpaceBP::operator()(const GpuMat& left, const GpuMat& right, GpuMat& disp)
{
::stereo_csbp_gpu_operator(ndisp, iters, levels, nr_plane, max_data_term, data_weight, max_disc_term, disc_single_jump, min_disp_th, msg_type,
u, d, l, r, disp_selected_pyr, data_cost, data_cost_selected, temp, out, left, right, disp, 0);
{
CV_Assert(msg_type == CV_32F || msg_type == CV_16S);
operators[msg_type](*this, u, d, l, r, disp_selected_pyr, data_cost, data_cost_selected, temp, out, left, right, disp, 0);
}
void cv::gpu::StereoConstantSpaceBP::operator()(const GpuMat& left, const GpuMat& right, GpuMat& disp, const Stream& stream)
{
::stereo_csbp_gpu_operator(ndisp, iters, levels, nr_plane, max_data_term, data_weight, max_disc_term, disc_single_jump, min_disp_th, msg_type,
u, d, l, r, disp_selected_pyr, data_cost, data_cost_selected, temp, out, left, right, disp,
StreamAccessor::getStream(stream));
void cv::gpu::StereoConstantSpaceBP::operator()(const GpuMat& left, const GpuMat& right, GpuMat& disp, Stream& stream)
{
CV_Assert(msg_type == CV_32F || msg_type == CV_16S);
operators[msg_type](*this, u, d, l, r, disp_selected_pyr, data_cost, data_cost_selected, temp, out, left, right, disp, StreamAccessor::getStream(stream));
}
#endif /* !defined (HAVE_CUDA) */

417
modules/gpu/src/cuda/constantspacebp.cu
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@ -74,7 +74,7 @@ struct TypeLimits<float>
/////////////////////// load constants ////////////////////////
///////////////////////////////////////////////////////////////
namespace csbp_kernels
namespace csbp_krnls
{
__constant__ int cndisp;
@ -101,20 +101,20 @@ namespace cv { namespace gpu { namespace csbp
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 DevMem2D& left, const DevMem2D& right, const DevMem2D& temp)
{
cudaSafeCall( cudaMemcpyToSymbol(csbp_kernels::cndisp, &ndisp, sizeof(int)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_krnls::cndisp, &ndisp, sizeof(int)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_kernels::cmax_data_term, &max_data_term, sizeof(float)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_kernels::cdata_weight, &data_weight, sizeof(float)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_kernels::cmax_disc_term, &max_disc_term, sizeof(float)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_kernels::cdisc_single_jump, &disc_single_jump, sizeof(float)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_krnls::cmax_data_term, &max_data_term, sizeof(float)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_krnls::cdata_weight, &data_weight, sizeof(float)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_krnls::cmax_disc_term, &max_disc_term, sizeof(float)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_krnls::cdisc_single_jump, &disc_single_jump, sizeof(float)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_kernels::cth, &min_disp_th, sizeof(int)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_krnls::cth, &min_disp_th, sizeof(int)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_kernels::cimg_step, &left.step, sizeof(size_t)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_krnls::cimg_step, &left.step, sizeof(size_t)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_kernels::cleft, &left.ptr, sizeof(left.ptr)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_kernels::cright, &right.ptr, sizeof(right.ptr)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_kernels::ctemp, &temp.ptr, sizeof(temp.ptr)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_krnls::cleft, &left.ptr, sizeof(left.ptr)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_krnls::cright, &right.ptr, sizeof(right.ptr)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_krnls::ctemp, &temp.ptr, sizeof(temp.ptr)) );
}
}}}
@ -122,7 +122,7 @@ namespace cv { namespace gpu { namespace csbp
/////////////////////// init data cost ////////////////////////
///////////////////////////////////////////////////////////////
namespace csbp_kernels
namespace csbp_krnls
{
template <int channels>
