From 41bec1b11210fc835537171efceba064795236c8 Mon Sep 17 00:00:00 2001 From: Peter Andreas Entschev Date: Sat, 7 Dec 2013 22:12:13 -0200 Subject: [PATCH] OCL: including FAST feature detector. --- .../ocl/doc/feature_detection_and_description.rst | 147 +++ modules/ocl/include/opencv2/ocl.hpp | 59 + modules/ocl/perf/perf_fast.cpp | 93 ++ modules/ocl/perf/perf_precomp.hpp | 55 + modules/ocl/src/fast.cpp | 229 ++++ modules/ocl/src/opencl/featdetect_fast.cl | 1331 ++++++++++++++++++++ modules/ocl/test/test_fast.cpp | 93 ++ modules/ocl/test/utility.cpp | 66 + modules/ocl/test/utility.hpp | 3 + 9 files changed, 2076 insertions(+) create mode 100644 modules/ocl/perf/perf_fast.cpp create mode 100644 modules/ocl/src/fast.cpp create mode 100644 modules/ocl/src/opencl/featdetect_fast.cl create mode 100644 modules/ocl/test/test_fast.cpp diff --git a/modules/ocl/doc/feature_detection_and_description.rst b/modules/ocl/doc/feature_detection_and_description.rst index d052ef8..b93d32f 100644 --- a/modules/ocl/doc/feature_detection_and_description.rst +++ b/modules/ocl/doc/feature_detection_and_description.rst @@ -305,6 +305,153 @@ Converts matrices obtained via :ocv:func:`ocl::BruteForceMatcher_OCL_base::radiu If ``compactResult`` is ``true`` , the ``matches`` vector does not contain matches for fully masked-out query descriptors. + +ocl::FAST_OCL +------------------ +.. ocv:class:: ocl::FAST_OCL + +Class used for corner detection using the FAST algorithm. :: + + class CV_EXPORTS FAST_OCL + { + public: + enum + { + X_ROW = 0, + Y_ROW, + RESPONSE_ROW, + ROWS_COUNT + }; + + // all features have same size + static const int FEATURE_SIZE = 7; + + explicit FAST_OCL(int threshold, bool nonmaxSupression = true, double keypointsRatio = 0.05); + + //! finds the keypoints using FAST detector + //! supports only CV_8UC1 images + void operator ()(const oclMat& image, const oclMat& mask, oclMat& keypoints); + void operator ()(const oclMat& image, const oclMat& mask, std::vector& keypoints); + + //! download keypoints from device to host memory + static void downloadKeypoints(const oclMat& d_keypoints, std::vector& keypoints); + + //! convert keypoints to KeyPoint vector + static void convertKeypoints(const Mat& h_keypoints, std::vector& keypoints); + + //! release temporary buffer's memory + void release(); + + bool nonmaxSupression; + + int threshold; + + //! max keypoints = keypointsRatio * img.size().area() + double keypointsRatio; + + //! find keypoints and compute it's response if nonmaxSupression is true + //! return count of detected keypoints + int calcKeyPointsLocation(const oclMat& image, const oclMat& mask); + + //! get final array of keypoints + //! performs nonmax supression if needed + //! return final count of keypoints + int getKeyPoints(oclMat& keypoints); + + private: + // Hidden + }; + + +The class ``FAST_OCL`` implements FAST corner detection algorithm. + +.. seealso:: :ocv:func:`FAST` + + + +ocl::FAST_OCL::FAST_OCL +-------------------------- +Constructor. + +.. ocv:function:: ocl::FAST_OCL::FAST_OCL(int threshold, bool nonmaxSupression = true, double keypointsRatio = 0.05) + + :param threshold: Threshold on difference between intensity of the central pixel and pixels on a circle around this pixel. + + :param nonmaxSupression: If it is true, non-maximum suppression is applied to detected corners (keypoints). + + :param keypointsRatio: Inner buffer size for keypoints store is determined as (keypointsRatio * image_width * image_height). + + + +ocl::FAST_OCL::operator () +---------------------------- +Finds the keypoints using FAST detector. + +.. ocv:function:: void ocl::FAST_OCL::operator ()(const oclMat& image, const oclMat& mask, oclMat& keypoints) +.. ocv:function:: void ocl::FAST_OCL::operator ()(const oclMat& image, const oclMat& mask, std::vector& keypoints) + + :param image: Image where keypoints (corners) are detected. Only 8-bit grayscale images are supported. + + :param mask: Optional input mask that marks the regions where we should detect features. + + :param keypoints: The output vector of keypoints. Can be stored both in host or device memory. For device memory: + + * X_ROW of keypoints will contain the horizontal coordinate of the i'th point + * Y_ROW of keypoints will contain the vertical coordinate of the i'th point + * RESPONSE_ROW will contain response of i'th point (if non-maximum suppression is applied) + + + +ocl::FAST_OCL::downloadKeypoints +---------------------------------- +Download keypoints from device to host memory. + +.. ocv:function:: void ocl::FAST_OCL::downloadKeypoints(const oclMat& d_keypoints, std::vector& keypoints) + + + +ocl::FAST_OCL::convertKeypoints +--------------------------------- +Converts keypoints from OpenCL representation to vector of ``KeyPoint``. + +.. ocv:function:: void ocl::FAST_OCL::convertKeypoints(const Mat& h_keypoints, std::vector& keypoints) + + + +ocl::FAST_OCL::release +------------------------ +Releases inner buffer memory. + +.. ocv:function:: void ocl::FAST_OCL::release() + + + +ocl::FAST_OCL::calcKeyPointsLocation +-------------------------------------- +Find keypoints. If ``nonmaxSupression`` is true, responses are computed and eliminates keypoints with the smaller responses from 9-neighborhood regions. + +.. ocv:function:: int ocl::FAST_OCL::calcKeyPointsLocation(const oclMat& image, const oclMat& mask) + + :param image: Image where keypoints (corners) are detected. Only 8-bit grayscale images are supported. + + :param mask: Optional input mask that marks the regions where we should detect features. + +The function returns the amount of detected keypoints. + + + +ocl::FAST_OCL::getKeyPoints +----------------------------- +Gets final array of keypoints. + +.. ocv:function:: int ocl::FAST_OCL::getKeyPoints(oclMat& keypoints) + + :param keypoints: The output vector of keypoints. + +The function performs non-max suppression if needed and returns the final amount of keypoints. + + + ocl::HOGDescriptor ---------------------- diff --git a/modules/ocl/include/opencv2/ocl.hpp b/modules/ocl/include/opencv2/ocl.hpp index 19af00b..6626b20 100644 --- a/modules/ocl/include/opencv2/ocl.hpp +++ b/modules/ocl/include/opencv2/ocl.hpp @@ -1486,6 +1486,65 @@ namespace cv harrisK = harrisK_; } + ////////////////////////////////// FAST Feature Detector ////////////////////////////////// + class CV_EXPORTS FAST_OCL + { + public: + enum + { + X_ROW = 0, + Y_ROW, + RESPONSE_ROW, + ROWS_COUNT + }; + + // all features have same size + static const int FEATURE_SIZE = 7; + + explicit FAST_OCL(int threshold, bool nonmaxSupression = true, double keypointsRatio = 0.05); + + //! finds the keypoints using FAST detector + //! supports only CV_8UC1 images + void operator ()(const oclMat& image, const oclMat& mask, oclMat& keypoints); + void operator ()(const oclMat& image, const oclMat& mask, std::vector& keypoints); + + //! download keypoints from device to host memory + static void downloadKeypoints(const oclMat& d_keypoints, std::vector& keypoints); + + //! convert keypoints to KeyPoint vector + static void convertKeypoints(const Mat& h_keypoints, std::vector& keypoints); + + //! release temporary buffer's memory + void release(); + + bool nonmaxSupression; + + int threshold; + + //! max keypoints = keypointsRatio * img.size().area() + double keypointsRatio; + + //! find keypoints and compute it's response if nonmaxSupression is true + //! return count of detected keypoints + int calcKeyPointsLocation(const oclMat& image, const oclMat& mask); + + //! get final array of keypoints + //! performs nonmax supression if needed + //! return final count of keypoints + int getKeyPoints(oclMat& keypoints); + + private: + oclMat kpLoc_; + int count_; + + oclMat score_; + + oclMat d_keypoints_; + + int calcKeypointsOCL(const oclMat& img, const oclMat& mask, int maxKeypoints); + int nonmaxSupressionOCL(oclMat& keypoints); + }; + /////////////////////////////// PyrLKOpticalFlow ///////////////////////////////////// class CV_EXPORTS PyrLKOpticalFlow diff --git a/modules/ocl/perf/perf_fast.cpp b/modules/ocl/perf/perf_fast.cpp new file mode 100644 index 0000000..e5ac848 --- /dev/null +++ b/modules/ocl/perf/perf_fast.cpp @@ -0,0 +1,93 @@ +/*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) 2013, OpenCV Foundation, 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. +// +// Authors: +// * Peter Andreas Entschev, peter@entschev.com +// +//M*/ + +#include "perf_precomp.hpp" + +using