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refactored StereoConstantSpaceBP

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pull/1014/head
Vladislav Vinogradov 12 years ago
parent d0e89337da
commit be9bb8f18b
6 changed files with 274 additions and 206 deletions
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  1. 63
      modules/gpustereo/include/opencv2/gpustereo.hpp
  2. 4
      modules/gpustereo/perf/perf_stereo.cpp
  3. 1
      modules/gpustereo/src/precomp.hpp
  4. 378
      modules/gpustereo/src/stereocsbp.cpp
  5. 4
      modules/gpustereo/test/test_stereo.cpp
  6. 30
      samples/gpu/stereo_match.cpp

63
modules/gpustereo/include/opencv2/gpustereo.hpp
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@ -112,63 +112,30 @@ public:
CV_EXPORTS Ptr<gpu::StereoBeliefPropagation>
createStereoBeliefPropagation(int ndisp = 64, int iters = 5, int levels = 5, int msg_type = CV_32F);
/////////////////////////////////////////
// StereoConstantSpaceBP
// "A Constant-Space Belief Propagation Algorithm for Stereo Matching"
// Qingxiong Yang, Liang Wang, Narendra Ahuja
// http://vision.ai.uiuc.edu/~qyang6/
class CV_EXPORTS StereoConstantSpaceBP
//! "A Constant-Space Belief Propagation Algorithm for Stereo Matching"
//! Qingxiong Yang, Liang Wang, Narendra Ahuja
//! http://vision.ai.uiuc.edu/~qyang6/
class CV_EXPORTS StereoConstantSpaceBP : public gpu::StereoBeliefPropagation
{
public:
enum { DEFAULT_NDISP = 128 };
enum { DEFAULT_ITERS = 8 };
enum { DEFAULT_LEVELS = 4 };
enum { DEFAULT_NR_PLANE = 4 };
static void estimateRecommendedParams(int width, int height, int& ndisp, int& iters, int& levels, int& nr_plane);
//! the default constructor
explicit StereoConstantSpaceBP(int ndisp = DEFAULT_NDISP,
int iters = DEFAULT_ITERS,
int levels = DEFAULT_LEVELS,
int nr_plane = DEFAULT_NR_PLANE,
int msg_type = CV_32F);
//! the full constructor taking the number of disparities, number of BP iterations on each level,
//! number of levels, number of active disparity on the first level, truncation of data cost, data weight,
//! truncation of discontinuity cost, discontinuity single jump and minimum disparity threshold
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 = 0,
int msg_type = CV_32F);
//! the stereo correspondence operator. Finds the disparity for the specified rectified stereo pair,
//! if disparity is empty output type will be CV_16S else output type will be disparity.type().
void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream = Stream::Null());
//! number of active disparity on the first level
virtual int getNrPlane() const = 0;
virtual void setNrPlane(int nr_plane) = 0;
int ndisp;
int iters;
int levels;
int nr_plane;
virtual bool getUseLocalInitDataCost() const = 0;
virtual void setUseLocalInitDataCost(bool use_local_init_data_cost) = 0;
float max_data_term;
float data_weight;
float max_disc_term;
float disc_single_jump;
static void estimateRecommendedParams(int width, int height, int& ndisp, int& iters, int& levels, int& nr_plane);
};
int min_disp_th;
CV_EXPORTS Ptr<gpu::StereoConstantSpaceBP>
createStereoConstantSpaceBP(int ndisp = 128, int iters = 8, int levels = 4, int nr_plane = 4, int msg_type = CV_32F);
int msg_type;
bool use_local_init_data_cost;
private:
GpuMat messages_buffers;
GpuMat temp;
GpuMat out;
};
// Disparity map refinement using joint bilateral filtering given a single color image.
