gpustereo module for stereo correspondence

This commit is contained in:
Vladislav Vinogradov 2013-04-18 10:30:04 +04:00
parent cad9518928
commit 28b1caa730
38 changed files with 786 additions and 609 deletions

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@ -7,7 +7,7 @@ set(the_description "GPU-accelerated Computer Vision")
ocv_warnings_disable(CMAKE_CXX_FLAGS -Wundef -Wmissing-declarations -Wshadow -Wunused-parameter)
ocv_define_module(gpu opencv_gpuarithm opencv_gpufilters opencv_gpuwarping opencv_gpuimgproc
opencv_gpufeatures2d opencv_gpuvideo opencv_gpucalib3d opencv_gpuobjdetect)
opencv_gpufeatures2d opencv_gpuvideo opencv_gpustereo opencv_gpuobjdetect)
if(HAVE_CUDA)
add_subdirectory(perf4au)

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@ -0,0 +1,36 @@
Camera Calibration and 3D Reconstruction
========================================
.. highlight:: cpp
gpu::solvePnPRansac
-------------------
Finds the object pose from 3D-2D point correspondences.
.. ocv:function:: void gpu::solvePnPRansac(const Mat& object, const Mat& image, const Mat& camera_mat, const Mat& dist_coef, Mat& rvec, Mat& tvec, bool use_extrinsic_guess=false, int num_iters=100, float max_dist=8.0, int min_inlier_count=100, vector<int>* inliers=NULL)
:param object: Single-row matrix of object points.
:param image: Single-row matrix of image points.
:param camera_mat: 3x3 matrix of intrinsic camera parameters.
:param dist_coef: Distortion coefficients. See :ocv:func:`undistortPoints` for details.
:param rvec: Output 3D rotation vector.
:param tvec: Output 3D translation vector.
:param use_extrinsic_guess: Flag to indicate that the function must use ``rvec`` and ``tvec`` as an initial transformation guess. It is not supported for now.
:param num_iters: Maximum number of RANSAC iterations.
:param max_dist: Euclidean distance threshold to detect whether point is inlier or not.
:param min_inlier_count: Flag to indicate that the function must stop if greater or equal number of inliers is achieved. It is not supported for now.
:param inliers: Output vector of inlier indices.
.. seealso:: :ocv:func:`solvePnPRansac`

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@ -50,7 +50,7 @@
#include "opencv2/gpuimgproc.hpp"
#include "opencv2/gpufeatures2d.hpp"
#include "opencv2/gpuvideo.hpp"
#include "opencv2/gpucalib3d.hpp"
#include "opencv2/gpustereo.hpp"
#include "opencv2/gpuobjdetect.hpp"
namespace cv { namespace gpu {
@ -71,6 +71,18 @@ CV_EXPORTS void connectivityMask(const GpuMat& image, GpuMat& mask, const cv::Sc
//! performs connected componnents labeling.
CV_EXPORTS void labelComponents(const GpuMat& mask, GpuMat& components, int flags = 0, Stream& stream = Stream::Null());
CV_EXPORTS void transformPoints(const GpuMat& src, const Mat& rvec, const Mat& tvec,
GpuMat& dst, Stream& stream = Stream::Null());
CV_EXPORTS void projectPoints(const GpuMat& src, const Mat& rvec, const Mat& tvec,
const Mat& camera_mat, const Mat& dist_coef, GpuMat& dst,
Stream& stream = Stream::Null());
CV_EXPORTS void solvePnPRansac(const Mat& object, const Mat& image, const Mat& camera_mat,
const Mat& dist_coef, Mat& rvec, Mat& tvec, bool use_extrinsic_guess=false,
int num_iters=100, float max_dist=8.0, int min_inlier_count=100,
std::vector<int>* inliers=NULL);
//! removes points (CV_32FC2, single row matrix) with zero mask value
CV_EXPORTS void compactPoints(GpuMat &points0, GpuMat &points1, const GpuMat &mask);

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@ -0,0 +1,135 @@
/*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.
//
//
// 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,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "perf_precomp.hpp"
using namespace std;
using namespace testing;
using namespace perf;
DEF_PARAM_TEST_1(Count, int);
//////////////////////////////////////////////////////////////////////
// ProjectPoints
PERF_TEST_P(Count, Calib3D_ProjectPoints,
Values(5000, 10000, 20000))
{
const int count = GetParam();
cv::Mat src(1, count, CV_32FC3);
declare.in(src, WARMUP_RNG);
const cv::Mat rvec = cv::Mat::ones(1, 3, CV_32FC1);
const cv::Mat tvec = cv::Mat::ones(1, 3, CV_32FC1);
const cv::Mat camera_mat = cv::Mat::ones(3, 3, CV_32FC1);
if (PERF_RUN_GPU())
{
const cv::gpu::GpuMat d_src(src);
cv::gpu::GpuMat dst;
TEST_CYCLE() cv::gpu::projectPoints(d_src, rvec, tvec, camera_mat, cv::Mat(), dst);
GPU_SANITY_CHECK(dst);
}
else
{
cv::Mat dst;
TEST_CYCLE() cv::projectPoints(src, rvec, tvec, camera_mat, cv::noArray(), dst);
CPU_SANITY_CHECK(dst);
}
}
//////////////////////////////////////////////////////////////////////
// SolvePnPRansac
PERF_TEST_P(Count, Calib3D_SolvePnPRansac,
Values(5000, 10000, 20000))
{
declare.time(10.0);
const int count = GetParam();
cv::Mat object(1, count, CV_32FC3);
declare.in(object, WARMUP_RNG);
cv::Mat camera_mat(3, 3, CV_32FC1);
cv::randu(camera_mat, 0.5, 1);
camera_mat.at<float>(0, 1) = 0.f;
camera_mat.at<float>(1, 0) = 0.f;
camera_mat.at<float>(2, 0) = 0.f;
camera_mat.at<float>(2, 1) = 0.f;
const cv::Mat dist_coef(1, 8, CV_32F, cv::Scalar::all(0));
cv::Mat rvec_gold(1, 3, CV_32FC1);
cv::randu(rvec_gold, 0, 1);
cv::Mat tvec_gold(1, 3, CV_32FC1);
cv::randu(tvec_gold, 0, 1);
std::vector<cv::Point2f> image_vec;
cv::projectPoints(object, rvec_gold, tvec_gold, camera_mat, dist_coef, image_vec);
const cv::Mat image(1, count, CV_32FC2, &image_vec[0]);
cv::Mat rvec;
cv::Mat tvec;
if (PERF_RUN_GPU())
{
TEST_CYCLE() cv::gpu::solvePnPRansac(object, image, camera_mat, dist_coef, rvec, tvec);
GPU_SANITY_CHECK(rvec, 1e-3);
GPU_SANITY_CHECK(tvec, 1e-3);
}
else
{
TEST_CYCLE() cv::solvePnPRansac(object, image, camera_mat, dist_coef, rvec, tvec);
CPU_SANITY_CHECK(rvec, 1e-6);
CPU_SANITY_CHECK(tvec, 1e-6);
}
}

