added version of StereoBeliefPropagation::operator() for user specified data term
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@ -415,6 +415,11 @@ namespace cv
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//! Acync version
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//! Acync version
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void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream);
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void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream);
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//! version for user specified data term
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void operator()(const GpuMat& data, GpuMat& disparity);
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void operator()(const GpuMat& data, GpuMat& disparity, Stream& stream);
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int ndisp;
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int ndisp;
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int iters;
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int iters;
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@ -54,6 +54,9 @@ cv::gpu::StereoBeliefPropagation::StereoBeliefPropagation(int, int, int, float,
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void cv::gpu::StereoBeliefPropagation::operator()(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::StereoBeliefPropagation::operator()(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::StereoBeliefPropagation::operator()(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
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void cv::gpu::StereoBeliefPropagation::operator()(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
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void cv::gpu::StereoBeliefPropagation::operator()(const GpuMat&, GpuMat&) { throw_nogpu(); }
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void cv::gpu::StereoBeliefPropagation::operator()(const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
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#else /* !defined (HAVE_CUDA) */
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#else /* !defined (HAVE_CUDA) */
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namespace cv { namespace gpu { namespace bp
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namespace cv { namespace gpu { namespace bp
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@ -90,40 +93,76 @@ cv::gpu::StereoBeliefPropagation::StereoBeliefPropagation(int ndisp_, int iters_
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{
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{
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}
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}
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static void stereo_bp_gpu_operator(int& ndisp, int& iters, int& levels,
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namespace
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float& max_data_term, float& data_weight, float& max_disc_term, float& disc_single_jump,
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int& msg_type,
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GpuMat& u, GpuMat& d, GpuMat& l, GpuMat& r,
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GpuMat& u2, GpuMat& d2, GpuMat& l2, GpuMat& r2,
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vector<GpuMat>& datas, GpuMat& out,
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const GpuMat& left, const GpuMat& right, GpuMat& disp,
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const cudaStream_t& stream)
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{
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{
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CV_DbgAssert(0 < ndisp && 0 < iters && 0 < levels
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class StereoBeliefPropagationImpl
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&& (msg_type == CV_32F || msg_type == CV_16S)
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{
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&& left.rows == right.rows && left.cols == right.cols && left.type() == right.type());
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public:
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StereoBeliefPropagationImpl(StereoBeliefPropagation& rthis_,
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GpuMat& u_, GpuMat& d_, GpuMat& l_, GpuMat& r_,
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GpuMat& u2_, GpuMat& d2_, GpuMat& l2_, GpuMat& r2_,
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vector<GpuMat>& datas_, GpuMat& out_)
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: rthis(rthis_), u(u_), d(d_), l(l_), r(r_), u2(u2_), d2(d2_), l2(l2_), r2(r2_), datas(datas_), out(out_),
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zero(Scalar::all(0)), scale(rthis_.msg_type == CV_32F ? 1.0f : 10.0f)
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{
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CV_DbgAssert(0 < rthis.ndisp && 0 < rthis.iters && 0 < rthis.levels);
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CV_Assert(rthis.msg_type == CV_32F || rthis.msg_type == CV_16S);
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CV_Assert((left.type() == CV_8UC1 || left.type() == CV_8UC3));
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if (rthis.msg_type == CV_16S)
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CV_Assert((1 << (rthis.levels - 1)) * scale * rthis.max_data_term < numeric_limits<short>::max());
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}
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const Scalar zero = Scalar::all(0);
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void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disp, const cudaStream_t& stream)
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{
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CV_DbgAssert(left.rows == right.rows && left.cols == right.cols && left.type() == right.type());
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CV_Assert(left.type() == CV_8UC1 || left.type() == CV_8UC3);
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const float scale = ((msg_type == CV_32F) ? 1.0f : 10.0f);
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rows = left.rows;
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cols = left.cols;
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int rows = left.rows;
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int divisor = (int)pow(2.f, rthis.levels - 1.0f);
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int cols = left.cols;
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int divisor = (int)pow(2.f, levels - 1.0f);
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int lowest_cols = cols / divisor;
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int lowest_cols = cols / divisor;
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int lowest_rows = rows / divisor;
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int lowest_rows = rows / divisor;
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const int min_image_dim_size = 2;
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const int min_image_dim_size = 2;
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CV_Assert(min(lowest_cols, lowest_rows) > min_image_dim_size);
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CV_Assert(min(lowest_cols, lowest_rows) > min_image_dim_size);
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u.create(rows * ndisp, cols, msg_type);
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init();
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d.create(rows * ndisp, cols, msg_type);
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l.create(rows * ndisp, cols, msg_type);
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r.create(rows * ndisp, cols, msg_type);
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if (levels & 1)
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datas[0].create(rows * rthis.ndisp, cols, rthis.msg_type);