// Qingxiong Yang, Liang Wang, Narendra Ahuja

4
modules/gpustereo/perf/perf_stereo.cpp
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@ -141,13 +141,13 @@ PERF_TEST_P(ImagePair, StereoConstantSpaceBP,
if (PERF_RUN_GPU())
{
cv::gpu::StereoConstantSpaceBP d_csbp(ndisp);
cv::Ptr<cv::gpu::StereoConstantSpaceBP> d_csbp = cv::gpu::createStereoConstantSpaceBP(ndisp);
const cv::gpu::GpuMat d_imgLeft(imgLeft);
const cv::gpu::GpuMat d_imgRight(imgRight);
cv::gpu::GpuMat dst;
TEST_CYCLE() d_csbp(d_imgLeft, d_imgRight, dst);
TEST_CYCLE() d_csbp->compute(d_imgLeft, d_imgRight, dst);
GPU_SANITY_CHECK(dst);
}

1
modules/gpustereo/src/precomp.hpp
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@ -48,5 +48,6 @@
#include "opencv2/gpustereo.hpp"
#include "opencv2/core/private.gpu.hpp"
#include "opencv2/core/utility.hpp"
#endif /* __OPENCV_PRECOMP_H__ */

378
modules/gpustereo/src/stereocsbp.cpp
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@ -49,13 +49,9 @@ using namespace cv::gpu;
void cv::gpu::StereoConstantSpaceBP::estimateRecommendedParams(int, int, int&, int&, int&, int&) { throw_no_cuda(); }
cv::gpu::StereoConstantSpaceBP::StereoConstantSpaceBP(int, int, int, int, int) { throw_no_cuda(); }
cv::gpu::StereoConstantSpaceBP::StereoConstantSpaceBP(int, int, int, int, float, float, float, float, int, int) { throw_no_cuda(); }
void cv::gpu::StereoConstantSpaceBP::operator()(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_no_cuda(); }
Ptr<gpu::StereoConstantSpaceBP> cv::gpu::createStereoConstantSpaceBP(int, int, int, int, int) { throw_no_cuda(); return Ptr<gpu::StereoConstantSpaceBP>(); }
#else /* !defined (HAVE_CUDA) */
#include "opencv2/core/utility.hpp"
namespace cv { namespace gpu { namespace cudev
{
@ -89,199 +85,303 @@ namespace cv { namespace gpu { namespace cudev
}
}}}
using namespace ::cv::gpu::cudev::stereocsbp;
namespace
{
const float DEFAULT_MAX_DATA_TERM = 30.0f;
const float DEFAULT_DATA_WEIGHT = 1.0f;
const float DEFAULT_MAX_DISC_TERM = 160.0f;
const float DEFAULT_DISC_SINGLE_JUMP = 10.0f;
}
class StereoCSBPImpl : public gpu::StereoConstantSpaceBP
{
public:
StereoCSBPImpl(int ndisp, int iters, int levels, int nr_plane, int msg_type);
void cv::gpu::StereoConstantSpaceBP::estimateRecommendedParams(int width, int height, int& ndisp, int& iters, int& levels, int& nr_plane)
{
ndisp = (int) ((float) width / 3.14f);
if ((ndisp & 1) != 0)
ndisp++;
void compute(InputArray left, InputArray right, OutputArray disparity);
void compute(InputArray left, InputArray right, OutputArray disparity, Stream& stream);
void compute(InputArray data, OutputArray disparity, Stream& stream);
int mm = std::max(width, height);
iters = mm / 100 + ((mm > 1200)? - 4 : 4);
int getMinDisparity() const { return min_disp_th_; }
void setMinDisparity(int minDisparity) { min_disp_th_ = minDisparity; }
levels = (int)::log(static_cast<double>(mm)) * 2 / 3;
if (levels == 0) levels++;
int getNumDisparities() const { return ndisp_; }
void setNumDisparities(int numDisparities) { ndisp_ = numDisparities; }
nr_plane = (int) ((float) ndisp / std::pow(2.0, levels + 1));
}
int getBlockSize() const { return 0; }
void setBlockSize(int /*blockSize*/) {}
cv::gpu::StereoConstantSpaceBP::StereoConstantSpaceBP(int ndisp_, int iters_, int levels_, int nr_plane_,
int msg_type_)
int getSpeckleWindowSize() const { return 0; }
void setSpeckleWindowSize(int /*speckleWindowSize*/) {}