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@ -55,6 +55,7 @@
#include "opencv2/ts/gpu_perf.hpp"
#include "opencv2/gpu.hpp"
#include "opencv2/calib3d.hpp"
#ifdef GTEST_CREATE_SHARED_LIBRARY
#error no modules except ts should have GTEST_CREATE_SHARED_LIBRARY defined

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@ -50,8 +50,6 @@ using namespace cv::gpu;
void cv::gpu::transformPoints(const GpuMat&, const Mat&, const Mat&, GpuMat&, Stream&) { throw_no_cuda(); }
void cv::gpu::projectPoints(const GpuMat&, const Mat&, const Mat&, const Mat&, const Mat&, GpuMat&, Stream&) { throw_no_cuda(); }
void cv::gpu::solvePnPRansac(const Mat&, const Mat&, const Mat&, const Mat&, Mat&, Mat&, bool, int, float, int, std::vector<int>*) { throw_no_cuda(); }
void cv::gpu::reprojectImageTo3D(const GpuMat&, GpuMat&, const Mat&, int, Stream&) { throw_no_cuda(); }
void cv::gpu::drawColorDisp(const GpuMat&, GpuMat&, int, Stream&) { throw_no_cuda(); }
#else
@ -289,66 +287,4 @@ void cv::gpu::solvePnPRansac(const Mat& object, const Mat& image, const Mat& cam
}
}
////////////////////////////////////////////////////////////////////////
// reprojectImageTo3D
namespace cv { namespace gpu { namespace cudev
{
template <typename T, typename D>
void reprojectImageTo3D_gpu(const PtrStepSzb disp, PtrStepSzb xyz, const float* q, cudaStream_t stream);
}}}
void cv::gpu::reprojectImageTo3D(const GpuMat& disp, GpuMat& xyz, const Mat& Q, int dst_cn, Stream& stream)
{
using namespace cv::gpu::cudev;
typedef void (*func_t)(const PtrStepSzb disp, PtrStepSzb xyz, const float* q, cudaStream_t stream);
static const func_t funcs[2][4] =
{
{reprojectImageTo3D_gpu<uchar, float3>, 0, 0, reprojectImageTo3D_gpu<short, float3>},
{reprojectImageTo3D_gpu<uchar, float4>, 0, 0, reprojectImageTo3D_gpu<short, float4>}
};
CV_Assert(disp.type() == CV_8U || disp.type() == CV_16S);
CV_Assert(Q.type() == CV_32F && Q.rows == 4 && Q.cols == 4 && Q.isContinuous());
CV_Assert(dst_cn == 3 || dst_cn == 4);
xyz.create(disp.size(), CV_MAKE_TYPE(CV_32F, dst_cn));
funcs[dst_cn == 4][disp.type()](disp, xyz, Q.ptr<float>(), StreamAccessor::getStream(stream));
}
////////////////////////////////////////////////////////////////////////
// drawColorDisp
namespace cv { namespace gpu { namespace cudev
{
void drawColorDisp_gpu(const PtrStepSzb& src, const PtrStepSzb& dst, int ndisp, const cudaStream_t& stream);
void drawColorDisp_gpu(const PtrStepSz<short>& src, const PtrStepSzb& dst, int ndisp, const cudaStream_t& stream);
}}}
namespace
{
template <typename T>
void drawColorDisp_caller(const GpuMat& src, GpuMat& dst, int ndisp, const cudaStream_t& stream)
{
using namespace ::cv::gpu::cudev;
dst.create(src.size(), CV_8UC4);
drawColorDisp_gpu((PtrStepSz<T>)src, dst, ndisp, stream);
}
typedef void (*drawColorDisp_caller_t)(const GpuMat& src, GpuMat& dst, int ndisp, const cudaStream_t& stream);
const drawColorDisp_caller_t drawColorDisp_callers[] = {drawColorDisp_caller<unsigned char>, 0, 0, drawColorDisp_caller<short>, 0, 0, 0, 0};
}
void cv::gpu::drawColorDisp(const GpuMat& src, GpuMat& dst, int ndisp, Stream& stream)
{
CV_Assert(src.type() == CV_8U || src.type() == CV_16S);
drawColorDisp_callers[src.type()](src, dst, ndisp, StreamAccessor::getStream(stream));
}
#endif