struct DataCostPerPixel
@ -306,7 +306,7 @@ namespace csbp_kernels
namespace cv { namespace gpu { namespace csbp
{
template <typename T>
void init_data_cost_caller_(int /*rows*/, int /*cols*/, int h, int w, int level, int /*ndisp*/, int channels, const cudaStream_t& stream)
void init_data_cost_caller_(int /*rows*/, int /*cols*/, int h, int w, int level, int /*ndisp*/, int channels, cudaStream_t stream)
{
dim3 threads(32, 8, 1);
dim3 grid(1, 1, 1);
@ -316,14 +316,14 @@ namespace cv { namespace gpu { namespace csbp
switch (channels)
{
case 1: csbp_kernels::init_data_cost<T, 1><<<grid, threads, 0, stream>>>(h, w, level); break;
case 3: csbp_kernels::init_data_cost<T, 3><<<grid, threads, 0, stream>>>(h, w, level); break;
case 1: csbp_krnls::init_data_cost<T, 1><<<grid, threads, 0, stream>>>(h, w, level); break;
case 3: csbp_krnls::init_data_cost<T, 3><<<grid, threads, 0, stream>>>(h, w, level); break;
default: cv::gpu::error("Unsupported channels count", __FILE__, __LINE__);
}
}
template <typename T, int winsz>
void init_data_cost_reduce_caller_(int rows, int cols, int h, int w, int level, int ndisp, int channels, const cudaStream_t& stream)
void init_data_cost_reduce_caller_(int rows, int cols, int h, int w, int level, int ndisp, int channels, cudaStream_t stream)
{
const int threadsNum = 256;
const size_t smem_size = threadsNum * sizeof(float);
@ -334,83 +334,64 @@ namespace cv { namespace gpu { namespace csbp
switch (channels)
{
case 1: csbp_kernels::init_data_cost_reduce<T, winsz, 1><<<grid, threads, smem_size, stream>>>(level, rows, cols, h); break;
case 3: csbp_kernels::init_data_cost_reduce<T, winsz, 3><<<grid, threads, smem_size, stream>>>(level, rows, cols, h); break;
case 1: csbp_krnls::init_data_cost_reduce<T, winsz, 1><<<grid, threads, smem_size, stream>>>(level, rows, cols, h); break;
case 3: csbp_krnls::init_data_cost_reduce<T, winsz, 3><<<grid, threads, smem_size, stream>>>(level, rows, cols, h); break;
default: cv::gpu::error("Unsupported channels count", __FILE__, __LINE__);
}
}
typedef void (*InitDataCostCaller)(int cols, int rows, int w, int h, int level, int ndisp, int channels, const cudaStream_t& stream);
template <typename T>
void get_first_k_initial_local_caller_(const DevMem2D& disp_selected_pyr, const DevMem2D& data_cost_selected, int h, int w, int nr_plane, const cudaStream_t& stream)
{
dim3 threads(32, 8, 1);
dim3 grid(1, 1, 1);
grid.x = divUp(w, threads.x);
grid.y = divUp(h, threads.y);
csbp_kernels::get_first_k_initial_local<T><<<grid, threads, 0, stream>>>((T*)data_cost_selected.ptr, (T*)disp_selected_pyr.ptr, h, w, nr_plane);
}
template<class T>
void init_data_cost_tmpl(int rows, int cols, T* disp_selected_pyr, T* data_cost_selected,
size_t msg_step, int h, int w, int level, int nr_plane, int ndisp, int channels, cudaStream_t stream)
{
typedef void (*GetFirstKInitialLocalCaller)(const DevMem2D& disp_selected_pyr, const DevMem2D& data_cost_selected, int h, int w, int nr_plane, const cudaStream_t& stream);
typedef void (*InitDataCostCaller)(int cols, int rows, int w, int h, int level, int ndisp, int channels, cudaStream_t stream);
void init_data_cost(int rows, int cols, const DevMem2D& disp_selected_pyr, const DevMem2D& data_cost_selected,
size_t msg_step, int msg_type, int h, int w, int level, int nr_plane, int ndisp, int channels, const cudaStream_t& stream)
{
static const InitDataCostCaller init_data_cost_callers[8][9] =
{
{0, 0, 0, 0, 0, 0, 0, 0, 0},
{0, 0, 0, 0, 0, 0, 0, 0, 0},
{0, 0, 0, 0, 0, 0, 0, 0, 0},
{init_data_cost_caller_<short>, init_data_cost_caller_<short>, init_data_cost_reduce_caller_<short, 4>,
init_data_cost_reduce_caller_<short, 8>, init_data_cost_reduce_caller_<short, 16>, init_data_cost_reduce_caller_<short, 32>,
init_data_cost_reduce_caller_<short, 64>, init_data_cost_reduce_caller_<short, 128>, init_data_cost_reduce_caller_<short, 256>},
{0, 0, 0, 0, 0, 0, 0, 0, 0},
{init_data_cost_caller_<float>, init_data_cost_caller_<float>, init_data_cost_reduce_caller_<float, 4>,
init_data_cost_reduce_caller_<float, 8>, init_data_cost_reduce_caller_<float, 16>, init_data_cost_reduce_caller_<float, 32>,