: 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_), use_local_init_data_cost(true)
{
CV_Assert(msg_type_ == CV_32F || msg_type_ == CV_16S);
}
int getSpeckleRange() const { return 0; }
void setSpeckleRange(int /*speckleRange*/) {}
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_)
: 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_), use_local_init_data_cost(true)
{
CV_Assert(msg_type_ == CV_32F || msg_type_ == CV_16S);
}
int getDisp12MaxDiff() const { return 0; }
void setDisp12MaxDiff(int /*disp12MaxDiff*/) {}
template<class T>
static void csbp_operator(StereoConstantSpaceBP& rthis, GpuMat& mbuf, GpuMat& temp, GpuMat& out, const GpuMat& left, const GpuMat& right, GpuMat& disp, Stream& stream)
{
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());
int getNumIters() const { return iters_; }
void setNumIters(int iters) { iters_ = iters; }
int getNumLevels() const { return levels_; }
void setNumLevels(int levels) { levels_ = levels; }
double getMaxDataTerm() const { return max_data_term_; }
void setMaxDataTerm(double max_data_term) { max_data_term_ = (float) max_data_term; }
double getDataWeight() const { return data_weight_; }
void setDataWeight(double data_weight) { data_weight_ = (float) data_weight; }
double getMaxDiscTerm() const { return max_disc_term_; }
void setMaxDiscTerm(double max_disc_term) { max_disc_term_ = (float) max_disc_term; }
CV_Assert(rthis.levels <= 8 && (left.type() == CV_8UC1 || left.type() == CV_8UC3 || left.type() == CV_8UC4));
double getDiscSingleJump() const { return disc_single_jump_; }
void setDiscSingleJump(double disc_single_jump) { disc_single_jump_ = (float) disc_single_jump; }
const Scalar zero = Scalar::all(0);
int getMsgType() const { return msg_type_; }
void setMsgType(int msg_type) { msg_type_ = msg_type; }
cudaStream_t cudaStream = StreamAccessor::getStream(stream);
int getNrPlane() const { return nr_plane_; }
void setNrPlane(int nr_plane) { nr_plane_ = nr_plane; }
////////////////////////////////////////////////////////////////////////////////////////////
// Init
bool getUseLocalInitDataCost() const { return use_local_init_data_cost_; }
void setUseLocalInitDataCost(bool use_local_init_data_cost) { use_local_init_data_cost_ = use_local_init_data_cost; }
int rows = left.rows;
int cols = left.cols;
private:
int min_disp_th_;
int ndisp_;
int iters_;
int levels_;
float max_data_term_;
float data_weight_;
float max_disc_term_;
float disc_single_jump_;
int msg_type_;
int nr_plane_;
bool use_local_init_data_cost_;
rthis.levels = std::min(rthis.levels, int(log((double)rthis.ndisp) / log(2.0)));
int levels = rthis.levels;
GpuMat mbuf_;
GpuMat temp_;
GpuMat outBuf_;
};
// compute sizes
AutoBuffer<int> buf(levels * 3);
int* cols_pyr = buf;
int* rows_pyr = cols_pyr + levels;
int* nr_plane_pyr = rows_pyr + levels;
const float DEFAULT_MAX_DATA_TERM = 30.0f;
const float DEFAULT_DATA_WEIGHT = 1.0f;
const float DEFAULT_MAX_DISC_TERM = 160.0f;
const float DEFAULT_DISC_SINGLE_JUMP = 10.0f;
cols_pyr[0] = cols;
rows_pyr[0] = rows;
nr_plane_pyr[0] = rthis.nr_plane;
StereoCSBPImpl::StereoCSBPImpl(int ndisp, int iters, int levels, int nr_plane, int msg_type) :
min_disp_th_(0), ndisp_(ndisp), iters_(iters), levels_(levels),
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),
msg_type_(msg_type), nr_plane_(nr_plane), use_local_init_data_cost_(true)
{
}
for (int i = 1; i < levels; i++)
void StereoCSBPImpl::compute(InputArray left, InputArray right, OutputArray disparity)