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@ -187,189 +187,6 @@ namespace cv { namespace gpu { namespace cudev
cudaSafeCall( cudaDeviceSynchronize() );
}
} // namespace solvepnp_ransac
/////////////////////////////////// reprojectImageTo3D ///////////////////////////////////////////////
__constant__ float cq[16];
template <typename T, typename D>
__global__ void reprojectImageTo3D(const PtrStepSz<T> disp, PtrStep<D> xyz)
{
const int x = blockIdx.x * blockDim.x + threadIdx.x;
const int y = blockIdx.y * blockDim.y + threadIdx.y;
if (y >= disp.rows || x >= disp.cols)
return;
const float qx = x * cq[ 0] + y * cq[ 1] + cq[ 3];
const float qy = x * cq[ 4] + y * cq[ 5] + cq[ 7];
const float qz = x * cq[ 8] + y * cq[ 9] + cq[11];
const float qw = x * cq[12] + y * cq[13] + cq[15];
const T d = disp(y, x);
const float iW = 1.f / (qw + cq[14] * d);
D v = VecTraits<D>::all(1.0f);
v.x = (qx + cq[2] * d) * iW;
v.y = (qy + cq[6] * d) * iW;
v.z = (qz + cq[10] * d) * iW;
xyz(y, x) = v;
}
template <typename T, typename D>
void reprojectImageTo3D_gpu(const PtrStepSzb disp, PtrStepSzb xyz, const float* q, cudaStream_t stream)
{
dim3 block(32, 8);
dim3 grid(divUp(disp.cols, block.x), divUp(disp.rows, block.y));
cudaSafeCall( cudaMemcpyToSymbol(cq, q, 16 * sizeof(float)) );
reprojectImageTo3D<T, D><<<grid, block, 0, stream>>>((PtrStepSz<T>)disp, (PtrStepSz<D>)xyz);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
template void reprojectImageTo3D_gpu<uchar, float3>(const PtrStepSzb disp, PtrStepSzb xyz, const float* q, cudaStream_t stream);
template void reprojectImageTo3D_gpu<uchar, float4>(const PtrStepSzb disp, PtrStepSzb xyz, const float* q, cudaStream_t stream);
template void reprojectImageTo3D_gpu<short, float3>(const PtrStepSzb disp, PtrStepSzb xyz, const float* q, cudaStream_t stream);
template void reprojectImageTo3D_gpu<short, float4>(const PtrStepSzb disp, PtrStepSzb xyz, const float* q, cudaStream_t stream);
/////////////////////////////////// drawColorDisp ///////////////////////////////////////////////
template <typename T>
__device__ unsigned int cvtPixel(T d, int ndisp, float S = 1, float V = 1)
{
unsigned int H = ((ndisp-d) * 240)/ndisp;
unsigned int hi = (H/60) % 6;
float f = H/60.f - H/60;
float p = V * (1 - S);
float q = V * (1 - f * S);
float t = V * (1 - (1 - f) * S);
float3 res;
if (hi == 0) //R = V, G = t, B = p
{
res.x = p;
res.y = t;
res.z = V;
}
if (hi == 1) // R = q, G = V, B = p
{
res.x = p;
res.y = V;
res.z = q;
}
if (hi == 2) // R = p, G = V, B = t
{
res.x = t;
res.y = V;
res.z = p;
}
if (hi == 3) // R = p, G = q, B = V
{
res.x = V;
res.y = q;
res.z = p;
}
if (hi == 4) // R = t, G = p, B = V
{
res.x = V;
res.y = p;
res.z = t;
}
if (hi == 5) // R = V, G = p, B = q
{
res.x = q;
res.y = p;
res.z = V;
}
const unsigned int b = (unsigned int)(::max(0.f, ::min(res.x, 1.f)) * 255.f);
const unsigned int g = (unsigned int)(::max(0.f, ::min(res.y, 1.f)) * 255.f);
const unsigned int r = (unsigned int)(::max(0.f, ::min(res.z, 1.f)) * 255.f);
const unsigned int a = 255U;
return (a << 24) + (r << 16) + (g << 8) + b;
}
__global__ void drawColorDisp(uchar* disp, size_t disp_step, uchar* out_image, size_t out_step, int width, int height, int ndisp)
{
const int x = (blockIdx.x * blockDim.x + threadIdx.x) << 2;
const int y = blockIdx.y * blockDim.y + threadIdx.y;
if(x < width && y < height)
{
uchar4 d4 = *(uchar4*)(disp + y * disp_step + x);
uint4 res;
res.x = cvtPixel(d4.x, ndisp);
res.y = cvtPixel(d4.y, ndisp);
res.z = cvtPixel(d4.z, ndisp);
res.w = cvtPixel(d4.w, ndisp);
uint4* line = (uint4*)(out_image + y * out_step);
line[x >> 2] = res;
}
}
__global__ void drawColorDisp(short* disp, size_t disp_step, uchar* out_image, size_t out_step, int width, int height, int ndisp)
{
const int x = (blockIdx.x * blockDim.x + threadIdx.x) << 1;
const int y = blockIdx.y * blockDim.y + threadIdx.y;
if(x < width && y < height)
{
short2 d2 = *(short2*)(disp + y * disp_step + x);
uint2 res;
res.x = cvtPixel(d2.x, ndisp);
res.y = cvtPixel(d2.y, ndisp);
uint2* line = (uint2*)(out_image + y * out_step);
line[x >> 1] = res;
}
}
void drawColorDisp_gpu(const PtrStepSzb& src, const PtrStepSzb& dst, int ndisp, const cudaStream_t& stream)
{
dim3 threads(16, 16, 1);
dim3 grid(1, 1, 1);
grid.x = divUp(src.cols, threads.x << 2);
grid.y = divUp(src.rows, threads.y);
drawColorDisp<<<grid, threads, 0, stream>>>(src.data, src.step, dst.data, dst.step, src.cols, src.rows, ndisp);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
void drawColorDisp_gpu(const PtrStepSz<short>& src, const PtrStepSzb& dst, int ndisp, const cudaStream_t& stream)
{
dim3 threads(32, 8, 1);
dim3 grid(1, 1, 1);
grid.x = divUp(src.cols, threads.x << 1);
grid.y = divUp(src.rows, threads.y);
drawColorDisp<<<grid, threads, 0, stream>>>(src.data, src.step / sizeof(short), dst.data, dst.step, src.cols, src.rows, ndisp);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
}}} // namespace cv { namespace gpu { namespace cudev

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@ -44,6 +44,7 @@
#define __OPENCV_PRECOMP_H__
#include "opencv2/gpu.hpp"
#include "opencv2/calib3d.hpp"
#include "opencv2/core/gpu_private.hpp"

