提交 c18aa438 编写于 作者: V Vladislav Vinogradov

added support of 4 channels images to StereoBeliefPropagation, minor code refactoring.

上级 5e401f29
......@@ -64,11 +64,18 @@ void cv::gpu::StereoBeliefPropagation::operator()(const GpuMat&, GpuMat&, Stream
namespace cv { namespace gpu { namespace bp
{
void load_constants(int ndisp, float max_data_term, float data_weight, float max_disc_term, float disc_single_jump);
void comp_data(int msg_type, const DevMem2D& l, const DevMem2D& r, int channels, DevMem2D mdata, const cudaStream_t& stream);
void data_step_down(int dst_cols, int dst_rows, int src_rows, int msg_type, const DevMem2D& src, DevMem2D dst, const cudaStream_t& stream);
void level_up_messages(int dst_idx, int dst_cols, int dst_rows, int src_rows, int msg_type, DevMem2D* mus, DevMem2D* mds, DevMem2D* mls, DevMem2D* mrs, const cudaStream_t& stream);
void calc_all_iterations(int cols, int rows, int iters, int msg_type, DevMem2D& u, DevMem2D& d, DevMem2D& l, DevMem2D& r, const DevMem2D& data, const cudaStream_t& stream);
void output(int msg_type, const DevMem2D& u, const DevMem2D& d, const DevMem2D& l, const DevMem2D& r, const DevMem2D& data, DevMem2D disp, const cudaStream_t& stream);
template<typename T, typename D>
void comp_data_gpu(const DevMem2D& left, const DevMem2D& right, const DevMem2D& data, cudaStream_t stream);
template<typename T>
void data_step_down_gpu(int dst_cols, int dst_rows, int src_rows, const DevMem2D& src, const DevMem2D& dst, cudaStream_t stream);
template <typename T>
void level_up_messages_gpu(int dst_idx, int dst_cols, int dst_rows, int src_rows, DevMem2D* mus, DevMem2D* mds, DevMem2D* mls, DevMem2D* mrs, cudaStream_t stream);
template <typename T>
void calc_all_iterations_gpu(int cols, int rows, int iters, const DevMem2D& u, const DevMem2D& d,
const DevMem2D& l, const DevMem2D& r, const DevMem2D& data, cudaStream_t stream);
template <typename T>
void output_gpu(const DevMem2D& u, const DevMem2D& d, const DevMem2D& l, const DevMem2D& r, const DevMem2D& data,
const DevMem2D_<short>& disp, cudaStream_t stream);
}}}
namespace
......@@ -121,17 +128,24 @@ namespace
: rthis(rthis_), u(u_), d(d_), l(l_), r(r_), u2(u2_), d2(d2_), l2(l2_), r2(r2_), datas(datas_), out(out_),
zero(Scalar::all(0)), scale(rthis_.msg_type == CV_32F ? 1.0f : 10.0f)
{
CV_DbgAssert(0 < rthis.ndisp && 0 < rthis.iters && 0 < rthis.levels);
CV_Assert(0 < rthis.ndisp && 0 < rthis.iters && 0 < rthis.levels);
CV_Assert(rthis.msg_type == CV_32F || rthis.msg_type == CV_16S);
if (rthis.msg_type == CV_16S)
CV_Assert((1 << (rthis.levels - 1)) * scale * rthis.max_data_term < numeric_limits<short>::max());
}
void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disp, const cudaStream_t& stream)
void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disp, cudaStream_t stream)
{
CV_DbgAssert(left.rows == right.rows && left.cols == right.cols && left.type() == right.type());
CV_Assert(left.type() == CV_8UC1 || left.type() == CV_8UC3);
typedef void (*comp_data_t)(const DevMem2D& left, const DevMem2D& right, const DevMem2D& data, cudaStream_t stream);
static const comp_data_t comp_data_callers[2][5] =
{
{0, bp::comp_data_gpu<unsigned char, short>, 0, bp::comp_data_gpu<uchar3, short>, bp::comp_data_gpu<uchar4, short>},
{0, bp::comp_data_gpu<unsigned char, float>, 0, bp::comp_data_gpu<uchar3, float>, bp::comp_data_gpu<uchar4, float>}
};
CV_Assert(left.size() == right.size() && left.type() == right.type());
CV_Assert(left.type() == CV_8UC1 || left.type() == CV_8UC3 || left.type() == CV_8UC4);
rows = left.rows;
cols = left.cols;
......@@ -146,12 +160,12 @@ namespace
datas[0].create(rows * rthis.ndisp, cols, rthis.msg_type);
bp::comp_data(rthis.msg_type, left, right, left.channels(), datas[0], stream);
comp_data_callers[rthis.msg_type == CV_32F][left.channels()](left, right, datas[0], stream);
calcBP(disp, stream);
}
void operator()(const GpuMat& data, GpuMat& disp, const cudaStream_t& stream)
