opencv/modules/gpu/src/beliefpropagation_gpu.cpp

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
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//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
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// * Redistribution's of source code must retain the above copyright notice,
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#include "precomp.hpp"
using namespace cv;
using namespace cv::gpu;
using namespace std;
#if !defined (HAVE_CUDA)
cv::gpu::StereoBeliefPropagation_GPU::StereoBeliefPropagation_GPU(int, int, int, int, float) { throw_nogpu(); }
cv::gpu::StereoBeliefPropagation_GPU::StereoBeliefPropagation_GPU(int, int, int, float, float, float, float, int, float) { throw_nogpu(); }
void cv::gpu::StereoBeliefPropagation_GPU::operator()(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); }
void cv::gpu::StereoBeliefPropagation_GPU::operator()(const GpuMat&, const GpuMat&, GpuMat&, const CudaStream&) { throw_nogpu(); }
bool cv::gpu::StereoBeliefPropagation_GPU::checkIfGpuCallReasonable() { throw_nogpu(); return false; }
#else /* !defined (HAVE_CUDA) */
const float DEFAULT_MAX_DATA_TERM = 10.0f;
const float DEFAULT_DATA_WEIGHT = 0.07f;
const float DEFAULT_MAX_DISC_TERM = 1.7f;
const float DEFAULT_DISC_SINGLE_JUMP = 1.0f;
namespace cv { namespace gpu { namespace impl {
void load_constants(int ndisp, float max_data_term, float data_weight, float max_disc_term, float disc_single_jump);
void comp_data(int msgType, const DevMem2D& l, const DevMem2D& r, DevMem2D mdata, const cudaStream_t& stream);
void data_step_down(int dst_cols, int dst_rows, int src_rows, int msgType, 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 msgType, DevMem2D* mus, DevMem2D* mds, DevMem2D* mls, DevMem2D* mrs, const cudaStream_t& stream);
void calc_all_iterations(int cols, int rows, int iters, int msgType, DevMem2D& u, DevMem2D& d, DevMem2D& l, DevMem2D& r, const DevMem2D& data, const cudaStream_t& stream);
void output(int msgType, const DevMem2D& u, const DevMem2D& d, const DevMem2D& l, const DevMem2D& r, const DevMem2D& data, DevMem2D disp, const cudaStream_t& stream);
}}}
cv::gpu::StereoBeliefPropagation_GPU::StereoBeliefPropagation_GPU(int ndisp_, int iters_, int levels_, int msg_type_, float msg_scale_)
: 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_), msg_scale(msg_scale_), datas(levels_)
{
CV_Assert(0 < ndisp && 0 < iters && 0 < levels);
}
cv::gpu::StereoBeliefPropagation_GPU::StereoBeliefPropagation_GPU(int ndisp_, int iters_, int levels_, float max_data_term_, float data_weight_, float max_disc_term_, float disc_single_jump_, int msg_type_, float msg_scale_)
: ndisp(ndisp_), iters(iters_), levels(levels_),
max_data_term(max_data_term_), data_weight(data_weight_),
max_disc_term(max_disc_term_), disc_single_jump(disc_single_jump_),
msg_type(msg_type_), msg_scale(msg_scale_), datas(levels_)
{
CV_Assert(0 < ndisp && 0 < iters && 0 < levels);
}
static bool checkMsgOverflow(int levels, float max_data_term, float data_weight, float max_disc_term, float msg_scale)
{
float maxV = ceil(max_disc_term * msg_scale);
float maxD = ceil(max_data_term * data_weight * msg_scale);
float maxMsg = maxV + (maxD * pow(4.0f, (float)levels));
maxMsg = maxV + (maxD * pow(4.0f, (float)levels)) + 3 * maxMsg;
return (maxMsg > numeric_limits<short>::max());
}
static void stereo_bp_gpu_operator(int ndisp, int iters, int levels,
float max_data_term, float data_weight, float max_disc_term, float disc_single_jump,
int msg_type, float& msg_scale,
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GpuMat& u, GpuMat& d, GpuMat& l, GpuMat& r,
GpuMat& u2, GpuMat& d2, GpuMat& l2, GpuMat& r2,
vector<GpuMat>& datas, GpuMat& out,
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const GpuMat& left, const GpuMat& right, GpuMat& disp,
const cudaStream_t& stream)
{
CV_DbgAssert(left.cols == right.cols && left.rows == right.rows && left.type() == right.type() && left.type() == CV_8U);
const Scalar zero = Scalar::all(0);
int rows = left.rows;
int cols = left.cols;
int divisor = (int)pow(2.f, levels - 1.0f);
int lowest_cols = cols / divisor;
int lowest_rows = rows / divisor;
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const int min_image_dim_size = 2;
CV_Assert(min(lowest_cols, lowest_rows) > min_image_dim_size);
switch (msg_type)
{
case StereoBeliefPropagation_GPU::MSG_TYPE_AUTO:
if (!checkMsgOverflow(levels, max_data_term, data_weight, max_disc_term, 100.0f))
{
msg_type = CV_16S;
msg_scale = 100.0f;
}
else if (!checkMsgOverflow(levels, max_data_term, data_weight, max_disc_term, 64.0f))
{
msg_type = CV_16S;
msg_scale = 64.0f;
}
else if (!checkMsgOverflow(levels, max_data_term, data_weight, max_disc_term, 32.0f))
{