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@ -46,123 +46,6 @@
using namespace cvtest;
//////////////////////////////////////////////////////////////////////////
// StereoBM
struct StereoBM : testing::TestWithParam<cv::gpu::DeviceInfo>
{
cv::gpu::DeviceInfo devInfo;
virtual void SetUp()
{
devInfo = GetParam();
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(StereoBM, Regression)
{
cv::Mat left_image = readImage("stereobm/aloe-L.png", cv::IMREAD_GRAYSCALE);
cv::Mat right_image = readImage("stereobm/aloe-R.png", cv::IMREAD_GRAYSCALE);
cv::Mat disp_gold = readImage("stereobm/aloe-disp.png", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(left_image.empty());
ASSERT_FALSE(right_image.empty());
ASSERT_FALSE(disp_gold.empty());
cv::gpu::StereoBM_GPU bm(0, 128, 19);
cv::gpu::GpuMat disp;
bm(loadMat(left_image), loadMat(right_image), disp);
EXPECT_MAT_NEAR(disp_gold, disp, 0.0);
}
INSTANTIATE_TEST_CASE_P(GPU_Calib3D, StereoBM, ALL_DEVICES);
//////////////////////////////////////////////////////////////////////////
// StereoBeliefPropagation
struct StereoBeliefPropagation : testing::TestWithParam<cv::gpu::DeviceInfo>
{
cv::gpu::DeviceInfo devInfo;
virtual void SetUp()
{
devInfo = GetParam();
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(StereoBeliefPropagation, Regression)
{
cv::Mat left_image = readImage("stereobp/aloe-L.png");
cv::Mat right_image = readImage("stereobp/aloe-R.png");
cv::Mat disp_gold = readImage("stereobp/aloe-disp.png", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(left_image.empty());
ASSERT_FALSE(right_image.empty());
ASSERT_FALSE(disp_gold.empty());
cv::gpu::StereoBeliefPropagation bp(64, 8, 2, 25, 0.1f, 15, 1, CV_16S);
cv::gpu::GpuMat disp;
bp(loadMat(left_image), loadMat(right_image), disp);
cv::Mat h_disp(disp);
h_disp.convertTo(h_disp, disp_gold.depth());
EXPECT_MAT_NEAR(disp_gold, h_disp, 0.0);
}
INSTANTIATE_TEST_CASE_P(GPU_Calib3D, StereoBeliefPropagation, ALL_DEVICES);
//////////////////////////////////////////////////////////////////////////
// StereoConstantSpaceBP
struct StereoConstantSpaceBP : testing::TestWithParam<cv::gpu::DeviceInfo>
{
cv::gpu::DeviceInfo devInfo;
virtual void SetUp()
{
devInfo = GetParam();
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(StereoConstantSpaceBP, Regression)
{
cv::Mat left_image = readImage("csstereobp/aloe-L.png");
cv::Mat right_image = readImage("csstereobp/aloe-R.png");
cv::Mat disp_gold;
if (supportFeature(devInfo, cv::gpu::FEATURE_SET_COMPUTE_20))
disp_gold = readImage("csstereobp/aloe-disp.png", cv::IMREAD_GRAYSCALE);
else
disp_gold = readImage("csstereobp/aloe-disp_CC1X.png", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(left_image.empty());
ASSERT_FALSE(right_image.empty());
ASSERT_FALSE(disp_gold.empty());
cv::gpu::StereoConstantSpaceBP csbp(128, 16, 4, 4);
cv::gpu::GpuMat disp;
csbp(loadMat(left_image), loadMat(right_image), disp);
cv::Mat h_disp(disp);
h_disp.convertTo(h_disp, disp_gold.depth());
EXPECT_MAT_NEAR(disp_gold, h_disp, 1.0);
}
INSTANTIATE_TEST_CASE_P(GPU_Calib3D, StereoConstantSpaceBP, ALL_DEVICES);
///////////////////////////////////////////////////////////////////////////////////////////////////////
// transformPoints
@ -304,45 +187,4 @@ GPU_TEST_P(SolvePnPRansac, Accuracy)
INSTANTIATE_TEST_CASE_P(GPU_Calib3D, SolvePnPRansac, ALL_DEVICES);
////////////////////////////////////////////////////////////////////////////////
// reprojectImageTo3D
PARAM_TEST_CASE(ReprojectImageTo3D, cv::gpu::DeviceInfo, cv::Size, MatDepth, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int depth;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(ReprojectImageTo3D, Accuracy)
{
cv::Mat disp = randomMat(size, depth, 5.0, 30.0);
cv::Mat Q = randomMat(cv::Size(4, 4), CV_32FC1, 0.1, 1.0);
cv::gpu::GpuMat dst;
cv::gpu::reprojectImageTo3D(loadMat(disp, useRoi), dst, Q, 3);
cv::Mat dst_gold;
cv::reprojectImageTo3D(disp, dst_gold, Q, false);
EXPECT_MAT_NEAR(dst_gold, dst, 1e-5);
}
INSTANTIATE_TEST_CASE_P(GPU_Calib3D, ReprojectImageTo3D, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatDepth(CV_8U), MatDepth(CV_16S)),
WHOLE_SUBMAT));
#endif // HAVE_CUDA

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@ -57,5 +57,6 @@
#include "opencv2/core.hpp"
#include "opencv2/core/opengl.hpp"
#include "opencv2/gpu.hpp"
#include "opencv2/calib3d.hpp"
#endif

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@ -1,9 +0,0 @@
if(ANDROID OR IOS)
ocv_module_disable(gpucalib3d)
endif()
set(the_description "GPU-accelerated Camera Calibration and 3D Reconstruction")
ocv_warnings_disable(CMAKE_CXX_FLAGS -Wundef -Wmissing-declarations)
ocv_define_module(gpucalib3d opencv_calib3d opencv_gpuarithm)

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@ -1,8 +0,0 @@
*************************************************************
gpu. GPU-accelerated Camera Calibration and 3D Reconstruction
*************************************************************
.. toctree::
:maxdepth: 1
camera_calibration_and_3d_reconstruction

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@ -0,0 +1,9 @@
if(ANDROID OR IOS)
ocv_module_disable(gpustereo)
endif()
set(the_description "GPU-accelerated Stereo Correspondence")
ocv_warnings_disable(CMAKE_CXX_FLAGS /wd4127 /wd4324 /wd4512 -Wundef -Wmissing-declarations)
ocv_define_module(gpustereo opencv_calib3d)

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@ -0,0 +1,8 @@
************************************************
gpustereo. GPU-accelerated Stereo Correspondence
************************************************
.. toctree::
:maxdepth: 1
stereo

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@ -1,5 +1,5 @@
Camera Calibration and 3D Reconstruction
========================================
Stereo Correspondence
=====================
.. highlight:: cpp
@ -462,38 +462,6 @@ Reprojects a disparity image to 3D space.
gpu::solvePnPRansac
-------------------
Finds the object pose from 3D-2D point correspondences.
.. ocv:function:: void gpu::solvePnPRansac(const Mat& object, const Mat& image, const Mat& camera_mat, const Mat& dist_coef, Mat& rvec, Mat& tvec, bool use_extrinsic_guess=false, int num_iters=100, float max_dist=8.0, int min_inlier_count=100, vector<int>* inliers=NULL)
:param object: Single-row matrix of object points.
:param image: Single-row matrix of image points.
:param camera_mat: 3x3 matrix of intrinsic camera parameters.
:param dist_coef: Distortion coefficients. See :ocv:func:`undistortPoints` for details.
:param rvec: Output 3D rotation vector.
:param tvec: Output 3D translation vector.
:param use_extrinsic_guess: Flag to indicate that the function must use ``rvec`` and ``tvec`` as an initial transformation guess. It is not supported for now.
:param num_iters: Maximum number of RANSAC iterations.
:param max_dist: Euclidean distance threshold to detect whether point is inlier or not.
:param min_inlier_count: Flag to indicate that the function must stop if greater or equal number of inliers is achieved. It is not supported for now.
:param inliers: Output vector of inlier indices.
.. seealso:: :ocv:func:`solvePnPRansac`
.. [Felzenszwalb2006] Pedro F. Felzenszwalb algorithm [Pedro F. Felzenszwalb and Daniel P. Huttenlocher. *Efficient belief propagation for early vision*. International Journal of Computer Vision, 70(1), October 2006
.. [Yang2010] Q. Yang, L. Wang, and N. Ahuja. *A constant-space belief propagation algorithm for stereo matching*. In CVPR, 2010.