init_data_cost_reduce_caller_<float, 64>, init_data_cost_reduce_caller_<float, 128>, init_data_cost_reduce_caller_<float, 256>},
{0, 0, 0, 0, 0, 0, 0, 0, 0},
{0, 0, 0, 0, 0, 0, 0, 0, 0}
};
static const GetFirstKInitialLocalCaller get_first_k_initial_local_callers[8] =
{
0, 0, 0,
get_first_k_initial_local_caller_<short>,
0,
get_first_k_initial_local_caller_<float>,
0, 0
};
InitDataCostCaller init_data_cost_caller = init_data_cost_callers[msg_type][level];
GetFirstKInitialLocalCaller get_first_k_initial_local_caller = get_first_k_initial_local_callers[msg_type];
if (!init_data_cost_caller || !get_first_k_initial_local_caller)
cv::gpu::error("Unsupported message type or levels count", __FILE__, __LINE__);
static const InitDataCostCaller init_data_cost_callers[] =
{
init_data_cost_caller_<T>, init_data_cost_caller_<T>, init_data_cost_reduce_caller_<T, 4>,
init_data_cost_reduce_caller_<T, 8>, init_data_cost_reduce_caller_<T, 16>, init_data_cost_reduce_caller_<T, 32>,
init_data_cost_reduce_caller_<T, 64>, init_data_cost_reduce_caller_<T, 128>, init_data_cost_reduce_caller_<T, 256>
};
size_t disp_step = msg_step * h;
cudaSafeCall( cudaMemcpyToSymbol(csbp_kernels::cdisp_step1, &disp_step, sizeof(size_t)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_kernels::cmsg_step1, &msg_step, sizeof(size_t)) );
init_data_cost_caller(rows, cols, h, w, level, ndisp, channels, stream);
cudaSafeCall( cudaMemcpyToSymbol(csbp_krnls::cdisp_step1, &disp_step, sizeof(size_t)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_krnls::cmsg_step1, &msg_step, sizeof(size_t)) );
init_data_cost_callers[level](rows, cols, h, w, level, ndisp, channels, stream);
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
get_first_k_initial_local_caller(disp_selected_pyr, data_cost_selected, h, w, nr_plane, stream);
dim3 threads(32, 8, 1);
dim3 grid(1, 1, 1);
grid.x = divUp(w, threads.x);
grid.y = divUp(h, threads.y);
csbp_krnls::get_first_k_initial_local<<<grid, threads, 0, stream>>>(data_cost_selected, disp_selected_pyr, h, w, nr_plane);
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
}
void init_data_cost(int rows, int cols, short* disp_selected_pyr, short* data_cost_selected,
size_t msg_step, int h, int w, int level, int nr_plane, int ndisp, int channels, cudaStream_t stream)
{
init_data_cost_tmpl(rows, cols, disp_selected_pyr, data_cost_selected, msg_step, h, w, level, nr_plane, ndisp, channels, stream);
}
void init_data_cost(int rows, int cols, float* disp_selected_pyr, float* data_cost_selected,
size_t msg_step, int h, int w, int level, int nr_plane, int ndisp, int channels, cudaStream_t stream)
{
init_data_cost_tmpl(rows, cols, disp_selected_pyr, data_cost_selected, msg_step, h, w, level, nr_plane, ndisp, channels, stream);
}
}}}
///////////////////////////////////////////////////////////////
////////////////////// compute data cost //////////////////////
///////////////////////////////////////////////////////////////
namespace csbp_kernels
namespace csbp_krnls
{
template <typename T, int channels>
__global__ void compute_data_cost(const T* selected_disp_pyr, T* data_cost_, int h, int w, int level, int nr_plane)
@ -504,7 +485,7 @@ namespace csbp_kernels
__syncthreads();
if (winsz >= 256) { if (tid < 128) { dline[tid] += dline[tid + 128]; } __syncthreads(); }
if (winsz >= 128) { if (tid < 64) { dline[tid] += dline[tid + 64]; } __syncthreads(); }
if (winsz >= 128) { if (tid < 64) { dline[tid] += dline[tid + 64]; } __syncthreads(); }
if (winsz >= 64) if (tid < 32) dline[tid] += dline[tid + 32];
if (winsz >= 32) if (tid < 16) dline[tid] += dline[tid + 16];
@ -522,8 +503,8 @@ namespace csbp_kernels
namespace cv { namespace gpu { namespace csbp
{
template <typename T>
void compute_data_cost_caller_(const DevMem2D& disp_selected_pyr, const DevMem2D& data_cost, int /*rows*/, int /*cols*/,
int h, int w, int level, int nr_plane, int channels, const cudaStream_t& stream)
void compute_data_cost_caller_(const T* disp_selected_pyr, T* data_cost, int /*rows*/, int /*cols*/,