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bp::comp_data(rthis.msg_type, left, right, left.channels(), datas[0], stream);
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calcBP(disp, stream);
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}
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void operator()(const GpuMat& data, GpuMat& disp, const cudaStream_t& stream)
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{
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CV_Assert((data.type() == rthis.msg_type) && (data.rows % rthis.ndisp == 0));
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rows = data.rows / rthis.ndisp;
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cols = data.cols;
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int divisor = (int)pow(2.f, rthis.levels - 1.0f);
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int lowest_cols = cols / divisor;
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int lowest_rows = rows / divisor;
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const int min_image_dim_size = 2;
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CV_Assert(min(lowest_cols, lowest_rows) > min_image_dim_size);
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init();
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datas[0] = data;
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calcBP(disp, stream);
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}
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private:
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void init()
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{
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u.create(rows * rthis.ndisp, cols, rthis.msg_type);
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d.create(rows * rthis.ndisp, cols, rthis.msg_type);
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l.create(rows * rthis.ndisp, cols, rthis.msg_type);
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r.create(rows * rthis.ndisp, cols, rthis.msg_type);
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if (rthis.levels & 1)
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{
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{
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//can clear less area
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//can clear less area
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u = zero;
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u = zero;
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@ -132,17 +171,17 @@ static void stereo_bp_gpu_operator(int& ndisp, int& iters, int& levels,
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r = zero;
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r = zero;
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}
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}
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if (levels > 1)
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if (rthis.levels > 1)
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{
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{
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int less_rows = (rows + 1) / 2;
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int less_rows = (rows + 1) / 2;
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int less_cols = (cols + 1) / 2;
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int less_cols = (cols + 1) / 2;
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u2.create(less_rows * ndisp, less_cols, msg_type);
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u2.create(less_rows * rthis.ndisp, less_cols, rthis.msg_type);
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d2.create(less_rows * ndisp, less_cols, msg_type);
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d2.create(less_rows * rthis.ndisp, less_cols, rthis.msg_type);
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l2.create(less_rows * ndisp, less_cols, msg_type);
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l2.create(less_rows * rthis.ndisp, less_cols, rthis.msg_type);
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r2.create(less_rows * ndisp, less_cols, msg_type);
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r2.create(less_rows * rthis.ndisp, less_cols, rthis.msg_type);
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if ((levels & 1) == 0)
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if ((rthis.levels & 1) == 0)
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{
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{
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u2 = zero;
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u2 = zero;
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d2 = zero;
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d2 = zero;
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@ -151,30 +190,27 @@ static void stereo_bp_gpu_operator(int& ndisp, int& iters, int& levels,
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}
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}
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}
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}
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bp::load_constants(ndisp, max_data_term, scale * data_weight, scale * max_disc_term, scale * disc_single_jump);
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bp::load_constants(rthis.ndisp, rthis.max_data_term, scale * rthis.data_weight, scale * rthis.max_disc_term, scale * rthis.disc_single_jump);
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datas.resize(levels);
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datas.resize(rthis.levels);
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AutoBuffer<int> buf(levels << 1);
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cols_all.resize(rthis.levels);
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rows_all.resize(rthis.levels);
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int* cols_all = buf;
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int* rows_all = cols_all + levels;
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cols_all[0] = cols;
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cols_all[0] = cols;
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rows_all[0] = rows;
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rows_all[0] = rows;
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}
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datas[0].create(rows * ndisp, cols, msg_type);
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void calcBP(GpuMat& disp, const cudaStream_t& stream)
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{
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bp::comp_data(msg_type, left, right, left.channels(), datas.front(), stream);
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for (int i = 1; i < rthis.levels; ++i)
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for (int i = 1; i < levels; i++)
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{
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{
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cols_all[i] = (cols_all[i-1] + 1) / 2;
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cols_all[i] = (cols_all[i-1] + 1) / 2;
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rows_all[i] = (rows_all[i-1] + 1) / 2;
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rows_all[i] = (rows_all[i-1] + 1) / 2;
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datas[i].create(rows_all[i] * ndisp, cols_all[i], msg_type);
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datas[i].create(rows_all[i] * rthis.ndisp, cols_all[i], rthis.msg_type);
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bp::data_step_down(cols_all[i], rows_all[i], rows_all[i-1], msg_type, datas[i-1], datas[i], stream);
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bp::data_step_down(cols_all[i], rows_all[i], rows_all[i-1], rthis.msg_type, datas[i-1], datas[i], stream);
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}
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}
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DevMem2D mus[] = {u, u2};