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@ -40,8 +40,12 @@
//
//M*/
#ifndef __OPENCV_GPUCALIB3D_HPP__
#define __OPENCV_GPUCALIB3D_HPP__
#ifndef __OPENCV_GPUSTEREO_HPP__
#define __OPENCV_GPUSTEREO_HPP__
#ifndef __cplusplus
# error gpustereo.hpp header must be compiled as C++
#endif
#include "opencv2/core/gpumat.hpp"
@ -226,18 +230,6 @@ private:
GpuMat table_space;
};
CV_EXPORTS void transformPoints(const GpuMat& src, const Mat& rvec, const Mat& tvec,
GpuMat& dst, Stream& stream = Stream::Null());
CV_EXPORTS void projectPoints(const GpuMat& src, const Mat& rvec, const Mat& tvec,
const Mat& camera_mat, const Mat& dist_coef, GpuMat& dst,
Stream& stream = Stream::Null());
CV_EXPORTS void solvePnPRansac(const Mat& object, const Mat& image, const Mat& camera_mat,
const Mat& dist_coef, Mat& rvec, Mat& tvec, bool use_extrinsic_guess=false,
int num_iters=100, float max_dist=8.0, int min_inlier_count=100,
std::vector<int>* inliers=NULL);
//! Reprojects disparity image to 3D space.
//! Supports CV_8U and CV_16S types of input disparity.
//! The output is a 3- or 4-channel floating-point matrix.
@ -252,4 +244,4 @@ CV_EXPORTS void drawColorDisp(const GpuMat& src_disp, GpuMat& dst_disp, int ndis
}} // namespace cv { namespace gpu {
#endif /* __OPENCV_GPUCALIB3D_HPP__ */
#endif /* __OPENCV_GPUSTEREO_HPP__ */

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@ -44,4 +44,4 @@
using namespace perf;
CV_PERF_TEST_MAIN(gpuarithm, printCudaInfo())
CV_PERF_TEST_MAIN(gpustereo, printCudaInfo())

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@ -54,8 +54,7 @@
#include "opencv2/ts.hpp"
#include "opencv2/ts/gpu_perf.hpp"
#include "opencv2/gpucalib3d.hpp"
#include "opencv2/gpustereo.hpp"
#include "opencv2/calib3d.hpp"
#ifdef GTEST_CREATE_SHARED_LIBRARY

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@ -52,7 +52,7 @@ using namespace perf;
typedef std::tr1::tuple<string, string> pair_string;
DEF_PARAM_TEST_1(ImagePair, pair_string);
PERF_TEST_P(ImagePair, Calib3D_StereoBM,
PERF_TEST_P(ImagePair, StereoBM,
Values(pair_string("gpu/perf/aloe.png", "gpu/perf/aloeR.png")))
{
declare.time(300.0);
@ -93,7 +93,7 @@ PERF_TEST_P(ImagePair, Calib3D_StereoBM,
//////////////////////////////////////////////////////////////////////
// StereoBeliefPropagation
PERF_TEST_P(ImagePair, Calib3D_StereoBeliefPropagation,
PERF_TEST_P(ImagePair, StereoBeliefPropagation,
Values(pair_string("gpu/stereobp/aloe-L.png", "gpu/stereobp/aloe-R.png")))
{
declare.time(300.0);
@ -127,7 +127,7 @@ PERF_TEST_P(ImagePair, Calib3D_StereoBeliefPropagation,
//////////////////////////////////////////////////////////////////////
// StereoConstantSpaceBP
PERF_TEST_P(ImagePair, Calib3D_StereoConstantSpaceBP,
PERF_TEST_P(ImagePair, StereoConstantSpaceBP,
Values(pair_string("gpu/stereobm/aloe-L.png", "gpu/stereobm/aloe-R.png")))
{
declare.time(300.0);
@ -161,7 +161,7 @@ PERF_TEST_P(ImagePair, Calib3D_StereoConstantSpaceBP,
//////////////////////////////////////////////////////////////////////
// DisparityBilateralFilter
PERF_TEST_P(ImagePair, Calib3D_DisparityBilateralFilter,
PERF_TEST_P(ImagePair, DisparityBilateralFilter,
Values(pair_string("gpu/stereobm/aloe-L.png", "gpu/stereobm/aloe-disp.png")))
{
const cv::Mat img = readImage(GET_PARAM(0), cv::IMREAD_GRAYSCALE);
@ -190,127 +190,10 @@ PERF_TEST_P(ImagePair, Calib3D_DisparityBilateralFilter,
}
}
//////////////////////////////////////////////////////////////////////
// TransformPoints
DEF_PARAM_TEST_1(Count, int);
PERF_TEST_P(Count, Calib3D_TransformPoints,
Values(5000, 10000, 20000))
{
const int count = GetParam();
cv::Mat src(1, count, CV_32FC3);
declare.in(src, WARMUP_RNG);
const cv::Mat rvec = cv::Mat::ones(1, 3, CV_32FC1);
const cv::Mat tvec = cv::Mat::ones(1, 3, CV_32FC1);
if (PERF_RUN_GPU())
{
const cv::gpu::GpuMat d_src(src);
cv::gpu::GpuMat dst;
TEST_CYCLE() cv::gpu::transformPoints(d_src, rvec, tvec, dst);
GPU_SANITY_CHECK(dst);
}
else
{
FAIL_NO_CPU();
}
}
//////////////////////////////////////////////////////////////////////
// ProjectPoints
PERF_TEST_P(Count, Calib3D_ProjectPoints,
Values(5000, 10000, 20000))
{
const int count = GetParam();
cv::Mat src(1, count, CV_32FC3);
declare.in(src, WARMUP_RNG);
const cv::Mat rvec = cv::Mat::ones(1, 3, CV_32FC1);
const cv::Mat tvec = cv::Mat::ones(1, 3, CV_32FC1);
const cv::Mat camera_mat = cv::Mat::ones(3, 3, CV_32FC1);
if (PERF_RUN_GPU())
{
const cv::gpu::GpuMat d_src(src);
cv::gpu::GpuMat dst;
TEST_CYCLE() cv::gpu::projectPoints(d_src, rvec, tvec, camera_mat, cv::Mat(), dst);
GPU_SANITY_CHECK(dst);
}
else
{
cv::Mat dst;
TEST_CYCLE() cv::projectPoints(src, rvec, tvec, camera_mat, cv::noArray(), dst);
CPU_SANITY_CHECK(dst);
}
}
//////////////////////////////////////////////////////////////////////
// SolvePnPRansac
PERF_TEST_P(Count, Calib3D_SolvePnPRansac,
Values(5000, 10000, 20000))
{
declare.time(10.0);
const int count = GetParam();
cv::Mat object(1, count, CV_32FC3);
declare.in(object, WARMUP_RNG);
cv::Mat camera_mat(3, 3, CV_32FC1);
cv::randu(camera_mat, 0.5, 1);
camera_mat.at<float>(0, 1) = 0.f;
camera_mat.at<float>(1, 0) = 0.f;
camera_mat.at<float>(2, 0) = 0.f;
camera_mat.at<float>(2, 1) = 0.f;
const cv::Mat dist_coef(1, 8, CV_32F, cv::Scalar::all(0));
cv::Mat rvec_gold(1, 3, CV_32FC1);
cv::randu(rvec_gold, 0, 1);
cv::Mat tvec_gold(1, 3, CV_32FC1);
cv::randu(tvec_gold, 0, 1);
std::vector<cv::Point2f> image_vec;
cv::projectPoints(object, rvec_gold, tvec_gold, camera_mat, dist_coef, image_vec);
const cv::Mat image(1, count, CV_32FC2, &image_vec[0]);
cv::Mat rvec;
cv::Mat tvec;
if (PERF_RUN_GPU())
{
TEST_CYCLE() cv::gpu::solvePnPRansac(object, image, camera_mat, dist_coef, rvec, tvec);
GPU_SANITY_CHECK(rvec, 1e-3);
GPU_SANITY_CHECK(tvec, 1e-3);
}
else
{
TEST_CYCLE() cv::solvePnPRansac(object, image, camera_mat, dist_coef, rvec, tvec);
CPU_SANITY_CHECK(rvec, 1e-6);
CPU_SANITY_CHECK(tvec, 1e-6);
}
}
//////////////////////////////////////////////////////////////////////
// ReprojectImageTo3D
PERF_TEST_P(Sz_Depth, Calib3D_ReprojectImageTo3D,
PERF_TEST_P(Sz_Depth, ReprojectImageTo3D,
Combine(GPU_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_16S)))
{
@ -345,7 +228,7 @@ PERF_TEST_P(Sz_Depth, Calib3D_ReprojectImageTo3D,
//////////////////////////////////////////////////////////////////////
// DrawColorDisp
PERF_TEST_P(Sz_Depth, Calib3D_DrawColorDisp,
PERF_TEST_P(Sz_Depth, DrawColorDisp,
Combine(GPU_TYPICAL_MAT_SIZES,
Values(CV_8U, CV_16S)))
{

