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added support of 3-channels output to gpu::reprojectImageTo3D

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minor refactoring of gpu tests
This commit is contained in:
Vladislav Vinogradov 2012-03-28 12:48:28 +00:00
parent 07ec83cd1f
commit 8e3f1c09d2
8 changed files with 713 additions and 847 deletions
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4
modules/gpu/include/opencv2/gpu/gpu.hpp
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@ -605,10 +605,10 @@ CV_EXPORTS void drawColorDisp(const GpuMat& src_disp, GpuMat& dst_disp, int ndis
//! Reprojects disparity image to 3D space.
//! Supports CV_8U and CV_16S types of input disparity.
//! The output is a 4-channel floating-point (CV_32FC4) matrix.
//! The output is a 3- or 4-channel floating-point matrix.
//! Each element of this matrix will contain the 3D coordinates of the point (x,y,z,1), computed from the disparity map.
//! Q is the 4x4 perspective transformation matrix that can be obtained with cvStereoRectify.
CV_EXPORTS void reprojectImageTo3D(const GpuMat& disp, GpuMat& xyzw, const Mat& Q, Stream& stream = Stream::Null());
CV_EXPORTS void reprojectImageTo3D(const GpuMat& disp, GpuMat& xyzw, const Mat& Q, int dst_cn = 4, Stream& stream = Stream::Null());
//! converts image from one color space to another
CV_EXPORTS void cvtColor(const GpuMat& src, GpuMat& dst, int code, int dcn = 0, Stream& stream = Stream::Null());

59
modules/gpu/src/cuda/imgproc.cu
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@ -316,62 +316,51 @@ namespace cv { namespace gpu { namespace device
__constant__ float cq[16];
template <typename T>
__global__ void reprojectImageTo3D(const T* disp, size_t disp_step, float* xyzw, size_t xyzw_step, int rows, int cols)
template <typename T, typename D>
__global__ void reprojectImageTo3D(const DevMem2D_<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 < rows && x < cols)
{
if (y >= disp.rows || x >= disp.cols)
return;
float qx = cq[1] * y + cq[3], qy = cq[5] * y + cq[7];
float qz = cq[9] * y + cq[11], qw = cq[13] * y + cq[15];
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];
qx += x * cq[0];
qy += x * cq[4];
qz += x * cq[8];
qw += x * cq[12];
const T d = disp(y, x);
T d = *(disp + disp_step * y + x);
const float iW = 1.f / (qw + cq[14] * d);
float iW = 1.f / (qw + cq[14] * d);
float4 v;
v.x = (qx + cq[2] * d) * iW;
v.y = (qy + cq[6] * d) * iW;
v.z = (qz + cq[10] * d) * iW;
v.w = 1.f;
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;
*(float4*)(xyzw + xyzw_step * y + (x * 4)) = v;
}
xyz(y, x) = v;
}
template <typename T>
inline void reprojectImageTo3D_caller(const DevMem2D_<T>& disp, const DevMem2Df& xyzw, const float* q, const cudaStream_t& stream)
template <typename T, typename D>
void reprojectImageTo3D_gpu(const DevMem2Db disp, DevMem2Db xyz, const float* q, cudaStream_t stream)
{
dim3 threads(32, 8, 1);
dim3 grid(1, 1, 1);
grid.x = divUp(disp.cols, threads.x);
grid.y = divUp(disp.rows, threads.y);
dim3 block(32, 8);
dim3 grid(divUp(disp.cols, block.x), divUp(disp.rows, block.y));
cudaSafeCall( cudaMemcpyToSymbol(cq, q, 16 * sizeof(float)) );
reprojectImageTo3D<<<grid, threads, 0, stream>>>(disp.data, disp.step / sizeof(T), xyzw.data, xyzw.step / sizeof(float), disp.rows, disp.cols);
reprojectImageTo3D<T, D><<<grid, block, 0, stream>>>((DevMem2D_<T>)disp, (DevMem2D_<D>)xyz);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
void reprojectImageTo3D_gpu(const DevMem2Db& disp, const DevMem2Df& xyzw, const float* q, const cudaStream_t& stream)
{
reprojectImageTo3D_caller(disp, xyzw, q, stream);
}
void reprojectImageTo3D_gpu(const DevMem2D_<short>& disp, const DevMem2Df& xyzw, const float* q, const cudaStream_t& stream)
{
reprojectImageTo3D_caller(disp, xyzw, q, stream);
}
template void reprojectImageTo3D_gpu<uchar, float3>(const DevMem2Db disp, DevMem2Db xyz, const float* q, cudaStream_t stream);
template void reprojectImageTo3D_gpu<uchar, float4>(const DevMem2Db disp, DevMem2Db xyz, const float* q, cudaStream_t stream);
template void reprojectImageTo3D_gpu<short, float3>(const DevMem2Db disp, DevMem2Db xyz, const float* q, cudaStream_t stream);
template void reprojectImageTo3D_gpu<short, float4>(const DevMem2Db disp, DevMem2Db xyz, const float* q, cudaStream_t stream);
/////////////////////////////////////////// Corner Harris /////////////////////////////////////////////////