msg_type = CV_16S;
msg_scale = 32.0f;
}
else if (!checkMsgOverflow(levels, max_data_term, data_weight, max_disc_term, 16.0f))
{
msg_type = CV_16S;
msg_scale = 16.0f;
}
else if (!checkMsgOverflow(levels, max_data_term, data_weight, max_disc_term, 10.0f))
{
msg_type = CV_16S;
msg_scale = 10.0f;
}
else
{
msg_type = CV_32F;
msg_scale = 1.0f;
}
break;
case StereoBeliefPropagation_GPU::MSG_TYPE_FLOAT:
msg_type = CV_32F;
msg_scale = 1.0f;
break;
case StereoBeliefPropagation_GPU::MSG_TYPE_SHORT_SCALE_AUTO:
msg_type = CV_16S;
if (!checkMsgOverflow(levels, max_data_term, data_weight, max_disc_term, 100.0f))
msg_scale = 100.0f;
else if (!checkMsgOverflow(levels, max_data_term, data_weight, max_disc_term, 64.0f))
msg_scale = 64.0f;
else if (!checkMsgOverflow(levels, max_data_term, data_weight, max_disc_term, 32.0f))
msg_scale = 32.0f;
else if (!checkMsgOverflow(levels, max_data_term, data_weight, max_disc_term, 16.0f))
msg_scale = 16.0f;
else
msg_scale = 10.0f;
break;
case StereoBeliefPropagation_GPU::MSG_TYPE_SHORT_SCALE_MANUAL:
msg_type = CV_16S;
break;
default:
cv::gpu::error("Unsupported message type", __FILE__, __LINE__);
}
u.create(rows * ndisp, cols, msg_type);
d.create(rows * ndisp, cols, msg_type);
l.create(rows * ndisp, cols, msg_type);
r.create(rows * ndisp, cols, msg_type);
if (levels & 1)
{
//can clear less area
u = zero;
d = zero;
l = zero;
r = zero;
}
if (levels > 1)
{
int less_rows = (rows + 1) / 2;
int less_cols = (cols + 1) / 2;
u2.create(less_rows * ndisp, less_cols, msg_type);
d2.create(less_rows * ndisp, less_cols, msg_type);
l2.create(less_rows * ndisp, less_cols, msg_type);
r2.create(less_rows * ndisp, less_cols, msg_type);
if ((levels & 1) == 0)
{
u2 = zero;
d2 = zero;
l2 = zero;
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r2 = zero;
}
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}
impl::load_constants(ndisp, max_data_term, msg_scale * data_weight, msg_scale * max_disc_term, msg_scale * disc_single_jump);
datas.resize(levels);
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AutoBuffer<int> buf(levels << 1);
int* cols_all = buf;
int* rows_all = cols_all + levels;
cols_all[0] = cols;
rows_all[0] = rows;
datas[0].create(rows * ndisp, cols, msg_type);
impl::comp_data(msg_type, left, right, datas.front(), stream);
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for (int i = 1; i < levels; i++)
{
cols_all[i] = (cols_all[i-1] + 1) / 2;
rows_all[i] = (rows_all[i-1] + 1) / 2;
datas[i].create(rows_all[i] * ndisp, cols_all[i], msg_type);
impl::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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DevMem2D mus[] = {u, u2};
DevMem2D mds[] = {d, d2};
DevMem2D mrs[] = {r, r2};
DevMem2D mls[] = {l, l2};
int mem_idx = (levels & 1) ? 0 : 1;
for (int i = levels - 1; i >= 0; i--)
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{
// for lower level we have already computed messages by setting to zero
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if (i != levels - 1)
impl::level_up_messages(mem_idx, cols_all[i], rows_all[i], rows_all[i+1], msg_type, mus, mds, mls, mrs, stream);
impl::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);
mem_idx = (mem_idx + 1) & 1;
}
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if (disp.empty())
disp.create(rows, cols, CV_16S);
if (disp.type() == CV_16S)
{
disp = zero;
impl::output(msg_type, u, d, l, r, datas.front(), disp, stream);
}
else
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{
out.create(rows, cols, CV_16S);
out = zero;
impl::output(msg_type, u, d, l, r, datas.front(), out, stream);
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out.convertTo(disp, disp.type());
}
}
void cv::gpu::StereoBeliefPropagation_GPU::operator()(const GpuMat& left, const GpuMat& right, GpuMat& disp)
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{
::stereo_bp_gpu_operator(ndisp, iters, levels, max_data_term, data_weight, max_disc_term, disc_single_jump, msg_type, msg_scale, u, d, l, r, u2, d2, l2, r2, datas, out, left, right, disp, 0);
}
void cv::gpu::StereoBeliefPropagation_GPU::operator()(const GpuMat& left, const GpuMat& right, GpuMat& disp, const CudaStream& stream)
{
::stereo_bp_gpu_operator(ndisp, iters, levels, max_data_term, data_weight, max_disc_term, disc_single_jump, msg_type, msg_scale, u, d, l, r, u2, d2, l2, r2, datas, out, left, right, disp, StreamAccessor::getStream(stream));
}
bool cv::gpu::StereoBeliefPropagation_GPU::checkIfGpuCallReasonable()
{
if (0 == getCudaEnabledDeviceCount())
return false;
int device = getDevice();
int minor, major;
getComputeCapability(device, &major, &minor);
int numSM = getNumberOfSMs(device);
if (major > 1 || numSM > 16)
return true;
return false;
}
#endif /* !defined (HAVE_CUDA) */