Ilya Lavrenov
11 years ago
parent
2c35438771
commit
6ad4823f0c
18 changed files with 861 additions and 1474 deletions
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
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// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "perf_precomp.hpp" |
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#ifdef HAVE_OPENCV_OCL |
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#include "opencv2/ocl.hpp" |
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using namespace std; |
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using namespace testing; |
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using namespace perf; |
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using namespace cv; |
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using namespace cv::superres; |
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namespace |
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{ |
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class OneFrameSource_OCL : public FrameSource |
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{ |
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public: |
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explicit OneFrameSource_OCL(const ocl::oclMat& frame) : frame_(frame) {} |
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void nextFrame(OutputArray frame) |
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{ |
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ocl::getOclMatRef(frame) = frame_; |
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} |
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void reset() |
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{ |
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} |
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private: |
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ocl::oclMat frame_; |
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}; |
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class ZeroOpticalFlowOCL : public DenseOpticalFlowExt |
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{ |
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public: |
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void calc(InputArray frame0, InputArray, OutputArray flow1, OutputArray flow2) |
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{ |
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ocl::oclMat& frame0_ = ocl::getOclMatRef(frame0); |
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ocl::oclMat& flow1_ = ocl::getOclMatRef(flow1); |
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ocl::oclMat& flow2_ = ocl::getOclMatRef(flow2); |
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cv::Size size = frame0_.size(); |
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if(!flow2.needed()) |
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{ |
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flow1_.create(size, CV_32FC2); |
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flow1_.setTo(Scalar::all(0)); |
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} |
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else |
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{ |
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flow1_.create(size, CV_32FC1); |
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flow2_.create(size, CV_32FC1); |
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flow1_.setTo(Scalar::all(0)); |
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flow2_.setTo(Scalar::all(0)); |
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} |
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} |
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void collectGarbage() |
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{ |
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} |
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}; |
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} |
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PERF_TEST_P(Size_MatType, SuperResolution_BTVL1_OCL, |
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Combine(Values(szSmall64, szSmall128), |
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Values(MatType(CV_8UC1), MatType(CV_8UC3)))) |
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{ |
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declare.time(5 * 60); |
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const Size size = std::tr1::get<0>(GetParam()); |
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const int type = std::tr1::get<1>(GetParam()); |
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Mat frame(size, type); |
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declare.in(frame, WARMUP_RNG); |
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ocl::oclMat frame_ocl; |
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frame_ocl.upload(frame); |
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const int scale = 2; |
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const int iterations = 50; |
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const int temporalAreaRadius = 1; |
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Ptr<DenseOpticalFlowExt> opticalFlowOcl(new ZeroOpticalFlowOCL); |
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Ptr<SuperResolution> superRes_ocl = createSuperResolution_BTVL1_OCL(); |
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superRes_ocl->set("scale", scale); |
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superRes_ocl->set("iterations", iterations); |
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superRes_ocl->set("temporalAreaRadius", temporalAreaRadius); |
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superRes_ocl->set("opticalFlow", opticalFlowOcl); |
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superRes_ocl->setInput(makePtr<OneFrameSource_OCL>(frame_ocl)); |
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ocl::oclMat dst_ocl; |
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superRes_ocl->nextFrame(dst_ocl); |
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TEST_CYCLE_N(10) superRes_ocl->nextFrame(dst_ocl); |
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frame_ocl.release(); |
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CPU_SANITY_CHECK(dst_ocl); |
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} |
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#endif |
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@ -1,725 +0,0 @@ |
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
|
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// By downloading, copying, installing or using the software you agree to this license.
|
|
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// If you do not agree to this license, do not download, install,
|
|
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// copy or use the software.
|
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//
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//
|
|
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
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// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// @Authors
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// Jin Ma, jin@multicorewareinc.com
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
|
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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// S. Farsiu , D. Robinson, M. Elad, P. Milanfar. Fast and robust multiframe super resolution.
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// Dennis Mitzel, Thomas Pock, Thomas Schoenemann, Daniel Cremers. Video Super Resolution using Duality Based TV-L1 Optical Flow.