40
modules/gpu/src/imgproc.cpp
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@ -50,7 +50,7 @@ using namespace cv::gpu;
void cv::gpu::meanShiftFiltering(const GpuMat&, GpuMat&, int, int, TermCriteria, Stream&) { throw_nogpu(); }
void cv::gpu::meanShiftProc(const GpuMat&, GpuMat&, GpuMat&, int, int, TermCriteria, Stream&) { throw_nogpu(); }
void cv::gpu::drawColorDisp(const GpuMat&, GpuMat&, int, Stream&) { throw_nogpu(); }
void cv::gpu::reprojectImageTo3D(const GpuMat&, GpuMat&, const Mat&, Stream&) { throw_nogpu(); }
void cv::gpu::reprojectImageTo3D(const GpuMat&, GpuMat&, const Mat&, int, Stream&) { throw_nogpu(); }
void cv::gpu::copyMakeBorder(const GpuMat&, GpuMat&, int, int, int, int, int, const Scalar&, Stream&) { throw_nogpu(); }
void cv::gpu::buildWarpPlaneMaps(Size, Rect, const Mat&, const Mat&, const Mat&, float, GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
void cv::gpu::buildWarpCylindricalMaps(Size, Rect, const Mat&, const Mat&, float, GpuMat&, GpuMat&, Stream&) { throw_nogpu(); }
@ -213,33 +213,29 @@ namespace cv { namespace gpu { namespace device
{
namespace imgproc
{
void reprojectImageTo3D_gpu(const DevMem2Db& disp, const DevMem2Df& xyzw, const float* q, const cudaStream_t& stream);
void reprojectImageTo3D_gpu(const DevMem2D_<short>& disp, const DevMem2Df& xyzw, const float* q, const cudaStream_t& stream);
template <typename T, typename D>
void reprojectImageTo3D_gpu(const DevMem2Db disp, DevMem2Db xyz, const float* q, cudaStream_t stream);
}
}}}
namespace
void cv::gpu::reprojectImageTo3D(const GpuMat& disp, GpuMat& xyz, const Mat& Q, int dst_cn, Stream& stream)
{
template <typename T>
void reprojectImageTo3D_caller(const GpuMat& disp, GpuMat& xyzw, const Mat& Q, const cudaStream_t& stream)
using namespace cv::gpu::device::imgproc;
typedef void (*func_t)(const DevMem2Db disp, DevMem2Db xyz, const float* q, cudaStream_t stream);
static const func_t funcs[2][4] =
{
using namespace ::cv::gpu::device::imgproc;
{reprojectImageTo3D_gpu<uchar, float3>, 0, 0, reprojectImageTo3D_gpu<short, float3>},
{reprojectImageTo3D_gpu<uchar, float4>, 0, 0, reprojectImageTo3D_gpu<short, float4>}
};
xyzw.create(disp.rows, disp.cols, CV_32FC4);
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);
reprojectImageTo3D_gpu((DevMem2D_<T>)disp, xyzw, Q.ptr<float>(), stream);
}
xyz.create(disp.size(), CV_MAKE_TYPE(CV_32F, dst_cn));
typedef void (*reprojectImageTo3D_caller_t)(const GpuMat& disp, GpuMat& xyzw, const Mat& Q, const cudaStream_t& stream);
const reprojectImageTo3D_caller_t reprojectImageTo3D_callers[] = {reprojectImageTo3D_caller<unsigned char>, 0, 0, reprojectImageTo3D_caller<short>, 0, 0, 0, 0};
}
void cv::gpu::reprojectImageTo3D(const GpuMat& disp, GpuMat& xyzw, const Mat& Q, Stream& stream)
{
CV_Assert((disp.type() == CV_8U || disp.type() == CV_16S) && Q.type() == CV_32F && Q.rows == 4 && Q.cols == 4);
reprojectImageTo3D_callers[disp.type()](disp, xyzw, Q, StreamAccessor::getStream(stream));
funcs[dst_cn == 4][disp.type()](disp, xyz, Q.ptr<float>(), StreamAccessor::getStream(stream));
}
////////////////////////////////////////////////////////////////////////
@ -1513,9 +1509,11 @@ void cv::gpu::Canny(const GpuMat& src, CannyBuf& buf, GpuMat& dst, double low_th
{
using namespace ::cv::gpu::device::canny;
CV_Assert(TargetArchs::builtWith(SHARED_ATOMICS) && DeviceInfo().supports(SHARED_ATOMICS));
CV_Assert(src.type() == CV_8UC1);
if (!TargetArchs::builtWith(SHARED_ATOMICS) || !DeviceInfo().supports(SHARED_ATOMICS))
CV_Error(CV_StsNotImplemented, "The device doesn't support shared atomics");
if( low_thresh > high_thresh )
std::swap( low_thresh, high_thresh);

41
modules/gpu/test/test_calib3d.cpp
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@ -301,4 +301,45 @@ 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());
}
};
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));
} // namespace