{
cols_pyr[i] = cols_pyr[i-1] / 2;
rows_pyr[i] = rows_pyr[i-1] / 2;
nr_plane_pyr[i] = nr_plane_pyr[i-1] * 2;
compute(left, right, disparity, Stream::Null());
}
void StereoCSBPImpl::compute(InputArray _left, InputArray _right, OutputArray disp, Stream& _stream)
{
using namespace cv::gpu::cudev::stereocsbp;
GpuMat u[2], d[2], l[2], r[2], disp_selected_pyr[2], data_cost, data_cost_selected;
CV_Assert( msg_type_ == CV_32F || msg_type_ == CV_16S );
CV_Assert( 0 < ndisp_ && 0 < iters_ && 0 < levels_ && 0 < nr_plane_ && levels_ <= 8 );
GpuMat left = _left.getGpuMat();
GpuMat right = _right.getGpuMat();
//allocate buffers
int buffers_count = 10; // (up + down + left + right + disp_selected_pyr) * 2
buffers_count += 2; // data_cost has twice more rows than other buffers, what's why +2, not +1;
buffers_count += 1; // data_cost_selected
mbuf.create(rows * rthis.nr_plane * buffers_count, cols, DataType<T>::type);
CV_Assert( left.type() == CV_8UC1 || left.type() == CV_8UC3 || left.type() == CV_8UC4 );
CV_Assert( left.size() == right.size() && left.type() == right.type() );
data_cost = mbuf.rowRange(0, rows * rthis.nr_plane * 2);
data_cost_selected = mbuf.rowRange(data_cost.rows, data_cost.rows + rows * rthis.nr_plane);
cudaStream_t stream = StreamAccessor::getStream(_stream);
for(int k = 0; k < 2; ++k) // in/out
{
GpuMat sub1 = mbuf.rowRange(data_cost.rows + data_cost_selected.rows, mbuf.rows);
GpuMat sub2 = sub1.rowRange((k+0)*sub1.rows/2, (k+1)*sub1.rows/2);
////////////////////////////////////////////////////////////////////////////////////////////
// Init
GpuMat *buf_ptrs[] = { &u[k], &d[k], &l[k], &r[k], &disp_selected_pyr[k] };
for(int _r = 0; _r < 5; ++_r)
int rows = left.rows;
int cols = left.cols;
levels_ = std::min(levels_, int(log((double)ndisp_) / log(2.0)));
// compute sizes
AutoBuffer<int> buf(levels_ * 3);
int* cols_pyr = buf;
int* rows_pyr = cols_pyr + levels_;
int* nr_plane_pyr = rows_pyr + levels_;
cols_pyr[0] = cols;
rows_pyr[0] = rows;
nr_plane_pyr[0] = nr_plane_;
for (int i = 1; i < levels_; i++)
{
*buf_ptrs[_r] = sub2.rowRange(_r * sub2.rows/5, (_r+1) * sub2.rows/5);
CV_DbgAssert(buf_ptrs[_r]->cols == cols && buf_ptrs[_r]->rows == rows * rthis.nr_plane);
cols_pyr[i] = cols_pyr[i-1] / 2;
rows_pyr[i] = rows_pyr[i-1] / 2;
nr_plane_pyr[i] = nr_plane_pyr[i-1] * 2;
}
};
size_t elem_step = mbuf.step / sizeof(T);
GpuMat u[2], d[2], l[2], r[2], disp_selected_pyr[2], data_cost, data_cost_selected;
Size temp_size = data_cost.size();
if ((size_t)temp_size.area() < elem_step * rows_pyr[levels - 1] * rthis.ndisp)
temp_size = Size(static_cast<int>(elem_step), rows_pyr[levels - 1] * rthis.ndisp);
//allocate buffers
int buffers_count = 10; // (up + down + left + right + disp_selected_pyr) * 2
buffers_count += 2; // data_cost has twice more rows than other buffers, what's why +2, not +1;
buffers_count += 1; // data_cost_selected
mbuf_.create(rows * nr_plane_ * buffers_count, cols, msg_type_);
temp.create(temp_size, DataType<T>::type);
data_cost = mbuf_.rowRange(0, rows * nr_plane_ * 2);
data_cost_selected = mbuf_.rowRange(data_cost.rows, data_cost.rows + rows * nr_plane_);
////////////////////////////////////////////////////////////////////////////
// Compute
for(int k = 0; k < 2; ++k) // in/out
{
GpuMat sub1 = mbuf_.rowRange(data_cost.rows + data_cost_selected.rows, mbuf_.rows);
GpuMat sub2 = sub1.rowRange((k+0)*sub1.rows/2, (k+1)*sub1.rows/2);