int h, int w, int level, int nr_plane, int channels, cudaStream_t stream)
{
dim3 threads(32, 8, 1);
dim3 grid(1, 1, 1);
@ -533,15 +514,15 @@ namespace cv { namespace gpu { namespace csbp
switch(channels)
{
case 1: csbp_kernels::compute_data_cost<T, 1><<<grid, threads, 0, stream>>>((const T*)disp_selected_pyr.ptr, (T*)data_cost.ptr, h, w, level, nr_plane); break;
case 3: csbp_kernels::compute_data_cost<T, 3><<<grid, threads, 0, stream>>>((const T*)disp_selected_pyr.ptr, (T*)data_cost.ptr, h, w, level, nr_plane); break;
case 1: csbp_krnls::compute_data_cost<T, 1><<<grid, threads, 0, stream>>>(disp_selected_pyr, data_cost, h, w, level, nr_plane); break;
case 3: csbp_krnls::compute_data_cost<T, 3><<<grid, threads, 0, stream>>>(disp_selected_pyr, data_cost, h, w, level, nr_plane); break;
default: cv::gpu::error("Unsupported channels count", __FILE__, __LINE__);
}
}
template <typename T, int winsz>
void compute_data_cost_reduce_caller_(const DevMem2D& disp_selected_pyr, const DevMem2D& data_cost, int rows, int cols,
int h, int w, int level, int nr_plane, int channels, const cudaStream_t& stream)
void compute_data_cost_reduce_caller_(const T* disp_selected_pyr, T* data_cost, int rows, int cols,
int h, int w, int level, int nr_plane, int channels, cudaStream_t stream)
{
const int threadsNum = 256;
const size_t smem_size = threadsNum * sizeof(float);
@ -552,57 +533,58 @@ namespace cv { namespace gpu { namespace csbp
switch (channels)
{
case 1: csbp_kernels::compute_data_cost_reduce<T, winsz, 1><<<grid, threads, smem_size, stream>>>((const T*)disp_selected_pyr.ptr, (T*)data_cost.ptr, level, rows, cols, h, nr_plane); break;
case 3: csbp_kernels::compute_data_cost_reduce<T, winsz, 3><<<grid, threads, smem_size, stream>>>((const T*)disp_selected_pyr.ptr, (T*)data_cost.ptr, level, rows, cols, h, nr_plane); break;
case 1: csbp_krnls::compute_data_cost_reduce<T, winsz, 1><<<grid, threads, smem_size, stream>>>(disp_selected_pyr, data_cost, level, rows, cols, h, nr_plane); break;
case 3: csbp_krnls::compute_data_cost_reduce<T, winsz, 3><<<grid, threads, smem_size, stream>>>(disp_selected_pyr, data_cost, level, rows, cols, h, nr_plane); break;
default: cv::gpu::error("Unsupported channels count", __FILE__, __LINE__);
}
}
typedef void (*ComputeDataCostCaller)(const DevMem2D& disp_selected_pyr, const DevMem2D& data_cost, int rows, int cols,
int h, int w, int level, int nr_plane, int channels, const cudaStream_t& stream);
void compute_data_cost(const DevMem2D& disp_selected_pyr, const DevMem2D& data_cost, size_t msg_step1, size_t msg_step2, int msg_type,
int rows, int cols, int h, int w, int h2, int level, int nr_plane, int channels, const cudaStream_t& stream)
template<class T>
void compute_data_cost_tmpl(const T* disp_selected_pyr, T* data_cost, size_t msg_step1, size_t msg_step2,
int rows, int cols, int h, int w, int h2, int level, int nr_plane, int channels, cudaStream_t stream)
{
static const ComputeDataCostCaller callers[8][9] =
{
{0, 0, 0, 0, 0, 0, 0, 0, 0},
{0, 0, 0, 0, 0, 0, 0, 0, 0},
{0, 0, 0, 0, 0, 0, 0, 0, 0},
{compute_data_cost_caller_<short>, compute_data_cost_caller_<short>, compute_data_cost_reduce_caller_<short, 4>,
compute_data_cost_reduce_caller_<short, 8>, compute_data_cost_reduce_caller_<short, 16>, compute_data_cost_reduce_caller_<short, 32>,
compute_data_cost_reduce_caller_<short, 64>, compute_data_cost_reduce_caller_<short, 128>, compute_data_cost_reduce_caller_<short, 256>},
{0, 0, 0, 0, 0, 0, 0, 0, 0},
{compute_data_cost_caller_<float>, compute_data_cost_caller_<float>, compute_data_cost_reduce_caller_<float, 4>,
compute_data_cost_reduce_caller_<float, 8>, compute_data_cost_reduce_caller_<float, 16>, compute_data_cost_reduce_caller_<float, 32>,
compute_data_cost_reduce_caller_<float, 64>, compute_data_cost_reduce_caller_<float, 128>, compute_data_cost_reduce_caller_<float, 256>},
{0, 0, 0, 0, 0, 0, 0, 0, 0},
{0, 0, 0, 0, 0, 0, 0, 0, 0}
};
typedef void (*ComputeDataCostCaller)(const T* disp_selected_pyr, T* data_cost, int rows, int cols,