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@ -0,0 +1,235 @@
/*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.
//
//
// 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,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#if !defined CUDA_DISABLER
#include "opencv2/core/cuda/common.hpp"
#include "opencv2/core/cuda/transform.hpp"
#include "opencv2/core/cuda/functional.hpp"
#include "opencv2/core/cuda/reduce.hpp"
namespace cv { namespace gpu { namespace cudev
{
/////////////////////////////////// reprojectImageTo3D ///////////////////////////////////////////////
__constant__ float cq[16];
template <typename T, typename D>
__global__ void reprojectImageTo3D(const PtrStepSz<T> disp, PtrStep<D> xyz)
{
const int x = blockIdx.x * blockDim.x + threadIdx.x;
const int y = blockIdx.y * blockDim.y + threadIdx.y;
if (y >= disp.rows || x >= disp.cols)
return;
const float qx = x * cq[ 0] + y * cq[ 1] + cq[ 3];
const float qy = x * cq[ 4] + y * cq[ 5] + cq[ 7];
const float qz = x * cq[ 8] + y * cq[ 9] + cq[11];
const float qw = x * cq[12] + y * cq[13] + cq[15];
const T d = disp(y, x);
const float iW = 1.f / (qw + cq[14] * d);
D v = VecTraits<D>::all(1.0f);
v.x = (qx + cq[2] * d) * iW;
v.y = (qy + cq[6] * d) * iW;
v.z = (qz + cq[10] * d) * iW;
xyz(y, x) = v;
}
template <typename T, typename D>
void reprojectImageTo3D_gpu(const PtrStepSzb disp, PtrStepSzb xyz, const float* q, cudaStream_t stream)
{
dim3 block(32, 8);
dim3 grid(divUp(disp.cols, block.x), divUp(disp.rows, block.y));
cudaSafeCall( cudaMemcpyToSymbol(cq, q, 16 * sizeof(float)) );
reprojectImageTo3D<T, D><<<grid, block, 0, stream>>>((PtrStepSz<T>)disp, (PtrStepSz<D>)xyz);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
template void reprojectImageTo3D_gpu<uchar, float3>(const PtrStepSzb disp, PtrStepSzb xyz, const float* q, cudaStream_t stream);
template void reprojectImageTo3D_gpu<uchar, float4>(const PtrStepSzb disp, PtrStepSzb xyz, const float* q, cudaStream_t stream);
template void reprojectImageTo3D_gpu<short, float3>(const PtrStepSzb disp, PtrStepSzb xyz, const float* q, cudaStream_t stream);
template void reprojectImageTo3D_gpu<short, float4>(const PtrStepSzb disp, PtrStepSzb xyz, const float* q, cudaStream_t stream);
/////////////////////////////////// drawColorDisp ///////////////////////////////////////////////
template <typename T>
__device__ unsigned int cvtPixel(T d, int ndisp, float S = 1, float V = 1)
{
unsigned int H = ((ndisp-d) * 240)/ndisp;
unsigned int hi = (H/60) % 6;
float f = H/60.f - H/60;
float p = V * (1 - S);
float q = V * (1 - f * S);
float t = V * (1 - (1 - f) * S);
float3 res;
if (hi == 0) //R = V, G = t, B = p
{
res.x = p;
res.y = t;
res.z = V;
}
if (hi == 1) // R = q, G = V, B = p
{
res.x = p;
res.y = V;
res.z = q;
}
if (hi == 2) // R = p, G = V, B = t
{
res.x = t;
res.y = V;
res.z = p;
}
if (hi == 3) // R = p, G = q, B = V
{
res.x = V;
res.y = q;
res.z = p;
}
if (hi == 4) // R = t, G = p, B = V
{
res.x = V;
res.y = p;
res.z = t;
}
if (hi == 5) // R = V, G = p, B = q
{
res.x = q;
res.y = p;
res.z = V;
}
const unsigned int b = (unsigned int)(::max(0.f, ::min(res.x, 1.f)) * 255.f);
const unsigned int g = (unsigned int)(::max(0.f, ::min(res.y, 1.f)) * 255.f);
const unsigned int r = (unsigned int)(::max(0.f, ::min(res.z, 1.f)) * 255.f);
const unsigned int a = 255U;
return (a << 24) + (r << 16) + (g << 8) + b;
}
__global__ void drawColorDisp(uchar* disp, size_t disp_step, uchar* out_image, size_t out_step, int width, int height, int ndisp)
{
const int x = (blockIdx.x * blockDim.x + threadIdx.x) << 2;
const int y = blockIdx.y * blockDim.y + threadIdx.y;
if(x < width && y < height)
{
uchar4 d4 = *(uchar4*)(disp + y * disp_step + x);
uint4 res;
res.x = cvtPixel(d4.x, ndisp);
res.y = cvtPixel(d4.y, ndisp);
res.z = cvtPixel(d4.z, ndisp);
res.w = cvtPixel(d4.w, ndisp);
uint4* line = (uint4*)(out_image + y * out_step);
line[x >> 2] = res;
}
}
__global__ void drawColorDisp(short* disp, size_t disp_step, uchar* out_image, size_t out_step, int width, int height, int ndisp)
{
const int x = (blockIdx.x * blockDim.x + threadIdx.x) << 1;
const int y = blockIdx.y * blockDim.y + threadIdx.y;
if(x < width && y < height)
{
short2 d2 = *(short2*)(disp + y * disp_step + x);
uint2 res;
res.x = cvtPixel(d2.x, ndisp);
res.y = cvtPixel(d2.y, ndisp);
uint2* line = (uint2*)(out_image + y * out_step);
line[x >> 1] = res;
}
}
void drawColorDisp_gpu(const PtrStepSzb& src, const PtrStepSzb& dst, int ndisp, const cudaStream_t& stream)
{
dim3 threads(16, 16, 1);
dim3 grid(1, 1, 1);
grid.x = divUp(src.cols, threads.x << 2);
grid.y = divUp(src.rows, threads.y);
drawColorDisp<<<grid, threads, 0, stream>>>(src.data, src.step, dst.data, dst.step, src.cols, src.rows, ndisp);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
void drawColorDisp_gpu(const PtrStepSz<short>& src, const PtrStepSzb& dst, int ndisp, const cudaStream_t& stream)
{
dim3 threads(32, 8, 1);
dim3 grid(1, 1, 1);
grid.x = divUp(src.cols, threads.x << 1);
grid.y = divUp(src.rows, threads.y);
drawColorDisp<<<grid, threads, 0, stream>>>(src.data, src.step / sizeof(short), dst.data, dst.step, src.cols, src.rows, ndisp);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
}}} // namespace cv { namespace gpu { namespace cudev
#endif /* CUDA_DISABLER */