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);
GpuMat *buf_ptrs[] = { &u[k], &d[k], &l[k], &r[k], &disp_selected_pyr[k] };
for(int _r = 0; _r < 5; ++_r)
{
*buf_ptrs[_r] = sub2.rowRange(_r * sub2.rows/5, (_r+1) * sub2.rows/5);
CV_DbgAssert( buf_ptrs[_r]->cols == cols && buf_ptrs[_r]->rows == rows * nr_plane_ );
}
};
l[0].setTo(zero, stream);
d[0].setTo(zero, stream);
r[0].setTo(zero, stream);
u[0].setTo(zero, stream);
size_t elem_step = mbuf_.step / mbuf_.elemSize();
l[1].setTo(zero, stream);
d[1].setTo(zero, stream);
r[1].setTo(zero, stream);
u[1].setTo(zero, stream);
Size temp_size = data_cost.size();
if ((size_t)temp_size.area() < elem_step * rows_pyr[levels_ - 1] * ndisp_)
temp_size = Size(static_cast<int>(elem_step), rows_pyr[levels_ - 1] * ndisp_);
data_cost.setTo(zero, stream);
data_cost_selected.setTo(zero, stream);
temp_.create(temp_size, msg_type_);
int cur_idx = 0;
////////////////////////////////////////////////////////////////////////////
// Compute
for (int i = levels - 1; i >= 0; i--)
{
if (i == levels - 1)
load_constants(ndisp_, max_data_term_, data_weight_, max_disc_term_, disc_single_jump_, min_disp_th_, left, right, temp_);
l[0].setTo(0, _stream);
d[0].setTo(0, _stream);
r[0].setTo(0, _stream);
u[0].setTo(0, _stream);
l[1].setTo(0, _stream);
d[1].setTo(0, _stream);
r[1].setTo(0, _stream);
u[1].setTo(0, _stream);
data_cost.setTo(0, _stream);
data_cost_selected.setTo(0, _stream);
int cur_idx = 0;
if (msg_type_ == CV_32F)
{
init_data_cost(left.rows, left.cols, disp_selected_pyr[cur_idx].ptr<T>(), data_cost_selected.ptr<T>(),
elem_step, rows_pyr[i], cols_pyr[i], i, nr_plane_pyr[i], rthis.ndisp, left.channels(), rthis.use_local_init_data_cost, cudaStream);
for (int i = levels_ - 1; i >= 0; i--)
{
if (i == levels_ - 1)
{
init_data_cost(left.rows, left.cols, disp_selected_pyr[cur_idx].ptr<float>(), data_cost_selected.ptr<float>(),
elem_step, rows_pyr[i], cols_pyr[i], i, nr_plane_pyr[i], ndisp_, left.channels(), use_local_init_data_cost_, stream);
}
else
{
compute_data_cost(disp_selected_pyr[cur_idx].ptr<float>(), data_cost.ptr<float>(), elem_step,
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;
init_message(u[new_idx].ptr<float>(), d[new_idx].ptr<float>(), l[new_idx].ptr<float>(), r[new_idx].ptr<float>(),
u[cur_idx].ptr<float>(), d[cur_idx].ptr<float>(), l[cur_idx].ptr<float>(), r[cur_idx].ptr<float>(),
disp_selected_pyr[new_idx].ptr<float>(), disp_selected_pyr[cur_idx].ptr<float>(),
data_cost_selected.ptr<float>(), data_cost.ptr<float>(), elem_step, 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;
}
calc_all_iterations(u[cur_idx].ptr<float>(), d[cur_idx].ptr<float>(), l[cur_idx].ptr<float>(), r[cur_idx].ptr<float>(),
data_cost_selected.ptr<float>(), disp_selected_pyr[cur_idx].ptr<float>(), elem_step,
rows_pyr[i], cols_pyr[i], nr_plane_pyr[i], iters_, stream);
}
}
else
{
compute_data_cost(disp_selected_pyr[cur_idx].ptr<T>(), data_cost.ptr<T>(), elem_step,
left.rows, left.cols, rows_pyr[i], cols_pyr[i], rows_pyr[i+1], i, nr_plane_pyr[i+1], left.channels(), cudaStream);
for (int i = levels_ - 1; i >= 0; i--)
{
if (i == levels_ - 1)
{
init_data_cost(left.rows, left.cols, disp_selected_pyr[cur_idx].ptr<short>(), data_cost_selected.ptr<short>(),
elem_step, rows_pyr[i], cols_pyr[i], i, nr_plane_pyr[i], ndisp_, left.channels(), use_local_init_data_cost_, stream);
}
else
{
compute_data_cost(disp_selected_pyr[cur_idx].ptr<short>(), data_cost.ptr<short>(), elem_step,