int h, int w, int level, int nr_plane, int channels, cudaStream_t stream);
static const ComputeDataCostCaller callers[] =
{
compute_data_cost_caller_<T>, compute_data_cost_caller_<T>, compute_data_cost_reduce_caller_<T, 4>,
compute_data_cost_reduce_caller_<T, 8>, compute_data_cost_reduce_caller_<T, 16>, compute_data_cost_reduce_caller_<T, 32>,
compute_data_cost_reduce_caller_<T, 64>, compute_data_cost_reduce_caller_<T, 128>, compute_data_cost_reduce_caller_<T, 256>
};
size_t disp_step1 = msg_step1 * h;
size_t disp_step2 = msg_step2 * h2;
cudaSafeCall( cudaMemcpyToSymbol(csbp_kernels::cdisp_step1, &disp_step1, sizeof(size_t)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_kernels::cdisp_step2, &disp_step2, sizeof(size_t)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_kernels::cmsg_step1, &msg_step1, sizeof(size_t)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_kernels::cmsg_step2, &msg_step2, sizeof(size_t)) );
ComputeDataCostCaller caller = callers[msg_type][level];
if (!caller)
cv::gpu::error("Unsopported message type", __FILE__, __LINE__);
cudaSafeCall( cudaMemcpyToSymbol(csbp_krnls::cdisp_step1, &disp_step1, sizeof(size_t)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_krnls::cdisp_step2, &disp_step2, sizeof(size_t)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_krnls::cmsg_step1, &msg_step1, sizeof(size_t)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_krnls::cmsg_step2, &msg_step2, sizeof(size_t)) );
caller(disp_selected_pyr, data_cost, rows, cols, h, w, level, nr_plane, channels, stream);
callers[level](disp_selected_pyr, data_cost, rows, cols, h, w, level, nr_plane, channels, stream);
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
}
void compute_data_cost(const short* disp_selected_pyr, short* data_cost, size_t msg_step1, size_t msg_step2,
int rows, int cols, int h, int w, int h2, int level, int nr_plane, int channels, cudaStream_t stream)
{
compute_data_cost_tmpl(disp_selected_pyr, data_cost, msg_step1, msg_step2, rows, cols, h, w, h2, level, nr_plane, channels, stream);
}
void compute_data_cost(const float* disp_selected_pyr, float* data_cost, size_t msg_step1, size_t msg_step2,
int rows, int cols, int h, int w, int h2, int level, int nr_plane, int channels, cudaStream_t stream)
{
compute_data_cost_tmpl(disp_selected_pyr, data_cost, msg_step1, msg_step2, rows, cols, h, w, h2, level, nr_plane, channels, stream);
}
}}}
///////////////////////////////////////////////////////////////
//////////////////////// init message /////////////////////////
///////////////////////////////////////////////////////////////
namespace csbp_kernels
namespace csbp_krnls
{
template <typename T>
__device__ void get_first_k_element_increase(T* u_new, T* d_new, T* l_new, T* r_new,
@ -641,7 +623,7 @@ namespace csbp_kernels
__global__ void init_message(T* u_new_, T* d_new_, T* l_new_, T* r_new_,
const T* u_cur_, const T* d_cur_, const T* l_cur_, const T* r_cur_,
T* selected_disp_pyr_new, const T* selected_disp_pyr_cur,
T* data_cost_selected_, T* data_cost_,
T* data_cost_selected_, const T* data_cost_,
int h, int w, int nr_plane, int h2, int w2, int nr_plane2)
{
int x = blockIdx.x * blockDim.x + threadIdx.x;
@ -657,7 +639,7 @@ namespace csbp_kernels
T* data_cost_new = (T*)ctemp + y * cmsg_step1 + x;
const T* disparity_selected_cur = selected_disp_pyr_cur + y/2 * cmsg_step2 + x/2;
T* data_cost = data_cost_ + y * cmsg_step1 + x;
const T* data_cost = data_cost_ + y * cmsg_step1 + x;
for(int d = 0; d < nr_plane2; d++)
{
@ -689,72 +671,65 @@ namespace csbp_kernels
namespace cv { namespace gpu { namespace csbp
{
template <typename T>
void init_message_caller_(const DevMem2D& u_new, const DevMem2D& d_new, const DevMem2D& l_new, const DevMem2D& r_new,
const DevMem2D& u_cur, const DevMem2D& d_cur, const DevMem2D& l_cur, const DevMem2D& r_cur,
const DevMem2D& selected_disp_pyr_new, const DevMem2D& selected_disp_pyr_cur,
const DevMem2D& data_cost_selected, const DevMem2D& data_cost,
int h, int w, int nr_plane, int h2, int w2, int nr_plane2, const cudaStream_t& stream)
{
template<class T>
