/*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 GpuMaterials 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 bpied warranties, including, but not limited to, the bpied // 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; using namespace std; #if !defined (HAVE_CUDA) cv::gpu::FAST_GPU::FAST_GPU(int, bool, double) { throw_nogpu(); } void cv::gpu::FAST_GPU::operator ()(const GpuMat&, const GpuMat&, GpuMat&) { throw_nogpu(); } void cv::gpu::FAST_GPU::operator ()(const GpuMat&, const GpuMat&, std::vector&) { throw_nogpu(); } void cv::gpu::FAST_GPU::downloadKeypoints(const GpuMat&, std::vector&) { throw_nogpu(); } void cv::gpu::FAST_GPU::convertKeypoints(const Mat&, std::vector&) { throw_nogpu(); } void cv::gpu::FAST_GPU::release() { throw_nogpu(); } int cv::gpu::FAST_GPU::calcKeyPointsLocation(const GpuMat&, const GpuMat&) { throw_nogpu(); return 0; } int cv::gpu::FAST_GPU::getKeyPoints(GpuMat&) { throw_nogpu(); return 0; } #else /* !defined (HAVE_CUDA) */ cv::gpu::FAST_GPU::FAST_GPU(int _threshold, bool _nonmaxSupression, double _keypointsRatio) : nonmaxSupression(_nonmaxSupression), threshold(_threshold), keypointsRatio(_keypointsRatio), count_(0) { } void cv::gpu::FAST_GPU::operator ()(const GpuMat& image, const GpuMat& mask, std::vector& keypoints) { if (image.empty()) return; (*this)(image, mask, d_keypoints_); downloadKeypoints(d_keypoints_, keypoints); } void cv::gpu::FAST_GPU::downloadKeypoints(const GpuMat& d_keypoints, std::vector& keypoints) { if (d_keypoints.empty()) return; Mat h_keypoints(d_keypoints); convertKeypoints(h_keypoints, keypoints); } void cv::gpu::FAST_GPU::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 short2* loc_row = h_keypoints.ptr(LOCATION_ROW); const float* response_row = h_keypoints.ptr(RESPONSE_ROW); for (int i = 0; i < npoints; ++i) { KeyPoint kp(loc_row[i].x, loc_row[i].y, static_cast(FEATURE_SIZE), -1, response_row[i]); keypoints[i] = kp; } } void cv::gpu::FAST_GPU::operator ()(const GpuMat& img, const GpuMat& mask, GpuMat& keypoints) { calcKeyPointsLocation(img, mask); keypoints.cols = getKeyPoints(keypoints); } namespace cv { namespace gpu { namespace device { namespace fast { int calcKeypoints_gpu(DevMem2Db img, DevMem2Db mask, short2* kpLoc, int maxKeypoints, DevMem2Di score, int threshold); int nonmaxSupression_gpu(const short2* kpLoc, int count, DevMem2Di score, short2* loc, float* response); } }}} int cv::gpu::FAST_GPU::calcKeyPointsLocation(const GpuMat& img, const GpuMat& mask) { using namespace cv::gpu::device::fast; CV_Assert(img.type() == CV_8UC1); CV_Assert(mask.empty() || (mask.type() == CV_8UC1 && mask.size() == img.size())); if (!TargetArchs::builtWith(GLOBAL_ATOMICS) || !DeviceInfo().supports(GLOBAL_ATOMICS)) CV_Error(CV_StsNotImplemented, "The device doesn't support global atomics"); int maxKeypoints = static_cast(keypointsRatio * img.size().area()); ensureSizeIsEnough(1, maxKeypoints, CV_16SC2, kpLoc_); if (nonmaxSupression) { ensureSizeIsEnough(img.size(), CV_32SC1, score_); score_.setTo(Scalar::all(0)); } count_ = calcKeypoints_gpu(img, mask, kpLoc_.ptr(), maxKeypoints, nonmaxSupression ? score_ : DevMem2Di(), threshold); count_ = std::min(count_, maxKeypoints); return count_; } int cv::gpu::FAST_GPU::getKeyPoints(GpuMat& keypoints) { using namespace cv::gpu::device::fast; if (!TargetArchs::builtWith(GLOBAL_ATOMICS) || !DeviceInfo().supports(GLOBAL_ATOMICS)) CV_Error(CV_StsNotImplemented, "The device doesn't support global atomics"); if (count_ == 0) return 0; ensureSizeIsEnough(ROWS_COUNT, count_, CV_32FC1, keypoints); if (nonmaxSupression) return nonmaxSupression_gpu(kpLoc_.ptr(), count_, score_, keypoints.ptr(LOCATION_ROW), keypoints.ptr(RESPONSE_ROW)); GpuMat locRow(1, count_, kpLoc_.type(), keypoints.ptr(0)); kpLoc_.colRange(0, count_).copyTo(locRow); keypoints.row(1).setTo(Scalar::all(0)); return count_; } void cv::gpu::FAST_GPU::release() { kpLoc_.release(); score_.release(); d_keypoints_.release(); } #endif /* !defined (HAVE_CUDA) */