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;
init_message(u[new_idx].ptr<short>(), d[new_idx].ptr<short>(), l[new_idx].ptr<short>(), r[new_idx].ptr<short>(),
u[cur_idx].ptr<short>(), d[cur_idx].ptr<short>(), l[cur_idx].ptr<short>(), r[cur_idx].ptr<short>(),
disp_selected_pyr[new_idx].ptr<short>(), disp_selected_pyr[cur_idx].ptr<short>(),
data_cost_selected.ptr<short>(), data_cost.ptr<short>(), elem_step, 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;
}
calc_all_iterations(u[cur_idx].ptr<short>(), d[cur_idx].ptr<short>(), l[cur_idx].ptr<short>(), r[cur_idx].ptr<short>(),
data_cost_selected.ptr<short>(), disp_selected_pyr[cur_idx].ptr<short>(), elem_step,
rows_pyr[i], cols_pyr[i], nr_plane_pyr[i], iters_, stream);
}
}
int new_idx = (cur_idx + 1) & 1;
const int dtype = disp.fixedType() ? disp.type() : CV_16SC1;
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>(), elem_step, rows_pyr[i],
cols_pyr[i], nr_plane_pyr[i], rows_pyr[i+1], cols_pyr[i+1], nr_plane_pyr[i+1], cudaStream);
disp.create(rows, cols, dtype);
GpuMat out = disp.getGpuMat();
cur_idx = new_idx;
if (dtype != CV_16SC1)
{
outBuf_.create(rows, cols, CV_16SC1);
out = outBuf_;
}
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>(), elem_step,
rows_pyr[i], cols_pyr[i], nr_plane_pyr[i], rthis.iters, cudaStream);
}
out.setTo(0, _stream);
if (disp.empty())
disp.create(rows, cols, CV_16S);
out = ((disp.type() == CV_16S) ? disp : (out.create(rows, cols, CV_16S), out));
out.setTo(zero, stream);
if (msg_type_ == CV_32F)
{
compute_disp(u[cur_idx].ptr<float>(), d[cur_idx].ptr<float>(), l[cur_idx].ptr<float>(), r[cur_idx].ptr<float>(),
data_cost_selected.ptr<float>(), disp_selected_pyr[cur_idx].ptr<float>(), elem_step, out, nr_plane_pyr[0], stream);
}
else
{
compute_disp(u[cur_idx].ptr<short>(), d[cur_idx].ptr<short>(), l[cur_idx].ptr<short>(), r[cur_idx].ptr<short>(),
data_cost_selected.ptr<short>(), disp_selected_pyr[cur_idx].ptr<short>(), elem_step, out, nr_plane_pyr[0], stream);
}
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>(), elem_step, out, nr_plane_pyr[0], cudaStream);
if (dtype != CV_16SC1)
out.convertTo(disp, dtype, _stream);
}
if (disp.type() != CV_16S)
void StereoCSBPImpl::compute(InputArray /*data*/, OutputArray /*disparity*/, Stream& /*stream*/)
{
out.convertTo(disp, disp.type(), stream);
CV_Error(Error::StsNotImplemented, "Not implemented");
}
}
Ptr<gpu::StereoConstantSpaceBP> cv::gpu::createStereoConstantSpaceBP(int ndisp, int iters, int levels, int nr_plane, int msg_type)
{
return new StereoCSBPImpl(ndisp, iters, levels, nr_plane, msg_type);
}
void cv::gpu::StereoConstantSpaceBP::estimateRecommendedParams(int width, int height, int& ndisp, int& iters, int& levels, int& nr_plane)
{
ndisp = (int) ((float) width / 3.14f);
if ((ndisp & 1) != 0)
ndisp++;
typedef void (*csbp_operator_t)(StereoConstantSpaceBP& rthis, GpuMat& mbuf,
GpuMat& temp, GpuMat& out, const GpuMat& left, const GpuMat& right, GpuMat& disp, Stream& stream);
int mm = std::max(width, height);
iters = mm / 100 + ((mm > 1200)? - 4 : 4);
const static csbp_operator_t operators[] = {0, 0, 0, csbp_operator<short>, 0, csbp_operator<float>, 0, 0};
levels = (int)::log(static_cast<double>(mm)) * 2 / 3;
if (levels == 0) levels++;
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, messages_buffers, temp, out, left, right, disp, stream);
nr_plane = (int) ((float) ndisp / std::pow(2.0, levels + 1));
}
#endif /* !defined (HAVE_CUDA) */