void init_message_tmpl(T* u_new, T* d_new, T* l_new, T* r_new,
const T* u_cur, const T* d_cur, const T* l_cur, const T* r_cur,
T* selected_disp_pyr_new, const T* selected_disp_pyr_cur,
T* data_cost_selected, const T* data_cost, size_t msg_step1, size_t msg_step2,
int h, int w, int nr_plane, int h2, int w2, int nr_plane2, cudaStream_t stream)
{
size_t disp_step1 = msg_step1 * h;
size_t disp_step2 = msg_step2 * h2;
cudaSafeCall( cudaMemcpyToSymbol(csbp_krnls::cdisp_step1, &disp_step1, sizeof(size_t)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_krnls::cdisp_step2, &disp_step2, sizeof(size_t)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_krnls::cmsg_step1, &msg_step1, sizeof(size_t)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_krnls::cmsg_step2, &msg_step2, sizeof(size_t)) );
dim3 threads(32, 8, 1);
dim3 grid(1, 1, 1);
grid.x = divUp(w, threads.x);
grid.y = divUp(h, threads.y);
csbp_kernels::init_message<T><<<grid, threads, 0, stream>>>((T*)u_new.ptr, (T*)d_new.ptr, (T*)l_new.ptr, (T*)r_new.ptr,
(const T*)u_cur.ptr, (const T*)d_cur.ptr, (const T*)l_cur.ptr, (const T*)r_cur.ptr,
(T*)selected_disp_pyr_new.ptr, (const T*)selected_disp_pyr_cur.ptr,
(T*)data_cost_selected.ptr, (T*)data_cost.ptr,
h, w, nr_plane, h2, w2, nr_plane2);
}
grid.y = divUp(h, threads.y);
typedef void (*InitMessageCaller)(const DevMem2D& u_new, const DevMem2D& d_new, const DevMem2D& l_new, const DevMem2D& r_new,
const DevMem2D& u_cur, const DevMem2D& d_cur, const DevMem2D& l_cur, const DevMem2D& r_cur,
const DevMem2D& selected_disp_pyr_new, const DevMem2D& selected_disp_pyr_cur,
const DevMem2D& data_cost_selected, const DevMem2D& data_cost,
int h, int w, int nr_plane, int h2, int w2, int nr_plane2, const cudaStream_t& stream);
void init_message(const DevMem2D& u_new, const DevMem2D& d_new, const DevMem2D& l_new, const DevMem2D& r_new,
const DevMem2D& u_cur, const DevMem2D& d_cur, const DevMem2D& l_cur, const DevMem2D& r_cur,
const DevMem2D& selected_disp_pyr_new, const DevMem2D& selected_disp_pyr_cur,
const DevMem2D& data_cost_selected, const DevMem2D& data_cost, size_t msg_step1, size_t msg_step2, int msg_type,
int h, int w, int nr_plane, int h2, int w2, int nr_plane2, const cudaStream_t& stream)
{
static const InitMessageCaller callers[8] =
{
0, 0, 0,
init_message_caller_<short>,
0,
init_message_caller_<float>,
0, 0
};
size_t disp_step1 = msg_step1 * h;
size_t disp_step2 = msg_step2 * h2;
cudaSafeCall( cudaMemcpyToSymbol(csbp_kernels::cdisp_step1, &disp_step1, sizeof(size_t)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_kernels::cdisp_step2, &disp_step2, sizeof(size_t)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_kernels::cmsg_step1, &msg_step1, sizeof(size_t)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_kernels::cmsg_step2, &msg_step2, sizeof(size_t)) );
InitMessageCaller caller = callers[msg_type];
if (!caller)
cv::gpu::error("Unsupported message type", __FILE__, __LINE__);
caller(u_new, d_new, l_new, r_new, u_cur, d_cur, l_cur, r_cur,
selected_disp_pyr_new, selected_disp_pyr_cur, data_cost_selected, data_cost,
h, w, nr_plane, h2, w2, nr_plane2, stream);
csbp_krnls::init_message<<<grid, threads, 0, stream>>>(u_new, d_new, l_new, r_new,
u_cur, d_cur, l_cur, r_cur,
selected_disp_pyr_new, selected_disp_pyr_cur,
data_cost_selected, data_cost,
h, w, nr_plane, h2, w2, nr_plane2);
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
}
void init_message(short* u_new, short* d_new, short* l_new, short* r_new,
const short* u_cur, const short* d_cur, const short* l_cur, const short* r_cur,
short* selected_disp_pyr_new, const short* selected_disp_pyr_cur,
short* data_cost_selected, const short* data_cost, size_t msg_step1, size_t msg_step2,
int h, int w, int nr_plane, int h2, int w2, int nr_plane2, cudaStream_t stream)
{
init_message_tmpl(u_new, d_new, l_new, r_new, u_cur, d_cur, l_cur, r_cur,
selected_disp_pyr_new, selected_disp_pyr_cur, data_cost_selected, data_cost, msg_step1, msg_step2,
h, w, nr_plane, h2, w2, nr_plane2, stream);
}
void init_message(float* u_new, float* d_new, float* l_new, float* r_new,
