generic-library/opencv
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

Merge pull request #520 from jet47:gpu-updates

Browse Source
This commit is contained in:
Andrey Kamaev 2013-02-21 18:03:06 +04:00 committed by OpenCV Buildbot
commit eda2a76ee9
15 changed files with 146 additions and 135 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

16
modules/core/src/gpumat.cpp
View File

@ -361,13 +361,13 @@ size_t cv::gpu::DeviceInfo::sharedMemPerBlock() const
return deviceProps.get(device_id_)->sharedMemPerBlock;
}
void cv::gpu::DeviceInfo::queryMemory(size_t& totalMemory, size_t& freeMemory) const
void cv::gpu::DeviceInfo::queryMemory(size_t& _totalMemory, size_t& _freeMemory) const
{
int prevDeviceID = getDevice();
if (prevDeviceID != device_id_)
setDevice(device_id_);
cudaSafeCall( cudaMemGetInfo(&freeMemory, &totalMemory) );
cudaSafeCall( cudaMemGetInfo(&_freeMemory, &_totalMemory) );
if (prevDeviceID != device_id_)
setDevice(prevDeviceID);
@ -375,16 +375,16 @@ void cv::gpu::DeviceInfo::queryMemory(size_t& totalMemory, size_t& freeMemory) c
size_t cv::gpu::DeviceInfo::freeMemory() const
{
size_t totalMemory, freeMemory;
queryMemory(totalMemory, freeMemory);
return freeMemory;
size_t _totalMemory, _freeMemory;
queryMemory(_totalMemory, _freeMemory);
return _freeMemory;
}
size_t cv::gpu::DeviceInfo::totalMemory() const
{
size_t totalMemory, freeMemory;
queryMemory(totalMemory, freeMemory);
return totalMemory;
size_t _totalMemory, _freeMemory;
queryMemory(_totalMemory, _freeMemory);
return _totalMemory;
}
bool cv::gpu::DeviceInfo::supports(FeatureSet feature_set) const

1
modules/gpu/doc/feature_detection_and_description.rst
View File

@ -640,4 +640,3 @@ Converts matrices obtained via :ocv:func:`gpu::BruteForceMatcher_GPU_base::radiu
.. ocv:function:: void gpu::BruteForceMatcher_GPU_base::radiusMatchConvert(const Mat& trainIdx, const Mat& imgIdx, const Mat& distance, const Mat& nMatches, std::vector< std::vector<DMatch> >& matches, bool compactResult = false)
If ``compactResult`` is ``true`` , the ``matches`` vector does not contain matches for fully masked-out query descriptors.

4
modules/gpu/doc/object_detection.rst
View File

@ -271,7 +271,9 @@ gpu::CascadeClassifier_GPU::detectMultiScale
------------------------------------------------
Detects objects of different sizes in the input image.
.. ocv:function:: int gpu::CascadeClassifier_GPU::detectMultiScale( const GpuMat& image, GpuMat& objectsBuf, double scaleFactor=1.1, int minNeighbors=4, Size minSize=Size() )
.. ocv:function:: int gpu::CascadeClassifier_GPU::detectMultiScale(const GpuMat& image, GpuMat& objectsBuf, double scaleFactor=1.2, int minNeighbors=4, Size minSize=Size())
.. ocv:function:: int gpu::CascadeClassifier_GPU::detectMultiScale(const GpuMat& image, GpuMat& objectsBuf, Size maxObjectSize, Size minSize = Size(), double scaleFactor = 1.1, int minNeighbors = 4)
:param image: Matrix of type ``CV_8U`` containing an image where objects should be detected.