void operator()(const GpuMat& data, GpuMat& disp, cudaStream_t stream)
{
CV_Assert((data.type() == rthis.msg_type) && (data.rows % rthis.ndisp == 0));
......@@ -217,8 +231,36 @@ namespace
rows_all[0] = rows;
}
void calcBP(GpuMat& disp, const cudaStream_t& stream)
void calcBP(GpuMat& disp, cudaStream_t stream)
{
using namespace cv::gpu::bp;
typedef void (*data_step_down_t)(int dst_cols, int dst_rows, int src_rows, const DevMem2D& src, const DevMem2D& dst, cudaStream_t stream);
static const data_step_down_t data_step_down_callers[2] =
{
data_step_down_gpu<short>, data_step_down_gpu<float>
};
typedef void (*level_up_messages_t)(int dst_idx, int dst_cols, int dst_rows, int src_rows, DevMem2D* mus, DevMem2D* mds, DevMem2D* mls, DevMem2D* mrs, cudaStream_t stream);
static const level_up_messages_t level_up_messages_callers[2] =
{
level_up_messages_gpu<short>, level_up_messages_gpu<float>
};
typedef void (*calc_all_iterations_t)(int cols, int rows, int iters, const DevMem2D& u, const DevMem2D& d, const DevMem2D& l, const DevMem2D& r, const DevMem2D& data, cudaStream_t stream);
static const calc_all_iterations_t calc_all_iterations_callers[2] =
{
calc_all_iterations_gpu<short>, calc_all_iterations_gpu<float>
};
typedef void (*output_t)(const DevMem2D& u, const DevMem2D& d, const DevMem2D& l, const DevMem2D& r, const DevMem2D& data, const DevMem2D_<short>& disp, cudaStream_t stream);
static const output_t output_callers[2] =
{
output_gpu<short>, output_gpu<float>
};
const int funcIdx = rthis.msg_type == CV_32F;
for (int i = 1; i < rthis.levels; ++i)
{
cols_all[i] = (cols_all[i-1] + 1) / 2;
......@@ -226,7 +268,7 @@ namespace
datas[i].create(rows_all[i] * rthis.ndisp, cols_all[i], rthis.msg_type);
bp::data_step_down(cols_all[i], rows_all[i], rows_all[i-1], rthis.msg_type, datas[i-1], datas[i], stream);
data_step_down_callers[funcIdx](cols_all[i], rows_all[i], rows_all[i-1], datas[i-1], datas[i], stream);
}
DevMem2D mus[] = {u, u2};
......@@ -240,9 +282,9 @@ namespace
{
// for lower level we have already computed messages by setting to zero
if (i != rthis.levels - 1)
bp::level_up_messages(mem_idx, cols_all[i], rows_all[i], rows_all[i+1], rthis.msg_type, mus, mds, mls, mrs, stream);
level_up_messages_callers[funcIdx](mem_idx, cols_all[i], rows_all[i], rows_all[i+1], mus, mds, mls, mrs, stream);
bp::calc_all_iterations(cols_all[i], rows_all[i], rthis.iters, rthis.msg_type, mus[mem_idx], mds[mem_idx], mls[mem_idx], mrs[mem_idx], datas[i], stream);
calc_all_iterations_callers[funcIdx](cols_all[i], rows_all[i], rthis.iters, mus[mem_idx], mds[mem_idx], mls[mem_idx], mrs[mem_idx], datas[i], stream);
mem_idx = (mem_idx + 1) & 1;
}
......@@ -253,7 +295,7 @@ namespace
out = ((disp.type() == CV_16S) ? disp : (out.create(rows, cols, CV_16S), out));
out = zero;
bp::output(rthis.msg_type, u, d, l, r, datas.front(), out, stream);
output_callers[funcIdx](u, d, l, r, datas.front(), out, stream);
if (disp.type() != CV_16S)
out.convertTo(disp, disp.type());
......
......@@ -106,6 +106,7 @@ protected:
if (!compareMatches(matchesCPU, matchesGPU))
{
ts->printf(CvTS::LOG, "Match FAIL");
ts->set_failed_test_info(CvTS::FAIL_MISMATCH);
return;
}
......@@ -117,6 +118,7 @@ protected:
if (!compareMatches(knnMatchesCPU, knnMatchesGPU))
{
ts->printf(CvTS::LOG, "KNN Match FAIL");
ts->set_failed_test_info(CvTS::FAIL_MISMATCH);
return;
}
......@@ -128,6 +130,7 @@ protected:
if (!compareMatches(radiusMatchesCPU, radiusMatchesGPU))
{
ts->printf(CvTS::LOG, "Radius Match FAIL");
ts->set_failed_test_info(CvTS::FAIL_MISMATCH);
return;
}
......
......@@ -62,6 +62,9 @@ struct CV_GpuStereoBPTest : public CvTest
try
{
{cv::Mat temp; cv::cvtColor(img_l, temp, CV_BGR2BGRA); cv::swap(temp, img_l);}
{cv::Mat temp; cv::cvtColor(img_r, temp, CV_BGR2BGRA); cv::swap(temp, img_r);}
cv::gpu::GpuMat disp;
cv::gpu::StereoBeliefPropagation bpm(64, 8, 2, 25, 0.1f, 15, 1, CV_16S);
......
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