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@ -45,11 +45,7 @@
#include <limits>
#include "opencv2/gpucalib3d.hpp"
#include "opencv2/gpuarithm.hpp"
#include "opencv2/calib3d.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/gpustereo.hpp"
#include "opencv2/core/gpu_private.hpp"

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@ -196,7 +196,7 @@ static void csbp_operator(StereoConstantSpaceBP& rthis, GpuMat& mbuf, GpuMat& te
for(int _r = 0; _r < 5; ++_r)
{
*buf_ptrs[_r] = sub2.rowRange(_r * sub2.rows/5, (_r+1) * sub2.rows/5);
assert(buf_ptrs[_r]->cols == cols && buf_ptrs[_r]->rows == rows * rthis.nr_plane);
CV_DbgAssert(buf_ptrs[_r]->cols == cols && buf_ptrs[_r]->rows == rows * rthis.nr_plane);
}
};

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@ -0,0 +1,117 @@
/*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.
//
//
// 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,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "precomp.hpp"
using namespace cv;
using namespace cv::gpu;
#if !defined HAVE_CUDA || defined(CUDA_DISABLER)
void cv::gpu::reprojectImageTo3D(const GpuMat&, GpuMat&, const Mat&, int, Stream&) { throw_no_cuda(); }
void cv::gpu::drawColorDisp(const GpuMat&, GpuMat&, int, Stream&) { throw_no_cuda(); }
#else
////////////////////////////////////////////////////////////////////////
// reprojectImageTo3D
namespace cv { namespace gpu { namespace cudev
{
template <typename T, typename D>
void reprojectImageTo3D_gpu(const PtrStepSzb disp, PtrStepSzb xyz, const float* q, cudaStream_t stream);
}}}
void cv::gpu::reprojectImageTo3D(const GpuMat& disp, GpuMat& xyz, const Mat& Q, int dst_cn, Stream& stream)
{
using namespace cv::gpu::cudev;
typedef void (*func_t)(const PtrStepSzb disp, PtrStepSzb xyz, const float* q, cudaStream_t stream);
static const func_t funcs[2][4] =
{
{reprojectImageTo3D_gpu<uchar, float3>, 0, 0, reprojectImageTo3D_gpu<short, float3>},
{reprojectImageTo3D_gpu<uchar, float4>, 0, 0, reprojectImageTo3D_gpu<short, float4>}
};
CV_Assert(disp.type() == CV_8U || disp.type() == CV_16S);
CV_Assert(Q.type() == CV_32F && Q.rows == 4 && Q.cols == 4 && Q.isContinuous());
CV_Assert(dst_cn == 3 || dst_cn == 4);
xyz.create(disp.size(), CV_MAKE_TYPE(CV_32F, dst_cn));
funcs[dst_cn == 4][disp.type()](disp, xyz, Q.ptr<float>(), StreamAccessor::getStream(stream));
}
////////////////////////////////////////////////////////////////////////
// drawColorDisp
namespace cv { namespace gpu { namespace cudev
{
void drawColorDisp_gpu(const PtrStepSzb& src, const PtrStepSzb& dst, int ndisp, const cudaStream_t& stream);
void drawColorDisp_gpu(const PtrStepSz<short>& src, const PtrStepSzb& dst, int ndisp, const cudaStream_t& stream);
}}}
namespace
{
template <typename T>
void drawColorDisp_caller(const GpuMat& src, GpuMat& dst, int ndisp, const cudaStream_t& stream)
{
using namespace ::cv::gpu::cudev;
dst.create(src.size(), CV_8UC4);
drawColorDisp_gpu((PtrStepSz<T>)src, dst, ndisp, stream);
}
typedef void (*drawColorDisp_caller_t)(const GpuMat& src, GpuMat& dst, int ndisp, const cudaStream_t& stream);
const drawColorDisp_caller_t drawColorDisp_callers[] = {drawColorDisp_caller<unsigned char>, 0, 0, drawColorDisp_caller<short>, 0, 0, 0, 0};
}
void cv::gpu::drawColorDisp(const GpuMat& src, GpuMat& dst, int ndisp, Stream& stream)
{
CV_Assert(src.type() == CV_8U || src.type() == CV_16S);
drawColorDisp_callers[src.type()](src, dst, ndisp, StreamAccessor::getStream(stream));
}
#endif