94
modules/gpu/include/opencv2/gpu/gpu.hpp
View File

@ -804,31 +804,24 @@ private:
GpuMat lab, l, ab;
};
struct CV_EXPORTS CannyBuf
{
void create(const Size& image_size, int apperture_size = 3);
void release();
struct CV_EXPORTS CannyBuf;
GpuMat dx, dy;
GpuMat mag;
GpuMat map;
GpuMat st1, st2;
GpuMat unused;
Ptr<FilterEngine_GPU> filterDX, filterDY;
};
CV_EXPORTS void Canny(const GpuMat& image, GpuMat& edges, double low_thresh, double high_thresh, int apperture_size = 3, bool L2gradient = false);
CV_EXPORTS void Canny(const GpuMat& image, CannyBuf& buf, GpuMat& edges, double low_thresh, double high_thresh, int apperture_size = 3, bool L2gradient = false);
CV_EXPORTS void Canny(const GpuMat& dx, const GpuMat& dy, GpuMat& edges, double low_thresh, double high_thresh, bool L2gradient = false);
CV_EXPORTS void Canny(const GpuMat& dx, const GpuMat& dy, CannyBuf& buf, GpuMat& edges, double low_thresh, double high_thresh, bool L2gradient = false);
struct CV_EXPORTS CannyBuf
{
CannyBuf() {}
explicit CannyBuf(const Size& image_size, int apperture_size = 3) {create(image_size, apperture_size);}
CannyBuf(const GpuMat& dx_, const GpuMat& dy_);
void create(const Size& image_size, int apperture_size = 3);
void release();
GpuMat dx, dy;
GpuMat dx_buf, dy_buf;
GpuMat edgeBuf;
GpuMat trackBuf1, trackBuf2;
Ptr<FilterEngine_GPU> filterDX, filterDY;
};
class CV_EXPORTS ImagePyramid
{
public:
@ -1504,6 +1497,12 @@ public:
explicit BruteForceMatcher_GPU(Hamming /*d*/) : BruteForceMatcher_GPU_base(HammingDist) {}
};
class CV_EXPORTS BFMatcher_GPU : public BruteForceMatcher_GPU_base
{
public:
explicit BFMatcher_GPU(int norm = NORM_L2) : BruteForceMatcher_GPU_base(norm == NORM_L1 ? L1Dist : norm == NORM_L2 ? L2Dist : HammingDist) {}
};
////////////////////////////////// CascadeClassifier_GPU //////////////////////////////////////////
// The cascade classifier class for object detection: supports old haar and new lbp xlm formats and nvbin for haar cascades olny.
class CV_EXPORTS CascadeClassifier_GPU
@ -1518,7 +1517,8 @@ public:
void release();
/* returns number of detected objects */
int detectMultiScale(const GpuMat& image, GpuMat& objectsBuf, double scaleFactor = 1.1, int minNeighbors = 4, Size minSize = Size());
int detectMultiScale(const GpuMat& image, GpuMat& objectsBuf, double scaleFactor = 1.2, int minNeighbors = 4, Size minSize = Size());
int detectMultiScale(const GpuMat& image, GpuMat& objectsBuf, Size maxObjectSize, Size minSize = Size(), double scaleFactor = 1.1, int minNeighbors = 4);
bool findLargestObject;
bool visualizeInPlace;
@ -1526,7 +1526,6 @@ public:
Size getClassifierSize() const;
private:
struct CascadeClassifierImpl;
CascadeClassifierImpl* impl;
struct HaarCascade;
@ -1858,64 +1857,33 @@ inline GoodFeaturesToTrackDetector_GPU::GoodFeaturesToTrackDetector_GPU(int maxC
class CV_EXPORTS PyrLKOpticalFlow
{
public:
PyrLKOpticalFlow()
{
winSize = Size(21, 21);
maxLevel = 3;
iters = 30;
derivLambda = 0.5;
useInitialFlow = false;
minEigThreshold = 1e-4f;
getMinEigenVals = false;
isDeviceArch11_ = !DeviceInfo().supports(FEATURE_SET_COMPUTE_12);
}
PyrLKOpticalFlow();
void sparse(const GpuMat& prevImg, const GpuMat& nextImg, const GpuMat& prevPts, GpuMat& nextPts,
GpuMat& status, GpuMat* err = 0);
void dense(const GpuMat& prevImg, const GpuMat& nextImg, GpuMat& u, GpuMat& v, GpuMat* err = 0);
void releaseMemory();
Size winSize;
int maxLevel;
int iters;
double derivLambda;
double derivLambda; //unused
bool useInitialFlow;
float minEigThreshold;
bool getMinEigenVals;
void releaseMemory()
{
dx_calcBuf_.release();
dy_calcBuf_.release();
prevPyr_.clear();
nextPyr_.clear();
dx_buf_.release();
dy_buf_.release();
uPyr_.clear();
vPyr_.clear();
}
float minEigThreshold; //unused
bool getMinEigenVals; //unused
private:
void calcSharrDeriv(const GpuMat& src, GpuMat& dx, GpuMat& dy);
void buildImagePyramid(const GpuMat& img0, vector<GpuMat>& pyr, bool withBorder);
GpuMat dx_calcBuf_;
GpuMat dy_calcBuf_;
GpuMat uPyr_[2];
vector<GpuMat> prevPyr_;
vector<GpuMat> nextPyr_;
GpuMat vPyr_[2];
vector<GpuMat> unused1;
vector<GpuMat> unused2;
bool unused3;
GpuMat dx_buf_;
GpuMat dy_buf_;
vector<GpuMat> uPyr_;
vector<GpuMat> vPyr_;
bool isDeviceArch11_;
GpuMat buf_;
};