const float* u_cur, const float* d_cur, const float* l_cur, const float* r_cur,
float* selected_disp_pyr_new, const float* selected_disp_pyr_cur,
float* data_cost_selected, const float* data_cost, size_t msg_step1, size_t msg_step2,
int h, int w, int nr_plane, int h2, int w2, int nr_plane2, cudaStream_t stream)
{
init_message_tmpl(u_new, d_new, l_new, r_new, u_cur, d_cur, l_cur, r_cur,
selected_disp_pyr_new, selected_disp_pyr_cur, data_cost_selected, data_cost, msg_step1, msg_step2,
h, w, nr_plane, h2, w2, nr_plane2, stream);
}
}}}
///////////////////////////////////////////////////////////////
//////////////////// calc all iterations /////////////////////
///////////////////////////////////////////////////////////////
namespace csbp_kernels
namespace csbp_krnls
{
template <typename T>
__device__ void message_per_pixel(const T* data, T* msg_dst, const T* msg1, const T* msg2, const T* msg3,
@ -792,8 +767,7 @@ namespace csbp_kernels
}
template <typename T>
__global__ void compute_message(T* u_, T* d_, T* l_, T* r_, const T* data_cost_selected, const T* selected_disp_pyr_cur,
int h, int w, int nr_plane, int i)
__global__ void compute_message(T* u_, T* d_, T* l_, T* r_, const T* data_cost_selected, const T* selected_disp_pyr_cur, int h, int w, int nr_plane, int i)
{
int y = blockIdx.y * blockDim.y + threadIdx.y;
int x = ((blockIdx.x * blockDim.x + threadIdx.x) << 1) + ((y + i) & 1);
@ -821,59 +795,48 @@ namespace csbp_kernels
namespace cv { namespace gpu { namespace csbp
{
template <typename T>
void compute_message_caller_(const DevMem2D& u, const DevMem2D& d, const DevMem2D& l, const DevMem2D& r, const DevMem2D& data_cost_selected,
const DevMem2D& selected_disp_pyr_cur, int h, int w, int nr_plane, int t, const cudaStream_t& stream)
{
template<class T>
void calc_all_iterations_tmpl(T* u, T* d, T* l, T* r, const T* data_cost_selected,
const T* selected_disp_pyr_cur, size_t msg_step, int h, int w, int nr_plane, int iters, cudaStream_t stream)
{
size_t disp_step = msg_step * h;
cudaSafeCall( cudaMemcpyToSymbol(csbp_krnls::cdisp_step1, &disp_step, sizeof(size_t)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_krnls::cmsg_step1, &msg_step, sizeof(size_t)) );
dim3 threads(32, 8, 1);
dim3 grid(1, 1, 1);
grid.x = divUp(w, threads.x << 1);
grid.y = divUp(h, threads.y);
csbp_kernels::compute_message<T><<<grid, threads, 0, stream>>>((T*)u.ptr, (T*)d.ptr, (T*)l.ptr, (T*)r.ptr,
(const T*)data_cost_selected.ptr, (const T*)selected_disp_pyr_cur.ptr,
h, w, nr_plane, t & 1);
}
typedef void (*ComputeMessageCaller)(const DevMem2D& u, const DevMem2D& d, const DevMem2D& l, const DevMem2D& r, const DevMem2D& data_cost_selected,
const DevMem2D& selected_disp_pyr_cur, int h, int w, int nr_plane, int t, const cudaStream_t& stream);
void calc_all_iterations(const DevMem2D& u, const DevMem2D& d, const DevMem2D& l, const DevMem2D& r, const DevMem2D& data_cost_selected,
const DevMem2D& selected_disp_pyr_cur, size_t msg_step, int msg_type, int h, int w, int nr_plane, int iters, const cudaStream_t& stream)
{
static const ComputeMessageCaller callers[8] =
{
0, 0, 0,
compute_message_caller_<short>,
0,
compute_message_caller_<float>,
0, 0
};
size_t disp_step = msg_step * h;
cudaSafeCall( cudaMemcpyToSymbol(csbp_kernels::cdisp_step1, &disp_step, sizeof(size_t)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_kernels::cmsg_step1, &msg_step, sizeof(size_t)) );
ComputeMessageCaller caller = callers[msg_type];
if (!caller)
cv::gpu::error("Unsupported message type", __FILE__, __LINE__);
for(int t = 0; t < iters; ++t)
{
caller(u, d, l, r, data_cost_selected, selected_disp_pyr_cur, h, w, nr_plane, t, stream);
csbp_krnls::compute_message<<<grid, threads, 0, stream>>>(u, d, l, r, data_cost_selected, selected_disp_pyr_cur, h, w, nr_plane, t & 1);
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
}
};
void calc_all_iterations(short* u, short* d, short* l, short* r, short* data_cost_selected,
const short* selected_disp_pyr_cur, size_t msg_step, int h, int w, int nr_plane, int iters, cudaStream_t stream)