4
modules/gpustereo/test/test_stereo.cpp
Unescape View File

@ -155,10 +155,10 @@ GPU_TEST_P(StereoConstantSpaceBP, Regression)
ASSERT_FALSE(right_image.empty());
ASSERT_FALSE(disp_gold.empty());
cv::gpu::StereoConstantSpaceBP csbp(128, 16, 4, 4);
cv::Ptr<cv::gpu::StereoConstantSpaceBP> csbp = cv::gpu::createStereoConstantSpaceBP(128, 16, 4, 4);
cv::gpu::GpuMat disp;
csbp(loadMat(left_image), loadMat(right_image), disp);
csbp->compute(loadMat(left_image), loadMat(right_image), disp);
cv::Mat h_disp(disp);
h_disp.convertTo(h_disp, disp_gold.depth());

30
samples/gpu/stereo_match.cpp
Unescape View File

@ -67,7 +67,7 @@ private:
Ptr<gpu::StereoBM> bm;
Ptr<gpu::StereoBeliefPropagation> bp;
gpu::StereoConstantSpaceBP csbp;
Ptr<gpu::StereoConstantSpaceBP> csbp;
int64 work_begin;
double work_fps;
@ -174,7 +174,7 @@ void App::run()
// Set common parameters
bm = gpu::createStereoBM(p.ndisp);
bp = gpu::createStereoBeliefPropagation(p.ndisp);
csbp.ndisp = p.ndisp;
csbp = cv::gpu::createStereoConstantSpaceBP(p.ndisp);
// Prepare disparity map of specified type
Mat disp(left.size(), CV_8U);
@ -204,7 +204,7 @@ void App::run()
bm->compute(d_left, d_right, d_disp);
break;
case Params::BP: bp->compute(d_left, d_right, d_disp); break;
case Params::CSBP: csbp(d_left, d_right, d_disp); break;
case Params::CSBP: csbp->compute(d_left, d_right, d_disp); break;
}
workEnd();
@ -236,8 +236,8 @@ void App::printParams() const
cout << "level_count: " << bp->getNumLevels() << endl;
break;
case Params::CSBP:
cout << "iter_count: " << csbp.iters << endl;
cout << "level_count: " << csbp.levels << endl;
cout << "iter_count: " << csbp->getNumIters() << endl;
cout << "level_count: " << csbp->getNumLevels() << endl;
break;
}
cout << endl;
@ -306,14 +306,14 @@ void App::handleKey(char key)
cout << "ndisp: " << p.ndisp << endl;
bm->setNumDisparities(p.ndisp);
bp->setNumDisparities(p.ndisp);
csbp.ndisp = p.ndisp;
csbp->setNumDisparities(p.ndisp);
break;
case 'q': case 'Q':
p.ndisp = max(p.ndisp - 8, 1);
cout << "ndisp: " << p.ndisp << endl;
bm->setNumDisparities(p.ndisp);
bp->setNumDisparities(p.ndisp);
csbp.ndisp = p.ndisp;
csbp->setNumDisparities(p.ndisp);
break;
case '2':
if (p.method == Params::BM)
@ -337,8 +337,8 @@ void App::handleKey(char key)
}
else if (p.method == Params::CSBP)
{
csbp.iters += 1;
cout << "iter_count: " << csbp.iters << endl;
csbp->setNumIters(csbp->getNumIters() + 1);
cout << "iter_count: " << csbp->getNumIters() << endl;
}
break;
case 'e': case 'E':
@ -349,8 +349,8 @@ void App::handleKey(char key)
}
else if (p.method == Params::CSBP)
{
csbp.iters = max(csbp.iters - 1, 1);
cout << "iter_count: " << csbp.iters << endl;
csbp->setNumIters(max(csbp->getNumIters() - 1, 1));
cout << "iter_count: " << csbp->getNumIters() << endl;
}
break;
case '4':
@ -361,8 +361,8 @@ void App::handleKey(char key)
}
else if (p.method == Params::CSBP)
{
csbp.levels += 1;
cout << "level_count: " << csbp.levels << endl;
csbp->setNumLevels(csbp->getNumLevels() + 1);
cout << "level_count: " << csbp->getNumLevels() << endl;
}
break;
case 'r': case 'R':
@ -373,8 +373,8 @@ void App::handleKey(char key)
}
else if (p.method == Params::CSBP)
{
csbp.levels = max(csbp.levels - 1, 1);
cout << "level_count: " << csbp.levels << endl;
csbp->setNumLevels(max(csbp->getNumLevels() - 1, 1));
cout << "level_count: " << csbp->getNumLevels() << endl;
}
break;
}

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