View File

@ -54,8 +54,7 @@
#include "opencv2/ts.hpp"
#include "opencv2/ts/gpu_test.hpp"
#include "opencv2/gpucalib3d.hpp"
#include "opencv2/gpustereo.hpp"
#include "opencv2/calib3d.hpp"
#endif

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@ -0,0 +1,207 @@
/*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,
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#include "test_precomp.hpp"
#ifdef HAVE_CUDA
using namespace cvtest;
//////////////////////////////////////////////////////////////////////////
// StereoBM
struct StereoBM : testing::TestWithParam<cv::gpu::DeviceInfo>
{
cv::gpu::DeviceInfo devInfo;
virtual void SetUp()
{
devInfo = GetParam();
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(StereoBM, Regression)
{
cv::Mat left_image = readImage("stereobm/aloe-L.png", cv::IMREAD_GRAYSCALE);
cv::Mat right_image = readImage("stereobm/aloe-R.png", cv::IMREAD_GRAYSCALE);
cv::Mat disp_gold = readImage("stereobm/aloe-disp.png", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(left_image.empty());
ASSERT_FALSE(right_image.empty());
ASSERT_FALSE(disp_gold.empty());
cv::gpu::StereoBM_GPU bm(0, 128, 19);
cv::gpu::GpuMat disp;
bm(loadMat(left_image), loadMat(right_image), disp);
EXPECT_MAT_NEAR(disp_gold, disp, 0.0);
}
INSTANTIATE_TEST_CASE_P(GPU_Stereo, StereoBM, ALL_DEVICES);
//////////////////////////////////////////////////////////////////////////
// StereoBeliefPropagation
struct StereoBeliefPropagation : testing::TestWithParam<cv::gpu::DeviceInfo>
{
cv::gpu::DeviceInfo devInfo;
virtual void SetUp()
{
devInfo = GetParam();
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(StereoBeliefPropagation, Regression)
{
cv::Mat left_image = readImage("stereobp/aloe-L.png");
cv::Mat right_image = readImage("stereobp/aloe-R.png");
cv::Mat disp_gold = readImage("stereobp/aloe-disp.png", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(left_image.empty());
ASSERT_FALSE(right_image.empty());
ASSERT_FALSE(disp_gold.empty());
cv::gpu::StereoBeliefPropagation bp(64, 8, 2, 25, 0.1f, 15, 1, CV_16S);
cv::gpu::GpuMat disp;
bp(loadMat(left_image), loadMat(right_image), disp);
cv::Mat h_disp(disp);
h_disp.convertTo(h_disp, disp_gold.depth());
EXPECT_MAT_NEAR(disp_gold, h_disp, 0.0);
}
INSTANTIATE_TEST_CASE_P(GPU_Stereo, StereoBeliefPropagation, ALL_DEVICES);
//////////////////////////////////////////////////////////////////////////
// StereoConstantSpaceBP
struct StereoConstantSpaceBP : testing::TestWithParam<cv::gpu::DeviceInfo>
{
cv::gpu::DeviceInfo devInfo;
virtual void SetUp()
{
devInfo = GetParam();
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(StereoConstantSpaceBP, Regression)
{
cv::Mat left_image = readImage("csstereobp/aloe-L.png");
cv::Mat right_image = readImage("csstereobp/aloe-R.png");
cv::Mat disp_gold;
if (supportFeature(devInfo, cv::gpu::FEATURE_SET_COMPUTE_20))
disp_gold = readImage("csstereobp/aloe-disp.png", cv::IMREAD_GRAYSCALE);
else
disp_gold = readImage("csstereobp/aloe-disp_CC1X.png", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(left_image.empty());
ASSERT_FALSE(right_image.empty());
ASSERT_FALSE(disp_gold.empty());
cv::gpu::StereoConstantSpaceBP csbp(128, 16, 4, 4);
cv::gpu::GpuMat disp;
csbp(loadMat(left_image), loadMat(right_image), disp);
cv::Mat h_disp(disp);
h_disp.convertTo(h_disp, disp_gold.depth());
EXPECT_MAT_NEAR(disp_gold, h_disp, 1.0);
}
INSTANTIATE_TEST_CASE_P(GPU_Stereo, StereoConstantSpaceBP, ALL_DEVICES);
////////////////////////////////////////////////////////////////////////////////
// reprojectImageTo3D
PARAM_TEST_CASE(ReprojectImageTo3D, cv::gpu::DeviceInfo, cv::Size, MatDepth, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
int depth;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
depth = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(ReprojectImageTo3D, Accuracy)
{
cv::Mat disp = randomMat(size, depth, 5.0, 30.0);
cv::Mat Q = randomMat(cv::Size(4, 4), CV_32FC1, 0.1, 1.0);
cv::gpu::GpuMat dst;
cv::gpu::reprojectImageTo3D(loadMat(disp, useRoi), dst, Q, 3);
cv::Mat dst_gold;
cv::reprojectImageTo3D(disp, dst_gold, Q, false);
EXPECT_MAT_NEAR(dst_gold, dst, 1e-5);
}
INSTANTIATE_TEST_CASE_P(GPU_Stereo, ReprojectImageTo3D, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatDepth(CV_8U), MatDepth(CV_16S)),
WHOLE_SUBMAT));
#endif // HAVE_CUDA

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@ -23,7 +23,7 @@ if(BUILD_EXAMPLES AND OCV_DEPENDENCIES_FOUND)
ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/gpuimgproc/include")
ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/gpufeatures2d/include")
ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/gpuvideo/include")
ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/gpucalib3d/include")
ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/gpustereo/include")
ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/gpuobjdetect/include")
ocv_include_directories("${OpenCV_SOURCE_DIR}/modules/gpu/include")
endif()

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@ -4,7 +4,7 @@ SET(OPENCV_GPU_SAMPLES_REQUIRED_DEPS opencv_core opencv_flann opencv_imgproc ope
opencv_nonfree opencv_softcascade opencv_superres
opencv_gpucodec opencv_gpuarithm opencv_gpufilters opencv_gpuwarping opencv_gpuimgproc
opencv_gpufeatures2d opencv_gpuvideo opencv_gpuobjdetect
opencv_gpucalib3d opencv_gpulegacy)
opencv_gpustereo opencv_gpulegacy)
ocv_check_dependencies(${OPENCV_GPU_SAMPLES_REQUIRED_DEPS})