9
modules/gpu/perf/perf_features2d.cpp
View File

@ -161,8 +161,7 @@ PERF_TEST_P(DescSize_Norm, Features2D_BFMatch, Combine(Values(64, 128, 256), Val
if (PERF_RUN_GPU())
{
cv::gpu::BruteForceMatcher_GPU_base d_matcher(
cv::gpu::BruteForceMatcher_GPU_base::DistType((normType -2) / 2));
cv::gpu::BFMatcher_GPU d_matcher(normType);
cv::gpu::GpuMat d_query(query);
cv::gpu::GpuMat d_train(train);
@ -221,8 +220,7 @@ PERF_TEST_P(DescSize_K_Norm, Features2D_BFKnnMatch, Combine(
if (PERF_RUN_GPU())
{
cv::gpu::BruteForceMatcher_GPU_base d_matcher(
cv::gpu::BruteForceMatcher_GPU_base::DistType((normType -2) / 2));
cv::gpu::BFMatcher_GPU d_matcher(normType);
cv::gpu::GpuMat d_query(query);
cv::gpu::GpuMat d_train(train);
@ -275,8 +273,7 @@ PERF_TEST_P(DescSize_Norm, Features2D_BFRadiusMatch, Combine(Values(64, 128, 256
if (PERF_RUN_GPU())
{
cv::gpu::BruteForceMatcher_GPU_base d_matcher(
cv::gpu::BruteForceMatcher_GPU_base::DistType((normType -2) / 2));
cv::gpu::BFMatcher_GPU d_matcher(normType);
cv::gpu::GpuMat d_query(query);
cv::gpu::GpuMat d_train(train);

9
modules/gpu/src/cascadeclassifier.cpp
View File

@ -58,6 +58,7 @@ bool cv::gpu::CascadeClassifier_GPU::load(const string&) { throw_no
Size cv::gpu::CascadeClassifier_GPU::getClassifierSize() const { throw_nogpu(); return Size();}
void cv::gpu::CascadeClassifier_GPU::release() { throw_nogpu(); }
int cv::gpu::CascadeClassifier_GPU::detectMultiScale( const GpuMat&, GpuMat&, double, int, Size) {throw_nogpu(); return -1;}
int cv::gpu::CascadeClassifier_GPU::detectMultiScale( const GpuMat&, GpuMat&, Size, Size, double, int) {throw_nogpu(); return -1;}
#else
@ -682,6 +683,12 @@ int cv::gpu::CascadeClassifier_GPU::detectMultiScale( const GpuMat& image, GpuMa
return impl->process(image, objectsBuf, (float)scaleFactor, minNeighbors, findLargestObject, visualizeInPlace, minSize, cv::Size());
}
int cv::gpu::CascadeClassifier_GPU::detectMultiScale(const GpuMat& image, GpuMat& objectsBuf, Size maxObjectSize, Size minSize, double scaleFactor, int minNeighbors)
{
CV_Assert( !this->empty());
return impl->process(image, objectsBuf, (float)scaleFactor, minNeighbors, findLargestObject, visualizeInPlace, minSize, maxObjectSize);
}
bool cv::gpu::CascadeClassifier_GPU::load(const string& filename)
{
release();
@ -771,6 +778,8 @@ NCVStatus loadFromXML(const std::string &filename,
haar.bNeedsTiltedII = false;
Ncv32u curMaxTreeDepth;
std::vector<char> xmlFileCont;
std::vector<HaarClassifierNode128> h_TmpClassifierNotRootNodes;
haarStages.resize(0);
haarClassifierNodes.resize(0);