4
modules/gpu/test/test_color.cpp
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@ -41,6 +41,8 @@
#include "precomp.hpp"
namespace {
///////////////////////////////////////////////////////////////////////////////////////////////////////
// cvtColor
@ -1652,3 +1654,5 @@ INSTANTIATE_TEST_CASE_P(GPU_ImgProc, SwapChannels, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
WHOLE_SUBMAT));
} // namespace

52
modules/gpu/test/test_filters.cpp
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@ -41,15 +41,9 @@
#include "precomp.hpp"
struct KSize : cv::Size
{
KSize() {}
KSize(int width, int height) : cv::Size(width, height) {}
};
void PrintTo(KSize ksize, std::ostream* os)
{
*os << "kernel size " << ksize.width << "x" << ksize.height;
}
namespace {
IMPLEMENT_PARAM_CLASS(KSize, cv::Size)
cv::Mat getInnerROI(cv::InputArray m_, cv::Size ksize)
{
@ -107,7 +101,7 @@ INSTANTIATE_TEST_CASE_P(GPU_Filter, Blur, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC4)),
testing::Values(KSize(3, 3), KSize(5, 5), KSize(7, 7)),
testing::Values(KSize(cv::Size(3, 3)), KSize(cv::Size(5, 5)), KSize(cv::Size(7, 7))),
testing::Values(Anchor(cv::Point(-1, -1)), Anchor(cv::Point(0, 0)), Anchor(cv::Point(2, 2))),
WHOLE_SUBMAT));
@ -163,7 +157,7 @@ INSTANTIATE_TEST_CASE_P(GPU_Filter, Sobel, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC4)),
testing::Values(KSize(3, 3), KSize(5, 5), KSize(7, 7)),
testing::Values(KSize(cv::Size(3, 3)), KSize(cv::Size(5, 5)), KSize(cv::Size(7, 7))),
testing::Values(Deriv_X(0), Deriv_X(1), Deriv_X(2)),
testing::Values(Deriv_Y(0), Deriv_Y(1), Deriv_Y(2)),
testing::Values(BorderType(cv::BORDER_REFLECT101),
@ -286,21 +280,21 @@ INSTANTIATE_TEST_CASE_P(GPU_Filter, GaussianBlur, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC4)),
testing::Values(KSize(3, 3),
KSize(5, 5),
KSize(7, 7),
KSize(9, 9),
KSize(11, 11),
KSize(13, 13),
KSize(15, 15),
KSize(17, 17),
KSize(19, 19),
KSize(21, 21),
KSize(23, 23),
KSize(25, 25),
KSize(27, 27),
KSize(29, 29),
KSize(31, 31)),
testing::Values(KSize(cv::Size(3, 3)),
KSize(cv::Size(5, 5)),
KSize(cv::Size(7, 7)),
KSize(cv::Size(9, 9)),
KSize(cv::Size(11, 11)),
KSize(cv::Size(13, 13)),
KSize(cv::Size(15, 15)),
KSize(cv::Size(17, 17)),
KSize(cv::Size(19, 19)),
KSize(cv::Size(21, 21)),
KSize(cv::Size(23, 23)),
KSize(cv::Size(25, 25)),
KSize(cv::Size(27, 27)),
KSize(cv::Size(29, 29)),
KSize(cv::Size(31, 31))),
testing::Values(BorderType(cv::BORDER_REFLECT101),
BorderType(cv::BORDER_REPLICATE),
BorderType(cv::BORDER_CONSTANT),
@ -350,7 +344,7 @@ INSTANTIATE_TEST_CASE_P(GPU_Filter, Laplacian, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC4), MatType(CV_32FC1)),
testing::Values(KSize(1, 1), KSize(3, 3)),
testing::Values(KSize(cv::Size(1, 1)), KSize(cv::Size(3, 3))),
WHOLE_SUBMAT));
/////////////////////////////////////////////////////////////////////////////////////////////////
@ -557,6 +551,8 @@ INSTANTIATE_TEST_CASE_P(GPU_Filter, Filter2D, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC4), MatType(CV_32FC1)),
testing::Values(KSize(3, 3), KSize(5, 5), KSize(7, 7), KSize(11, 11), KSize(13, 13), KSize(15, 15)),
testing::Values(KSize(cv::Size(3, 3)), KSize(cv::Size(5, 5)), KSize(cv::Size(7, 7)), KSize(cv::Size(11, 11)), KSize(cv::Size(13, 13)), KSize(cv::Size(15, 15))),
testing::Values(Anchor(cv::Point(-1, -1)), Anchor(cv::Point(0, 0)), Anchor(cv::Point(2, 2))),
WHOLE_SUBMAT));
} // namespace

1358
modules/gpu/test/test_imgproc.cpp
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2
modules/gpu/test/utility.hpp
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@ -265,7 +265,7 @@ void PrintTo(const Inverse& useRoi, std::ostream* os);
}; \
inline void PrintTo( name param, std::ostream* os) \
{ \
*os << #name << "(" << static_cast< type >(param) << ")"; \
*os << #name << "(" << testing::PrintToString(static_cast< type >(param)) << ")"; \
}
IMPLEMENT_PARAM_CLASS(Channels, int)