namespace perf; + +///////////// FAST //////////////////////// + +typedef std::tr1::tuple Image_Threshold_NonmaxSupression_t; +typedef perf::TestBaseWithParam Image_Threshold_NonmaxSupression; + +PERF_TEST_P(Image_Threshold_NonmaxSupression, FAST, + testing::Combine(testing::Values("gpu/perf/aloe.png"), + testing::Values(20), + testing::Bool())) +{ + const Image_Threshold_NonmaxSupression_t params = GetParam(); + const std::string imgFile = std::tr1::get<0>(params); + const int threshold = std::tr1::get<1>(params); + const bool nonmaxSupression = std::tr1::get<2>(params); + + const cv::Mat img = imread(getDataPath(imgFile), cv::IMREAD_GRAYSCALE); + ASSERT_FALSE(img.empty()); + + if (RUN_OCL_IMPL) + { + cv::ocl::FAST_OCL fast(threshold, nonmaxSupression, 0.5); + + cv::ocl::oclMat d_img(img); + cv::ocl::oclMat d_keypoints; + + OCL_TEST_CYCLE() fast(d_img, cv::ocl::oclMat(), d_keypoints); + + std::vector ocl_keypoints; + fast.downloadKeypoints(d_keypoints, ocl_keypoints); + + sortKeyPoints(ocl_keypoints); + + SANITY_CHECK_KEYPOINTS(ocl_keypoints); + } + else if (RUN_PLAIN_IMPL) + { + std::vector cpu_keypoints; + + TEST_CYCLE() cv::FAST(img, cpu_keypoints, threshold, nonmaxSupression); + + SANITY_CHECK_KEYPOINTS(cpu_keypoints); + } + else + OCL_PERF_ELSE; +} diff --git a/modules/ocl/perf/perf_precomp.hpp b/modules/ocl/perf/perf_precomp.hpp index f7b6a76..01626d5 100644 --- a/modules/ocl/perf/perf_precomp.hpp +++ b/modules/ocl/perf/perf_precomp.hpp @@ -116,6 +116,7 @@ using namespace cv; #define OCL_TEST_CYCLE() for(; startTimer(), next(); cv::ocl::finish(), stopTimer()) #define OCL_TEST_CYCLE_MULTIRUN(runsNum) for(declare.runs(runsNum); startTimer(), next(); stopTimer()) for(int r = 0; r < runsNum; cv::ocl::finish(), ++r) +// TODO: Move to the ts module namespace cvtest { namespace ocl { inline void checkDeviceMaxMemoryAllocSize(const Size& size, int type, int factor = 1) @@ -133,6 +134,60 @@ inline void checkDeviceMaxMemoryAllocSize(const Size& size, int type, int factor throw perf::TestBase::PerfSkipTestException(); } } + +struct KeypointIdxCompare +{ + std::vector* keypoints; + + explicit KeypointIdxCompare(std::vector* _keypoints) : keypoints(_keypoints) {} + + bool operator ()(size_t i1, size_t i2) const + { + cv::KeyPoint kp1 = (*keypoints)[i1]; + cv::KeyPoint kp2 = (*keypoints)[i2]; + if (kp1.pt.x != kp2.pt.x) + return kp1.pt.x < kp2.pt.x; + if (kp1.pt.y != kp2.pt.y) + return kp1.pt.y < kp2.pt.y; + if (kp1.response != kp2.response) + return kp1.response < kp2.response; + return kp1.octave < kp2.octave; + } +}; + +inline void sortKeyPoints(std::vector& keypoints, cv::InputOutputArray _descriptors = cv::noArray()) +{ + std::vector indexies(keypoints.size()); + for (size_t i = 0; i < indexies.size(); ++i) + indexies[i] = i; + + std::sort(indexies.begin(), indexies.end(), KeypointIdxCompare(&keypoints)); + + std::vector new_keypoints; + cv::Mat new_descriptors; + + new_keypoints.resize(keypoints.size()); + + cv::Mat descriptors; + if (_descriptors.needed()) + { + descriptors = _descriptors.getMat(); + new_descriptors.create(descriptors.size(), descriptors.type()); + } + + for (size_t i = 0; i < indexies.size(); ++i) + { + size_t new_idx = indexies[i]; + new_keypoints[i] = keypoints[new_idx]; + if (!new_descriptors.empty()) + descriptors.row((int) new_idx).copyTo(new_descriptors.row((int) i)); + } + + keypoints.swap(new_keypoints); + if (_descriptors.needed()) + new_descriptors.copyTo(_descriptors); +} + } // namespace cvtest::ocl } // namespace cvtest diff --git a/modules/ocl/src/fast.cpp b/modules/ocl/src/fast.cpp new file mode 100644 index 0000000..b32ea28 --- /dev/null +++ b/modules/ocl/src/fast.cpp @@ -0,0 +1,229 @@ +/*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) 2013, OpenCV Foundation, 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. +// +// Authors: +// * Peter Andreas Entschev, peter@entschev.com +// +//M*/ + +#include "precomp.hpp" +#include "opencl_kernels.hpp" + +using namespace cv; +using namespace cv::ocl; + +cv::ocl::FAST_OCL::FAST_OCL(int _threshold, bool _nonmaxSupression, double _keypointsRatio) : + nonmaxSupression(_nonmaxSupression), threshold(_threshold), keypointsRatio(_keypointsRatio), count_(0) +{ +} + +void