8
modules/gpu/src/hough.cpp
View File

@ -121,9 +121,7 @@ void cv::gpu::HoughLines(const GpuMat& src, GpuMat& lines, HoughLinesBuf& buf, f
buf.accum.setTo(Scalar::all(0));
DeviceInfo devInfo;
cudaDeviceProp prop;
cudaSafeCall(cudaGetDeviceProperties(&prop, devInfo.deviceID()));
linesAccum_gpu(srcPoints, pointsCount, buf.accum, rho, theta, prop.sharedMemPerBlock, devInfo.supports(FEATURE_SET_COMPUTE_20));
linesAccum_gpu(srcPoints, pointsCount, buf.accum, rho, theta, devInfo.sharedMemPerBlock(), devInfo.supports(FEATURE_SET_COMPUTE_20));
ensureSizeIsEnough(2, maxLines, CV_32FC2, lines);
@ -196,9 +194,7 @@ void cv::gpu::HoughLinesP(const GpuMat& src, GpuMat& lines, HoughLinesBuf& buf,
buf.accum.setTo(Scalar::all(0));
DeviceInfo devInfo;
cudaDeviceProp prop;
cudaSafeCall(cudaGetDeviceProperties(&prop, devInfo.deviceID()));
linesAccum_gpu(srcPoints, pointsCount, buf.accum, rho, theta, prop.sharedMemPerBlock, devInfo.supports(FEATURE_SET_COMPUTE_20));
linesAccum_gpu(srcPoints, pointsCount, buf.accum, rho, theta, devInfo.sharedMemPerBlock(), devInfo.supports(FEATURE_SET_COMPUTE_20));
ensureSizeIsEnough(1, maxLines, CV_32SC4, lines);

39
modules/gpu/src/imgproc.cpp
View File

@ -91,7 +91,6 @@ void cv::gpu::Canny(const GpuMat&, GpuMat&, double, double, int, bool) { throw_n
void cv::gpu::Canny(const GpuMat&, CannyBuf&, GpuMat&, double, double, int, bool) { throw_nogpu(); }
void cv::gpu::Canny(const GpuMat&, const GpuMat&, GpuMat&, double, double, bool) { throw_nogpu(); }
void cv::gpu::Canny(const GpuMat&, const GpuMat&, CannyBuf&, GpuMat&, double, double, bool) { throw_nogpu(); }
cv::gpu::CannyBuf::CannyBuf(const GpuMat&, const GpuMat&) { throw_nogpu(); }
void cv::gpu::CannyBuf::create(const Size&, int) { throw_nogpu(); }
void cv::gpu::CannyBuf::release() { throw_nogpu(); }
@ -1429,12 +1428,6 @@ void cv::gpu::convolve(const GpuMat& image, const GpuMat& templ, GpuMat& result,
//////////////////////////////////////////////////////////////////////////////
// Canny
cv::gpu::CannyBuf::CannyBuf(const GpuMat& dx_, const GpuMat& dy_)
{
(void) dx_;
(void) dy_;
}
void cv::gpu::CannyBuf::create(const Size& image_size, int apperture_size)
{
if (apperture_size > 0)
@ -1449,22 +1442,21 @@ void cv::gpu::CannyBuf::create(const Size& image_size, int apperture_size)
}
}
ensureSizeIsEnough(image_size, CV_32FC1, edgeBuf);
ensureSizeIsEnough(image_size, CV_32SC1, dx_buf);
ensureSizeIsEnough(image_size, CV_32FC1, mag);
ensureSizeIsEnough(image_size, CV_32SC1, map);
ensureSizeIsEnough(1, image_size.area(), CV_16UC2, trackBuf1);
ensureSizeIsEnough(1, image_size.area(), CV_16UC2, trackBuf2);
ensureSizeIsEnough(1, image_size.area(), CV_16UC2, st1);
ensureSizeIsEnough(1, image_size.area(), CV_16UC2, st2);
}
void cv::gpu::CannyBuf::release()
{
dx.release();
dy.release();
dx_buf.release();
dy_buf.release();
edgeBuf.release();
trackBuf1.release();
trackBuf2.release();
mag.release();
map.release();
st1.release();
st2.release();
}
namespace canny
@ -1487,13 +1479,14 @@ namespace
{
using namespace canny;
calcMap(dx, dy, buf.edgeBuf, buf.dx_buf, low_thresh, high_thresh);
buf.map.setTo(Scalar::all(0));
calcMap(dx, dy, buf.mag, buf.map, low_thresh, high_thresh);
edgesHysteresisLocal(buf.dx_buf, buf.trackBuf1.ptr<ushort2>());
edgesHysteresisLocal(buf.map, buf.st1.ptr<ushort2>());
edgesHysteresisGlobal(buf.dx_buf, buf.trackBuf1.ptr<ushort2>(), buf.trackBuf2.ptr<ushort2>());
edgesHysteresisGlobal(buf.map, buf.st1.ptr<ushort2>(), buf.st2.ptr<ushort2>());
getEdges(buf.dx_buf, dst);
getEdges(buf.map, dst);
}
}
@ -1525,14 +1518,14 @@ void cv::gpu::Canny(const GpuMat& src, CannyBuf& buf, GpuMat& dst, double low_th
src.locateROI(wholeSize, ofs);
GpuMat srcWhole(wholeSize, src.type(), src.datastart, src.step);
calcMagnitude(srcWhole, ofs.x, ofs.y, buf.dx, buf.dy, buf.edgeBuf, L2gradient);
calcMagnitude(srcWhole, ofs.x, ofs.y, buf.dx, buf.dy, buf.mag, L2gradient);
}
else
{
buf.filterDX->apply(src, buf.dx, Rect(0, 0, src.cols, src.rows));
buf.filterDY->apply(src, buf.dy, Rect(0, 0, src.cols, src.rows));
calcMagnitude(buf.dx, buf.dy, buf.edgeBuf, L2gradient);
calcMagnitude(buf.dx, buf.dy, buf.mag, L2gradient);
}
CannyCaller(buf.dx, buf.dy, buf, dst, static_cast<float>(low_thresh), static_cast<float>(high_thresh));
@ -1557,7 +1550,7 @@ void cv::gpu::Canny(const GpuMat& dx, const GpuMat& dy, CannyBuf& buf, GpuMat& d
dst.create(dx.size(), CV_8U);
buf.create(dx.size(), -1);
calcMagnitude(dx, dy, buf.edgeBuf, L2gradient);
calcMagnitude(dx, dy, buf.mag, L2gradient);
CannyCaller(dx, dy, buf, dst, static_cast<float>(low_thresh), static_cast<float>(high_thresh));
}