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DevMem2D mus[] = {u, u2};
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@ -182,15 +218,15 @@ static void stereo_bp_gpu_operator(int& ndisp, int& iters, int& levels,
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DevMem2D mrs[] = {r, r2};
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DevMem2D mrs[] = {r, r2};
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DevMem2D mls[] = {l, l2};
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DevMem2D mls[] = {l, l2};
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int mem_idx = (levels & 1) ? 0 : 1;
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int mem_idx = (rthis.levels & 1) ? 0 : 1;
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for (int i = levels - 1; i >= 0; i--)
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for (int i = rthis.levels - 1; i >= 0; --i)
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{
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{
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// for lower level we have already computed messages by setting to zero
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// for lower level we have already computed messages by setting to zero
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if (i != levels - 1)
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if (i != rthis.levels - 1)
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bp::level_up_messages(mem_idx, cols_all[i], rows_all[i], rows_all[i+1], msg_type, mus, mds, mls, mrs, stream);
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bp::level_up_messages(mem_idx, cols_all[i], rows_all[i], rows_all[i+1], rthis.msg_type, mus, mds, mls, mrs, stream);
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bp::calc_all_iterations(cols_all[i], rows_all[i], iters, msg_type, mus[mem_idx], mds[mem_idx], mls[mem_idx], mrs[mem_idx], datas[i], stream);
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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);
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mem_idx = (mem_idx + 1) & 1;
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mem_idx = (mem_idx + 1) & 1;
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}
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}
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@ -201,20 +237,58 @@ static void stereo_bp_gpu_operator(int& ndisp, int& iters, int& levels,
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out = ((disp.type() == CV_16S) ? disp : GpuMat(rows, cols, CV_16S));
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out = ((disp.type() == CV_16S) ? disp : GpuMat(rows, cols, CV_16S));
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out = zero;
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out = zero;
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bp::output(msg_type, u, d, l, r, datas.front(), disp, stream);
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bp::output(rthis.msg_type, u, d, l, r, datas.front(), disp, stream);
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if (disp.type() != CV_16S)
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if (disp.type() != CV_16S)
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out.convertTo(disp, disp.type());
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out.convertTo(disp, disp.type());
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}
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}
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StereoBeliefPropagation& rthis;
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GpuMat& u;
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GpuMat& d;
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GpuMat& l;
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GpuMat& r;
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GpuMat& u2;
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GpuMat& d2;
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GpuMat& l2;
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GpuMat& r2;
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vector<GpuMat>& datas;
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GpuMat& out;
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const Scalar zero;
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const float scale;
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int rows, cols;
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vector<int> cols_all, rows_all;
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};
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}
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void cv::gpu::StereoBeliefPropagation::operator()(const GpuMat& left, const GpuMat& right, GpuMat& disp)
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void cv::gpu::StereoBeliefPropagation::operator()(const GpuMat& left, const GpuMat& right, GpuMat& disp)
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{
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{
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::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);
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::StereoBeliefPropagationImpl impl(*this, u, d, l, r, u2, d2, l2, r2, datas, out);
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impl(left, right, disp, 0);
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}
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}
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void cv::gpu::StereoBeliefPropagation::operator()(const GpuMat& left, const GpuMat& right, GpuMat& disp, Stream& stream)
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void cv::gpu::StereoBeliefPropagation::operator()(const GpuMat& left, const GpuMat& right, GpuMat& disp, Stream& stream)
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{
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{
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::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));
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::StereoBeliefPropagationImpl impl(*this, u, d, l, r, u2, d2, l2, r2, datas, out);
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impl(left, right, disp, StreamAccessor::getStream(stream));
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}
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void cv::gpu::StereoBeliefPropagation::operator()(const GpuMat& data, GpuMat& disp)
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{
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::StereoBeliefPropagationImpl impl(*this, u, d, l, r, u2, d2, l2, r2, datas, out);
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impl(data, disp, 0);
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}
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void cv::gpu::StereoBeliefPropagation::operator()(const GpuMat& data, GpuMat& disp, Stream& stream)
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{
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::StereoBeliefPropagationImpl impl(*this, u, d, l, r, u2, d2, l2, r2, datas, out);
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impl(data, disp, StreamAccessor::getStream(stream));
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}
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}
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#endif /* !defined (HAVE_CUDA) */
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#endif /* !defined (HAVE_CUDA) */
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@ -52,6 +52,7 @@
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#include <iostream>
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#include <iostream>
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#include <limits>
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#include <limits>
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#include <vector>
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#include "opencv2/gpu/gpu.hpp"
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#include "opencv2/gpu/gpu.hpp"
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