cv::ocl::FAST_OCL::operator ()(const oclMat& image, const oclMat& mask, std::vector& keypoints) +{ + if (image.empty()) + return; + + (*this)(image, mask, d_keypoints_); + downloadKeypoints(d_keypoints_, keypoints); +} + +void cv::ocl::FAST_OCL::downloadKeypoints(const oclMat& d_keypoints, std::vector& keypoints) +{ + if (d_keypoints.empty()) + return; + + Mat h_keypoints(d_keypoints); + convertKeypoints(h_keypoints, keypoints); +} + +void cv::ocl::FAST_OCL::convertKeypoints(const Mat& h_keypoints, std::vector& keypoints) +{ + if (h_keypoints.empty()) + return; + + CV_Assert(h_keypoints.rows == ROWS_COUNT && h_keypoints.elemSize() == 4); + + int npoints = h_keypoints.cols; + + keypoints.resize(npoints); + + const float* loc_x = h_keypoints.ptr(X_ROW); + const float* loc_y = h_keypoints.ptr(Y_ROW); + const float* response_row = h_keypoints.ptr(RESPONSE_ROW); + + for (int i = 0; i < npoints; ++i) + { + KeyPoint kp(loc_x[i], loc_y[i], static_cast(FEATURE_SIZE), -1, response_row[i]); + keypoints[i] = kp; + } +} + +void cv::ocl::FAST_OCL::operator ()(const oclMat& img, const oclMat& mask, oclMat& keypoints) +{ + calcKeyPointsLocation(img, mask); + keypoints.cols = getKeyPoints(keypoints); +} + +int cv::ocl::FAST_OCL::calcKeyPointsLocation(const oclMat& img, const oclMat& mask) +{ + CV_Assert(img.type() == CV_8UC1); + CV_Assert(mask.empty() || (mask.type() == CV_8UC1 && mask.size() == img.size())); + + int maxKeypoints = static_cast(keypointsRatio * img.size().area()); + + ensureSizeIsEnough(ROWS_COUNT, maxKeypoints, CV_32SC1, kpLoc_); + kpLoc_.setTo(Scalar::all(0)); + + if (nonmaxSupression) + { + ensureSizeIsEnough(img.size(), CV_32SC1, score_); + score_.setTo(Scalar::all(0)); + } + + count_ = calcKeypointsOCL(img, mask, maxKeypoints); + count_ = std::min(count_, maxKeypoints); + + return count_; +} + +int cv::ocl::FAST_OCL::calcKeypointsOCL(const oclMat& img, const oclMat& mask, int maxKeypoints) +{ + size_t localThreads[3] = {16, 16, 1}; + size_t globalThreads[3] = {divUp(img.cols - 6, localThreads[0]) * localThreads[0], + divUp(img.rows - 6, localThreads[1]) * localThreads[1], + 1}; + + Context *clCxt = Context::getContext(); + String kernelName = (mask.empty()) ? "calcKeypoints" : "calcKeypointsWithMask"; + std::vector< std::pair > args; + + int counter = 0; + int err = CL_SUCCESS; + cl_mem counterCL = clCreateBuffer(*(cl_context*)clCxt->getOpenCLContextPtr(), + CL_MEM_COPY_HOST_PTR, sizeof(int), + &counter, &err); + + int kpLocStep = kpLoc_.step / kpLoc_.elemSize(); + int scoreStep = score_.step / score_.elemSize(); + int nms = (nonmaxSupression) ? 1 : 0; + + args.push_back( std::make_pair( sizeof(cl_mem), (void *)&img.data)); + if (!mask.empty()) args.push_back( std::make_pair( sizeof(cl_mem), (void *)&mask.data)); + args.push_back( std::make_pair( sizeof(cl_mem), (void *)&kpLoc_.data)); + args.push_back( std::make_pair( sizeof(cl_mem), (void *)&score_.data)); + args.push_back( std::make_pair( sizeof(cl_mem), (void *)&counterCL)); + args.push_back( std::make_pair( sizeof(cl_int), (void *)&nms)); + args.push_back( std::make_pair( sizeof(cl_int), (void *)&maxKeypoints)); + args.push_back( std::make_pair( sizeof(cl_int), (void *)&threshold)); + args.push_back( std::make_pair( sizeof(cl_int), (void *)&img.step)); + args.push_back( std::make_pair( sizeof(cl_int), (void *)&img.rows)); + args.push_back( std::make_pair( sizeof(cl_int), (void *)&img.cols)); + if (!mask.empty()) args.push_back( std::make_pair( sizeof(cl_int), (void *)&mask.step)); + args.push_back( std::make_pair( sizeof(cl_int), (void *)&kpLocStep)); + args.push_back( std::make_pair( sizeof(cl_int), (void *)&scoreStep)); + + openCLExecuteKernel(clCxt, &featdetect_fast, kernelName, globalThreads, localThreads, args, -1, -1); + + openCLSafeCall(clEnqueueReadBuffer(*(cl_command_queue*)clCxt->getOpenCLCommandQueuePtr(), + counterCL, CL_TRUE, 0, sizeof(int), &counter, 0, NULL, NULL)); + openCLSafeCall(clReleaseMemObject(counterCL)); + + return counter; +} + +int cv::ocl::FAST_OCL::nonmaxSupressionOCL(oclMat& keypoints) +{ + size_t localThreads[3] = {256, 1, 1}; + size_t globalThreads[3] = {count_, 1, 1}; + + Context *clCxt = Context::getContext(); + String kernelName = "nonmaxSupression"; + std::vector< std::pair > args; + + int counter = 0; + int err = CL_SUCCESS; + cl_mem counterCL = clCreateBuffer(*(cl_context*)clCxt->getOpenCLContextPtr(), + CL_MEM_COPY_HOST_PTR, sizeof(int), + &counter, &err); + + int kpLocStep = kpLoc_.step / kpLoc_.elemSize(); + int sStep = score_.step / score_.elemSize(); + int kStep = keypoints.step / keypoints.elemSize(); + + args.push_back( std::make_pair( sizeof(cl_mem), (void *)&kpLoc_.data)); + args.push_back( std::make_pair( sizeof(cl_mem), (void *)&score_.data)); + args.push_back( std::make_pair( sizeof(cl_mem), (void *)&keypoints.data)); + args.push_back( std::make_pair( sizeof(cl_mem), (void *)&counterCL)); + args.push_back( std::make_pair( sizeof(cl_int), (void *)&count_)); + args.push_back( std::make_pair( sizeof(cl_int), (void *)&kpLocStep)); + args.push_back( std::make_pair( sizeof(cl_int), (void *)&sStep)); + args.push_back( std::make_pair( sizeof(cl_int), (void *)&kStep)); + + openCLExecuteKernel(clCxt, &featdetect_fast, kernelName, globalThreads, localThreads, args, -1, -1); + + openCLSafeCall(clEnqueueReadBuffer(*(cl_command_queue*)clCxt->getOpenCLCommandQueuePtr(), + counterCL, CL_TRUE, 0, sizeof(int), &counter, 0, NULL, NULL)); + openCLSafeCall(clReleaseMemObject(counterCL)); + + return counter; +} + +int cv::ocl::FAST_OCL::getKeyPoints(oclMat& keypoints) +{ + if (count_ == 0) + return 0; + + if (nonmaxSupression) + { + ensureSizeIsEnough(ROWS_COUNT, count_, CV_32FC1, keypoints); + return nonmaxSupressionOCL(keypoints); + } + + kpLoc_.convertTo(keypoints, CV_32FC1); + Mat k = keypoints; + + return count_; +} + +void cv::ocl::FAST_OCL::release() +{ + kpLoc_.release(); + score_.release(); + + d_keypoints_.release(); +} diff --git a/modules/ocl/src/opencl/featdetect_fast.cl b/modules/ocl/src/opencl/featdetect_fast.cl new file mode 100644 index 0000000..44d4f44 --- /dev/null +++ b/modules/ocl/src/opencl/featdetect_fast.cl @@ -0,0 +1,1331 @@ +/*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) 2013, OpenCV Foundation, 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. +// +// Authors: +// * Peter Andreas Entschev, peter@entschev.com +// +//M*/ + +#define X_ROW 0 +#define Y_ROW 1 +#define RESPONSE_ROW 2 +#define ROWS_COUNT 3 + + +__constant uchar c_table[] = { 0x80, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x00, 0xc0, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, + 0x00, 0x00, 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0x00, 0x80, 0x00, 0x80, 0x00, + 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, + 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, + 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, 0x80, 0x00, 0xc0, + 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, + 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, + 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, + 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, + 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, + 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, + 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, 0x80, + 0x80, 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, + 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, + 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, + 0x88, 0x88, 0x88, 0x88, 0x88, 0x88, 0xaa, 0xaa, 0xaa, + 0xaa, 0xaa, 0xaa, 0xaa, 0xaa, 0xaa, 0xaa, 0xaa, 0xaa, + 0xaa, 0xaa, 0xaa, 0xaa, 0xff, 0xff, 0xff, 0xff, 0xff, + 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, 0xff, + 0xff, 0xff }; + + +// 1 -> v > x + th +// 2 -> v < x - th +// 0 -> x - th <= v <= x + th +__inline int diffType(const int v, const int x, const int th) +{ + const int diff = x - v; + + return (int)(diff < -th) + ((int)(diff > th) << 1); +} + +// For OpenCL 1.1 compatibility +__inline int popCount(int x) { + x = x - ((x >> 1) & 0x55555555); + x = (x & 0x33333333) + ((x >> 2) & 0x33333333); + x = (x + (x >> 4)) & 0x0F0F0F0F; + x = x + (x >> 8); + x = x + (x >> 16); + + return x & 0x0000003F; +} + + +void calcMask( + const uint C[4], + const int v, + const int th, + int* mask1, + int* mask2) +{ + *mask1 = 0; + *mask2 = 0; + + int d1, d2; + + + + d1 = diffType(v, C[0] & 0xff, th); + d2 = diffType(v, C[2] & 0xff, th); + + if ((d1 | d2) == 0) + return; + + *mask1 |= (d1 & 1) << 0; + *mask2 |= ((d1 & 2) >> 1) << 0; + + *mask1 |= (d2 & 1) << 8; + *mask2 |= ((d2 & 2) >> 1) << 8; + + + + d1 = diffType(v, C[1] & 0xff, th); + d2 = diffType(v, C[3] & 0xff, th); + + if ((d1 | d2) == 0) + return; + + *mask1 |= (d1 & 1) << 4; + *mask2 |= ((d1 & 2) >> 1) << 4; + + *mask1 |= (d2 & 1) << 12; + *mask2 |= ((d2 & 2) >> 1) << 12; + + + + d1 = diffType(v, (C[0] >> (2 * 8)) & 0xff, th); + d2 = diffType(v, (C[2] >> (2 * 8)) & 0xff, th); + + if ((d1 | d2) == 0) + return; + + *mask1 |= (d1 & 1) << 2; + *mask2 |= ((d1 & 2) >> 1) << 2; + + *mask1 |= (d2 & 1) << 10; + *mask2 |= ((d2 & 2) >> 1) << 10; + + + + d1 = diffType(v, (C[1] >> (2 * 8)) & 0xff, th); + d2 = diffType(v, (C[3] >> (2 * 8)) & 0xff, th); + + if ((d1 | d2) == 0) + return; + + *mask1 |= (d1 & 1) << 6; + *mask2 |= ((d1 & 2) >> 1) << 6; + + *mask1 |= (d2 & 1) << 14; + *mask2 |= ((d2 & 2) >> 1) << 14; + + + + d1 = diffType(v, (C[0] >> (1 * 8)) & 0xff, th); + d2 = diffType(v, (C[2] >> (1 * 8)) & 0xff, th); + + /*if ((d1 | d2) == 0) + return;*/ + + *mask1 |= (d1 & 1) << 1; + *mask2 |= ((d1 & 2) >> 1) << 1; + + *mask1 |= (d2 & 1) << 9; + *mask2 |= ((d2 & 2) >> 1) << 9; + + + + d1 = diffType(v, (C[0] >> (3 * 8)) & 0xff, th); + d2 = diffType(v, (C[2] >> (3 * 8)) & 0xff, th); + + /*if ((d1 | d2) == 0) + return;*/ + + *mask1 |= (d1 & 1) << 3; + *mask2 |= ((d1 & 2) >> 1) << 3; + + *mask1 |= (d2 & 1) << 11; + *mask2 |= ((d2 & 2) >> 1) << 11; + + + + d1 = diffType(v, (C[1] >> (1 * 8)) & 0xff, th); + d2 = diffType(v, (C[3] >> (1 * 8)) & 0xff, th); + + /*if ((d1 | d2) == 0) + return;*/ + + *mask1 |= (d1 & 1) << 5; + *mask2 |= ((d1 & 2) >> 1) << 5; + + *mask1 |= (d2 & 1) << 13; + *mask2 |= ((d2 & 2) >> 1) << 13; + + + + d1 = diffType(v, (C[1] >> (3 * 8)) & 0xff, th); + d2 = diffType(v, (C[3] >> (3 * 8)) & 0xff, th); + + *mask1 |= (d1 & 1) << 7; + *mask2 |= ((d1 & 2) >> 1) << 7; + + *mask1 |= (d2 & 1) << 15; + *mask2 |= ((d2 & 2) >> 1) << 15; +} + +// 1 -> v > x + th +// 2 -> v < x - th +// 0 -> not a keypoint +__inline bool isKeyPoint(int mask1, int mask2) +{ + // TODO: Use OpenCL's popcount() function if OpenCL version >= 1.2 + return (popCount(mask1) > 8 && (c_table[(mask1 >> 3) - 63] & (1 << (mask1 & 7)))) || + (popCount(mask2) > 8 && (c_table[(mask2 >> 3) - 63] & (1 << (mask2 & 7)))); +} + +int cornerScore(const uint C[4], const int v, const int threshold) +{ + // binary search in [threshold + 1, 255] + + int min = threshold + 1; + int max = 255; + + while (min <= max) + { + const int mid = (min + max) >> 1; + + int mask1 = 0; + int mask2 = 0; + + calcMask(C, v, mid, &mask1, &mask2); + + int isKp = (int)isKeyPoint(mask1, mask2); + + min = isKp * (mid + 1) + (isKp ^ 1) * min; + max = (isKp ^ 1) * (mid - 1) + isKp * max; + } + + return min - 1; +} + +/////////////////////////////////////////////////////////////////////////// +// calcKeypoints + +__kernel +void calcKeypointsWithMask( + __global const uchar* img, + __global const uchar* mask, + __global int* kpLoc, + __global uint* score, + __global int* counter, + const int calcScore, + const unsigned int maxKeypoints, + const int threshold, + const int c_img_step, + const int c_img_rows, + const int c_img_cols, + const int c_mask_step, + const int c_kploc_step, + const int c_score_step) +{ + const int j = get_global_id(0) + 3; + const int i = get_global_id(1) + 3; + + if (i < c_img_rows - 3 && j < c_img_cols - 3 && mask[i * c_mask_step + j]) + { + int v; + uint C[4] = {0,0,0,0}; + + C[2] |= (uint)img[(i - 3) * c_img_step + j - 1] << 8; + C[2] |= (uint)img[(i - 3) * c_img_step + j]; + C[1] |= (uint)img[(i - 3) * c_img_step + j + 1] << (3 * 8); + + C[2] |= (uint)img[(i - 2) * c_img_step + j - 2] << (2 * 8); + C[1] |= (uint)img[(i - 2) * c_img_step + j + 2] << (2 * 8); + + C[2] |= (uint)img[(i - 1) * c_img_step + j - 3] << (3 * 8); + C[1] |= (uint)img[(i - 1) * c_img_step + j + 3] << 8; + + C[3] |= (uint)img[i * c_img_step + j - 3]; + v = (int) img[i * c_img_step + j]; + C[1] |= (uint)img[i * c_img_step + j + 3]; + + int d1 = diffType(v, C[1] & 0xff, threshold); + int d2 = diffType(v, C[3] & 0xff, threshold); + + if ((d1 | d2) == 0) + return; + + C[3] |= (uint)img[(i + 1) * c_img_step + j - 3] << 