35
modules/gpu/src/pyrlk.cpp
View File

@ -48,8 +48,10 @@ using namespace cv::gpu;
#if !defined (HAVE_CUDA) || defined (CUDA_DISABLER)
cv::gpu::PyrLKOpticalFlow::PyrLKOpticalFlow() { throw_nogpu(); }
void cv::gpu::PyrLKOpticalFlow::sparse(const GpuMat&, const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, GpuMat*) { throw_nogpu(); }
void cv::gpu::PyrLKOpticalFlow::dense(const GpuMat&, const GpuMat&, GpuMat&, GpuMat&, GpuMat*) { throw_nogpu(); }
void cv::gpu::PyrLKOpticalFlow::releaseMemory() {}
#else /* !defined (HAVE_CUDA) */
@ -66,6 +68,14 @@ namespace pyrlk
PtrStepSzf err, int2 winSize, cudaStream_t stream = 0);
}
cv::gpu::PyrLKOpticalFlow::PyrLKOpticalFlow()
{
winSize = Size(21, 21);
maxLevel = 3;
iters = 30;
useInitialFlow = false;
}
namespace
{
void calcPatchSize(cv::Size winSize, dim3& block, dim3& patch)
@ -137,11 +147,11 @@ void cv::gpu::PyrLKOpticalFlow::sparse(const GpuMat& prevImg, const GpuMat& next
}
else
{
cvtColor(prevImg, dx_calcBuf_, COLOR_BGR2BGRA);
dx_calcBuf_.convertTo(prevPyr_[0], CV_32F);
cvtColor(prevImg, buf_, COLOR_BGR2BGRA);
buf_.convertTo(prevPyr_[0], CV_32F);
cvtColor(nextImg, dx_calcBuf_, COLOR_BGR2BGRA);
dx_calcBuf_.convertTo(nextPyr_[0], CV_32F);
cvtColor(nextImg, buf_, COLOR_BGR2BGRA);
buf_.convertTo(nextPyr_[0], CV_32F);
}
for (int level = 1; level <= maxLevel; ++level)
@ -193,9 +203,6 @@ void cv::gpu::PyrLKOpticalFlow::dense(const GpuMat& prevImg, const GpuMat& nextI
pyrDown(nextPyr_[level - 1], nextPyr_[level]);
}
uPyr_.resize(2);
vPyr_.resize(2);
ensureSizeIsEnough(prevImg.size(), CV_32FC1, uPyr_[0]);
ensureSizeIsEnough(prevImg.size(), CV_32FC1, vPyr_[0]);
ensureSizeIsEnough(prevImg.size(), CV_32FC1, uPyr_[1]);
@ -225,4 +232,18 @@ void cv::gpu::PyrLKOpticalFlow::dense(const GpuMat& prevImg, const GpuMat& nextI
vPyr_[idx].copyTo(v);
}
void cv::gpu::PyrLKOpticalFlow::releaseMemory()
{
prevPyr_.clear();
nextPyr_.clear();
buf_.release();
uPyr_[0].release();
vPyr_[0].release();
uPyr_[1].release();
vPyr_[1].release();
}
#endif /* !defined (HAVE_CUDA) */