{
calc_all_iterations_tmpl(u, d, l, r, data_cost_selected, selected_disp_pyr_cur, msg_step, h, w, nr_plane, iters, stream);
}
void calc_all_iterations(float*u, float* d, float* l, float* r, float* data_cost_selected,
const float* selected_disp_pyr_cur, size_t msg_step, int h, int w, int nr_plane, int iters, cudaStream_t stream)
{
calc_all_iterations_tmpl(u, d, l, r, data_cost_selected, selected_disp_pyr_cur, msg_step, h, w, nr_plane, iters, stream);
}
}}}
///////////////////////////////////////////////////////////////
/////////////////////////// output ////////////////////////////
///////////////////////////////////////////////////////////////
namespace csbp_kernels
namespace csbp_krnls
{
template <typename T>
__global__ void compute_disp(const T* u_, const T* d_, const T* l_, const T* r_,
@ -906,7 +869,6 @@ namespace csbp_kernels
best = saturate_cast<short>(disp_selected[idx]);
}
}
disp[res_step * y + x] = best;
}
}
@ -914,47 +876,36 @@ namespace csbp_kernels
namespace cv { namespace gpu { namespace csbp
{
template <typename T>
void compute_disp_caller_(const DevMem2D& u, const DevMem2D& d, const DevMem2D& l, const DevMem2D& r, const DevMem2D& data_cost_selected,
const DevMem2D& disp_selected, const DevMem2D& disp, int nr_plane, const cudaStream_t& stream)
{
template<class T>
void compute_disp_tmpl(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)
{
size_t disp_step = disp.rows * msg_step;
cudaSafeCall( cudaMemcpyToSymbol(csbp_krnls::cdisp_step1, &disp_step, sizeof(size_t)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_krnls::cmsg_step1, &msg_step, sizeof(size_t)) );
dim3 threads(32, 8, 1);
dim3 grid(1, 1, 1);
grid.x = divUp(disp.cols, threads.x);
grid.y = divUp(disp.rows, threads.y);
csbp_kernels::compute_disp<T><<<grid, threads, 0, stream>>>((const T*)u.ptr, (const T*)d.ptr, (const T*)l.ptr, (const T*)r.ptr,
(const T*)data_cost_selected.ptr, (const T*)disp_selected.ptr,
(short*)disp.ptr, disp.step / sizeof(short), disp.cols, disp.rows, nr_plane);
csbp_krnls::compute_disp<<<grid, threads, 0, stream>>>(u, d, l, r, data_cost_selected, disp_selected,
disp.ptr, disp.step / disp.elemSize(), disp.cols, disp.rows, nr_plane);
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
}
typedef void (*ComputeDispCaller)(const DevMem2D& u, const DevMem2D& d, const DevMem2D& l, const DevMem2D& r, const DevMem2D& data_cost_selected,
const DevMem2D& disp_selected, const DevMem2D& disp, int nr_plane, const cudaStream_t& stream);
void compute_disp(const DevMem2D& u, const DevMem2D& d, const DevMem2D& l, const DevMem2D& r, const DevMem2D& data_cost_selected,
const DevMem2D& disp_selected, size_t msg_step, int msg_type, const DevMem2D& disp, int nr_plane, const cudaStream_t& stream)
void compute_disp(const short* u, const short* d, const short* l, const short* r, const short* data_cost_selected, const short* disp_selected, size_t msg_step,
DevMem2D_<short> disp, int nr_plane, cudaStream_t stream)
{
static const ComputeDispCaller callers[8] =
{
0, 0, 0,
compute_disp_caller_<short>,
0,
compute_disp_caller_<float>,
0, 0
};
size_t disp_step = disp.rows * msg_step;
cudaSafeCall( cudaMemcpyToSymbol(csbp_kernels::cdisp_step1, &disp_step, sizeof(size_t)) );
cudaSafeCall( cudaMemcpyToSymbol(csbp_kernels::cmsg_step1, &msg_step, sizeof(size_t)) );
ComputeDispCaller caller = callers[msg_type];
if (!caller)
cv::gpu::error("Unsupported message type", __FILE__, __LINE__);
caller(u, d, l, r, data_cost_selected, disp_selected, disp, nr_plane, stream);
compute_disp_tmpl(u, d, l, r, data_cost_selected, disp_selected, msg_step, disp, nr_plane, stream);
}
if (stream == 0)
cudaSafeCall( cudaThreadSynchronize() );
void compute_disp(const float* u, const float* d, const float* l, const float* r, const float* data_cost_selected, const float* disp_selected, size_t msg_step,
DevMem2D_<short> disp, int nr_plane, cudaStream_t stream)
{
compute_disp_tmpl(u, d, l, r, data_cost_selected, disp_selected, msg_step, disp, nr_plane, stream);
}
}}}
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