8; + C[0] |= (uint)img[(i + 1) * c_img_step + j + 3] << (3 * 8); + + C[3] |= (uint)img[(i + 2) * c_img_step + j - 2] << (2 * 8); + C[0] |= (uint)img[(i + 2) * c_img_step + j + 2] << (2 * 8); + + C[3] |= (uint)img[(i + 3) * c_img_step + j - 1] << (3 * 8); + C[0] |= (uint)img[(i + 3) * c_img_step + j]; + C[0] |= (uint)img[(i + 3) * c_img_step + j + 1] << 8; + + int mask1 = 0; + int mask2 = 0; + + calcMask(C, v, threshold, &mask1, &mask2); + + if (isKeyPoint(mask1, mask2)) + { + if (calcScore) score[i * c_score_step + j] = cornerScore(C, v, threshold); + + uint idx = atomic_inc(counter); + + if (idx < maxKeypoints) + { + kpLoc[X_ROW * c_kploc_step + idx] = j; + kpLoc[Y_ROW * c_kploc_step + idx] = i; + } + } + } +} + +__kernel +void calcKeypoints( + __global const uchar* img, + __global int* kpLoc, + __global uint* score, + __global int* counter, + const int calcScore, + const unsigned int maxKeypoints, + const int threshold, + const int c_img_step, + const int c_img_rows, + const int c_img_cols, + const int c_kploc_step, + const int c_score_step) +{ + const int j = get_global_id(0) + 3; + const int i = get_global_id(1) + 3; + + if (i < c_img_rows - 3 && j < c_img_cols - 3) + { + int v; + uint C[4] = {0,0,0,0}; + + C[2] |= (uint)img[(i - 3) * c_img_step + j - 1] << 8; + C[2] |= (uint)img[(i - 3) * c_img_step + j]; + C[1] |= (uint)img[(i - 3) * c_img_step + j + 1] << (3 * 8); + + C[2] |= (uint)img[(i - 2) * c_img_step + j - 2] << (2 * 8); + C[1] |= (uint)img[(i - 2) * c_img_step + j + 2] << (2 * 8); + + C[2] |= (uint)img[(i - 1) * c_img_step + j - 3] << (3 * 8); + C[1] |= (uint)img[(i - 1) * c_img_step + j + 3] << 8; + + C[3] |= (uint)img[i * c_img_step + j - 3]; + v = (int) img[i * c_img_step + j]; + C[1] |= (uint)img[i * c_img_step + j + 3]; + + int d1 = diffType(v, C[1] & 0xff, threshold); + int d2 = diffType(v, C[3] & 0xff, threshold); + + if ((d1 | d2) == 0) + return; + + C[3] |= (uint)img[(i + 1) * c_img_step + j - 3] << 8; + C[0] |= (uint)img[(i + 1) * c_img_step + j + 3] << (3 * 8); + + C[3] |= (uint)img[(i + 2) * c_img_step + j - 2] << (2 * 8); + C[0] |= (uint)img[(i + 2) * c_img_step + j + 2] << (2 * 8); + + C[3] |= (uint)img[(i + 3) * c_img_step + j - 1] << (3 * 8); + C[0] |= (uint)img[(i + 3) * c_img_step + j]; + C[0] |= (uint)img[(i + 3) * c_img_step + j + 1] << 8; + + int mask1 = 0; + int mask2 = 0; + + calcMask(C, v, threshold, &mask1, &mask2); + + if (isKeyPoint(mask1, mask2)) + { + if (calcScore) score[i * c_score_step + j] = cornerScore(C, v, threshold); + + uint idx = atomic_inc(counter); + + if (idx < maxKeypoints) + { + kpLoc[X_ROW * c_kploc_step + idx] = j; + kpLoc[Y_ROW * c_kploc_step + idx] = i; + } + } + } +} + +/////////////////////////////////////////////////////////////////////////// +// nonmaxSupression + +__kernel +void nonmaxSupression( + __global const int* kpLoc, + __global const uint* score, + __global float* keypoints, + __global int* new_counter, + const int counter, + const int c_kploc_step, + const int c_score_step, + const int c_keypoints_step) +{ + const int i = get_global_id(0); + + if (i < counter) + { + int loc_x = kpLoc[X_ROW * c_kploc_step + i]; + int loc_y = kpLoc[Y_ROW * c_kploc_step + i]; + + int s = score[loc_y * c_score_step + loc_x]; + + bool ismax = + s > score[(loc_y - 1) * c_score_step + loc_x - 1] && + s > score[(loc_y - 1) * c_score_step + loc_x ] && + s > score[(loc_y - 1) * c_score_step + loc_x + 1] && + + s > score[loc_y * c_score_step + loc_x - 1] && + s > score[loc_y * c_score_step + loc_x + 1] && + + s > score[(loc_y + 1) * c_score_step + loc_x - 1] && + s > score[(loc_y + 1) * c_score_step + loc_x ] && + s > score[(loc_y + 1) * c_score_step + loc_x + 1]; + + if (ismax) + { + uint idx = atomic_inc(new_counter); + + keypoints[X_ROW * c_keypoints_step + idx] = (float)loc_x; + keypoints[Y_ROW * c_keypoints_step + idx] = (float)loc_y; + keypoints[RESPONSE_ROW * c_keypoints_step + idx] = (float)s; + } + } +} diff --git a/modules/ocl/test/test_fast.cpp b/modules/ocl/test/test_fast.cpp new file mode 100644 index 0000000..19ff68e --- /dev/null +++ b/modules/ocl/test/test_fast.cpp @@ -0,0 +1,93 @@ +/*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) 2013, OpenCV Foundation, 