24
modules/gpu/test/test_features2d.cpp
View File

@ -583,8 +583,7 @@ PARAM_TEST_CASE(BruteForceMatcher, cv::gpu::DeviceInfo, NormCode, DescriptorSize
GPU_TEST_P(BruteForceMatcher, Match_Single)
{
cv::gpu::BruteForceMatcher_GPU_base matcher(
cv::gpu::BruteForceMatcher_GPU_base::DistType((normCode -2) / 2));
cv::gpu::BFMatcher_GPU matcher(normCode);
cv::gpu::GpuMat mask;
if (useMask)
@ -611,8 +610,7 @@ GPU_TEST_P(BruteForceMatcher, Match_Single)
GPU_TEST_P(BruteForceMatcher, Match_Collection)
{
cv::gpu::BruteForceMatcher_GPU_base matcher(
cv::gpu::BruteForceMatcher_GPU_base::DistType((normCode -2) / 2));
cv::gpu::BFMatcher_GPU matcher(normCode);
cv::gpu::GpuMat d_train(train);
@ -666,8 +664,7 @@ GPU_TEST_P(BruteForceMatcher, Match_Collection)
GPU_TEST_P(BruteForceMatcher, KnnMatch_2_Single)
{
cv::gpu::BruteForceMatcher_GPU_base matcher(
cv::gpu::BruteForceMatcher_GPU_base::DistType((normCode -2) / 2));
cv::gpu::BFMatcher_GPU matcher(normCode);
const int knn = 2;
@ -706,8 +703,7 @@ GPU_TEST_P(BruteForceMatcher, KnnMatch_2_Single)
GPU_TEST_P(BruteForceMatcher, KnnMatch_3_Single)
{
cv::gpu::BruteForceMatcher_GPU_base matcher(
cv::gpu::BruteForceMatcher_GPU_base::DistType((normCode -2) / 2));
cv::gpu::BFMatcher_GPU matcher(normCode);
const int knn = 3;
@ -746,8 +742,7 @@ GPU_TEST_P(BruteForceMatcher, KnnMatch_3_Single)
GPU_TEST_P(BruteForceMatcher, KnnMatch_2_Collection)
{
cv::gpu::BruteForceMatcher_GPU_base matcher(
cv::gpu::BruteForceMatcher_GPU_base::DistType((normCode -2) / 2));
cv::gpu::BFMatcher_GPU matcher(normCode);
const int knn = 2;
@ -809,8 +804,7 @@ GPU_TEST_P(BruteForceMatcher, KnnMatch_2_Collection)
GPU_TEST_P(BruteForceMatcher, KnnMatch_3_Collection)
{
cv::gpu::BruteForceMatcher_GPU_base matcher(
cv::gpu::BruteForceMatcher_GPU_base::DistType((normCode -2) / 2));
cv::gpu::BFMatcher_GPU matcher(normCode);
const int knn = 3;
@ -872,8 +866,7 @@ GPU_TEST_P(BruteForceMatcher, KnnMatch_3_Collection)
GPU_TEST_P(BruteForceMatcher, RadiusMatch_Single)
{
cv::gpu::BruteForceMatcher_GPU_base matcher(
cv::gpu::BruteForceMatcher_GPU_base::DistType((normCode -2) / 2));
cv::gpu::BFMatcher_GPU matcher(normCode);
const float radius = 1.f / countFactor;
@ -922,8 +915,7 @@ GPU_TEST_P(BruteForceMatcher, RadiusMatch_Single)
GPU_TEST_P(BruteForceMatcher, RadiusMatch_Collection)
{
cv::gpu::BruteForceMatcher_GPU_base matcher(
cv::gpu::BruteForceMatcher_GPU_base::DistType((normCode -2) / 2));
cv::gpu::BFMatcher_GPU matcher(normCode);
const int n = 3;
const float radius = 1.f / countFactor * n;

34
modules/gpu/test/test_gpumat.cpp
View File

@ -322,4 +322,38 @@ INSTANTIATE_TEST_CASE_P(GPU_GpuMat, ConvertTo, testing::Combine(
ALL_DEPTH,
WHOLE_SUBMAT));
////////////////////////////////////////////////////////////////////////////////
// ensureSizeIsEnough
struct EnsureSizeIsEnough : testing::TestWithParam<cv::gpu::DeviceInfo>
{
virtual void SetUp()
{
cv::gpu::DeviceInfo devInfo = GetParam();
cv::gpu::setDevice(devInfo.deviceID());
}
};
GPU_TEST_P(EnsureSizeIsEnough, BufferReuse)
{
cv::gpu::GpuMat buffer(100, 100, CV_8U);
cv::gpu::GpuMat old = buffer;
// don't reallocate memory
cv::gpu::ensureSizeIsEnough(10, 20, CV_8U, buffer);
EXPECT_EQ(10, buffer.rows);
EXPECT_EQ(20, buffer.cols);
EXPECT_EQ(CV_8UC1, buffer.type());
EXPECT_EQ(reinterpret_cast<intptr_t>(old.data), reinterpret_cast<intptr_t>(buffer.data));
// don't reallocate memory
cv::gpu::ensureSizeIsEnough(20, 30, CV_8U, buffer);
EXPECT_EQ(20, buffer.rows);
EXPECT_EQ(30, buffer.cols);
EXPECT_EQ(CV_8UC1, buffer.type());
EXPECT_EQ(reinterpret_cast<intptr_t>(old.data), reinterpret_cast<intptr_t>(buffer.data));
}
INSTANTIATE_TEST_CASE_P(GPU_GpuMat, EnsureSizeIsEnough, ALL_DEVICES);
#endif // HAVE_CUDA

2
modules/stitching/src/matchers.cpp
View File

@ -219,7 +219,7 @@ void GpuMatcher::match(const ImageFeatures &features1, const ImageFeatures &feat
descriptors1_.upload(features1.descriptors);
descriptors2_.upload(features2.descriptors);
BruteForceMatcher_GPU_base matcher(BruteForceMatcher_GPU_base::L2Dist);
BFMatcher_GPU matcher(NORM_L2);
MatchesSet matches;
// Find 1->2 matches

0
samples/gpu/morfology.cpp → samples/gpu/morphology.cpp
View File

2
samples/gpu/performance/tests.cpp
View File

@ -364,7 +364,7 @@ TEST(BruteForceMatcher)
// Init GPU matcher
gpu::BruteForceMatcher_GPU_base d_matcher(gpu::BruteForceMatcher_GPU_base::L2Dist);
gpu::BFMatcher_GPU d_matcher(NORM_L2);
gpu::GpuMat d_query(query);
gpu::GpuMat d_train(train);

4
samples/gpu/surf_keypoint_matcher.cpp
View File

@ -57,7 +57,7 @@ int main(int argc, char* argv[])
cout << "FOUND " << keypoints2GPU.cols << " keypoints on second image" << endl;
// matching descriptors
gpu::BruteForceMatcher_GPU_base matcher(gpu::BruteForceMatcher_GPU_base::L2Dist);
BFMatcher_GPU matcher(NORM_L2);
GpuMat trainIdx, distance;
matcher.matchSingle(descriptors1GPU, descriptors2GPU, trainIdx, distance);
@ -69,7 +69,7 @@ int main(int argc, char* argv[])
surf.downloadKeypoints(keypoints2GPU, keypoints2);
surf.downloadDescriptors(descriptors1GPU, descriptors1);
surf.downloadDescriptors(descriptors2GPU, descriptors2);
BruteForceMatcher_GPU_base::matchDownload(trainIdx, distance, matches);
BFMatcher_GPU::matchDownload(trainIdx, distance, matches);
// drawing the results
Mat img_matches;