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. +// +// Authors: +// * Peter Andreas Entschev, peter@entschev.com +// +//M*/ + +#include "test_precomp.hpp" + +#ifdef HAVE_OPENCL + +//////////////////////////////////////////////////////// +// FAST + +namespace +{ + IMPLEMENT_PARAM_CLASS(FAST_Threshold, int) + IMPLEMENT_PARAM_CLASS(FAST_NonmaxSupression, bool) +} + +PARAM_TEST_CASE(FAST, FAST_Threshold, FAST_NonmaxSupression) +{ + int threshold; + bool nonmaxSupression; + + virtual void SetUp() + { + threshold = GET_PARAM(0); + nonmaxSupression = GET_PARAM(1); + } +}; + +OCL_TEST_P(FAST, Accuracy) +{ + cv::Mat image = readImage("gpu/perf/aloe.png", cv::IMREAD_GRAYSCALE); + ASSERT_FALSE(image.empty()); + + cv::ocl::FAST_OCL fast(threshold); + fast.nonmaxSupression = nonmaxSupression; + + cv::ocl::oclMat ocl_image = cv::ocl::oclMat(image); + + std::vector keypoints; + fast(ocl_image, cv::ocl::oclMat(), keypoints); + + std::vector keypoints_gold; + cv::FAST(image, keypoints_gold, threshold, nonmaxSupression); + + ASSERT_KEYPOINTS_EQ(keypoints_gold, keypoints); +} + +INSTANTIATE_TEST_CASE_P(OCL_Features2D, FAST, testing::Combine( + testing::Values(FAST_Threshold(25), FAST_Threshold(50)), + testing::Values(FAST_NonmaxSupression(false), FAST_NonmaxSupression(true)))); + +#endif diff --git a/modules/ocl/test/utility.cpp b/modules/ocl/test/utility.cpp index 36fa75b..7d43b2a 100644 --- a/modules/ocl/test/utility.cpp +++ b/modules/ocl/test/utility.cpp @@ -259,4 +259,70 @@ void showDiff(const Mat& src, const Mat& gold, const Mat& actual, double eps, bo } } +namespace +{ + bool keyPointsEquals(const cv::KeyPoint& p1, const cv::KeyPoint& p2) + { + const double maxPtDif = 1.0; + const double maxSizeDif = 1.0; + const double maxAngleDif = 2.0; + const double maxResponseDif = 0.1; + + double dist = cv::norm(p1.pt - p2.pt); + + if (dist < maxPtDif && + fabs(p1.size - p2.size) < maxSizeDif && + abs(p1.angle - p2.angle) < maxAngleDif && + abs(p1.response - p2.response) < maxResponseDif && + p1.octave == p2.octave && + p1.class_id == p2.class_id) + { + return true; + } + + return false; + } + + struct KeyPointLess : std::binary_function + { + bool operator()(const cv::KeyPoint& kp1, const cv::KeyPoint& kp2) const + { + return kp1.pt.y < kp2.pt.y || (kp1.pt.y == kp2.pt.y && kp1.pt.x < kp2.pt.x); + } + }; +} + +testing::AssertionResult assertKeyPointsEquals(const char* gold_expr, const char* actual_expr, std::vector& gold, std::vector& actual) +{ + if (gold.size() != actual.size()) + { + return testing::AssertionFailure() << "KeyPoints size mistmach\n" + << "\"" << gold_expr << "\" : " << gold.size() << "\n" + << "\"" << actual_expr << "\" : " << actual.size(); + } + + std::sort(actual.begin(), actual.end(), KeyPointLess()); + std::sort(gold.begin(), gold.end(), KeyPointLess()); + + for (size_t i = 0; i < gold.size(); ++i) + { + const cv::KeyPoint& p1 = gold[i]; + const cv::KeyPoint& p2 = actual[i]; + + if (!keyPointsEquals(p1, p2)) + { + return testing::AssertionFailure() << "KeyPoints differ at " << i << "\n" + << "\"" << gold_expr << "\" vs \"" << actual_expr << "\" : \n" + << "pt : " << testing::PrintToString(p1.pt) << " vs " << testing::PrintToString(p2.pt) << "\n" + << "size : " << p1.size << " vs " << p2.size << "\n" + << "angle : " << p1.angle << " vs " << p2.angle << "\n" + << "response : " << p1.response << " vs " << p2.response << "\n" + << "octave : " << p1.octave << " vs " << p2.octave << "\n" + << "class_id : " << p1.class_id << " vs " << p2.class_id; + } + } + + return ::testing::AssertionSuccess(); +} + } // namespace cvtest diff --git a/modules/ocl/test/utility.hpp b/modules/ocl/test/utility.hpp index a3cac05..ab1a52b 100644 --- a/modules/ocl/test/utility.hpp +++ b/modules/ocl/test/utility.hpp @@ -54,6 +54,9 @@ extern int LOOP_TIMES; namespace cvtest { +testing::AssertionResult assertKeyPointsEquals(const char* gold_expr, const char* actual_expr, std::vector& gold, std::vector& actual); +#define ASSERT_KEYPOINTS_EQ(gold, actual) EXPECT_PRED_FORMAT2(assertKeyPointsEquals, gold, actual) + void showDiff(const Mat& src, const Mat& gold, const Mat& actual, double eps, bool alwaysShow = false); cv::ocl::oclMat createMat_ocl(cv::RNG& rng, Size size, int type, bool useRoi); -- 2.7.4