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#include "precomp.hpp" |
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#if !defined(HAVE_OPENCL) || !defined(HAVE_OPENCV_OCL) |
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cv::Ptr<cv::superres::SuperResolution> cv::superres::createSuperResolution_BTVL1_OCL() |
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{ |
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CV_Error(cv::Error::StsNotImplemented, "The called functionality is disabled for current build or platform"); |
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return Ptr<SuperResolution>(); |
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} |
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#else |
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#include "opencl_kernels.hpp" |
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using namespace std; |
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using namespace cv; |
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using namespace cv::ocl; |
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using namespace cv::superres; |
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using namespace cv::superres::detail; |
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static ProgramEntry superres_btvl1 = cv::ocl::superres::superres_btvl1; |
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namespace cv |
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{ |
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namespace ocl |
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{ |
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float* btvWeights_ = NULL; |
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size_t btvWeights_size = 0; |
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oclMat c_btvRegWeights; |
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} |
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} |
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namespace btv_l1_device_ocl |
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{ |
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void buildMotionMaps(const oclMat& forwardMotionX, const oclMat& forwardMotionY, |
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const oclMat& backwardMotionX, const oclMat& bacwardMotionY, |
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oclMat& forwardMapX, oclMat& forwardMapY, |
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oclMat& backwardMapX, oclMat& backwardMapY); |
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void upscale(const oclMat& src, oclMat& dst, int scale); |
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void diffSign(const oclMat& src1, const oclMat& src2, oclMat& dst); |
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void calcBtvRegularization(const oclMat& src, oclMat& dst, int ksize); |
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} |
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void btv_l1_device_ocl::buildMotionMaps(const oclMat& forwardMotionX, const oclMat& forwardMotionY, |
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const oclMat& backwardMotionX, const oclMat& backwardMotionY, |
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oclMat& forwardMapX, oclMat& forwardMapY, |
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oclMat& backwardMapX, oclMat& backwardMapY) |
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{ |
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Context* clCxt = Context::getContext(); |
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size_t local_thread[] = {32, 8, 1}; |
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size_t global_thread[] = {forwardMapX.cols, forwardMapX.rows, 1}; |
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int forwardMotionX_step = (int)(forwardMotionX.step/forwardMotionX.elemSize()); |
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int forwardMotionY_step = (int)(forwardMotionY.step/forwardMotionY.elemSize()); |
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int backwardMotionX_step = (int)(backwardMotionX.step/backwardMotionX.elemSize()); |
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int backwardMotionY_step = (int)(backwardMotionY.step/backwardMotionY.elemSize()); |
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int forwardMapX_step = (int)(forwardMapX.step/forwardMapX.elemSize()); |
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int forwardMapY_step = (int)(forwardMapY.step/forwardMapY.elemSize()); |
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int backwardMapX_step = (int)(backwardMapX.step/backwardMapX.elemSize()); |
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int backwardMapY_step = (int)(backwardMapY.step/backwardMapY.elemSize()); |
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String kernel_name = "buildMotionMapsKernel"; |
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vector< pair<size_t, const void*> > args; |
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args.push_back(make_pair(sizeof(cl_mem), (void*)&forwardMotionX.data)); |
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args.push_back(make_pair(sizeof(cl_mem), (void*)&forwardMotionY.data)); |
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args.push_back(make_pair(sizeof(cl_mem), (void*)&backwardMotionX.data)); |
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args.push_back(make_pair(sizeof(cl_mem), (void*)&backwardMotionY.data)); |
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args.push_back(make_pair(sizeof(cl_mem), (void*)&forwardMapX.data)); |
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args.push_back(make_pair(sizeof(cl_mem), (void*)&forwardMapY.data)); |
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args.push_back(make_pair(sizeof(cl_mem), (void*)&backwardMapX.data)); |
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args.push_back(make_pair(sizeof(cl_mem), (void*)&backwardMapY.data)); |
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args.push_back(make_pair(sizeof(cl_int), (void*)&forwardMotionX.rows)); |
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args.push_back(make_pair(sizeof(cl_int), (void*)&forwardMotionY.cols)); |
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args.push_back(make_pair(sizeof(cl_int), (void*)&forwardMotionX_step)); |
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args.push_back(make_pair(sizeof(cl_int), (void*)&forwardMotionY_step)); |
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args.push_back(make_pair(sizeof(cl_int), (void*)&backwardMotionX_step)); |
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args.push_back(make_pair(sizeof(cl_int), (void*)&backwardMotionY_step)); |
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args.push_back(make_pair(sizeof(cl_int), (void*)&forwardMapX_step)); |
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args.push_back(make_pair(sizeof(cl_int), (void*)&forwardMapY_step)); |
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args.push_back(make_pair(sizeof(cl_int), (void*)&backwardMapX_step)); |
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args.push_back(make_pair(sizeof(cl_int), (void*)&backwardMapY_step)); |
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openCLExecuteKernel(clCxt, &superres_btvl1, kernel_name, global_thread, local_thread, args, -1, -1); |
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} |
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void btv_l1_device_ocl::upscale(const oclMat& src, oclMat& dst, int scale) |
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{ |
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Context* clCxt = Context::getContext(); |
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size_t local_thread[] = {32, 8, 1}; |
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size_t global_thread[] = {src.cols, src.rows, 1}; |
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int src_step = (int)(src.step/src.elemSize()); |
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int dst_step = (int)(dst.step/dst.elemSize()); |
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String kernel_name = "upscaleKernel"; |
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vector< pair<size_t, const void*> > args; |
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int cn = src.oclchannels(); |
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args.push_back(make_pair(sizeof(cl_mem), (void*)&src.data)); |
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args.push_back(make_pair(sizeof(cl_mem), (void*)&dst.data)); |
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args.push_back(make_pair(sizeof(cl_int), (void*)&src_step)); |
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args.push_back(make_pair(sizeof(cl_int), (void*)&dst_step)); |
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args.push_back(make_pair(sizeof(cl_int), (void*)&src.rows)); |
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args.push_back(make_pair(sizeof(cl_int), (void*)&src.cols)); |
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args.push_back(make_pair(sizeof(cl_int), (void*)&scale)); |
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args.push_back(make_pair(sizeof(cl_int), (void*)&cn)); |
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openCLExecuteKernel(clCxt, &superres_btvl1, kernel_name, global_thread, local_thread, args, -1, -1); |
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} |
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void btv_l1_device_ocl::diffSign(const oclMat& src1, const oclMat& src2, oclMat& dst) |
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{ |
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Context* clCxt = Context::getContext(); |
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oclMat src1_ = src1.reshape(1); |
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oclMat src2_ = src2.reshape(1); |
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oclMat dst_ = dst.reshape(1); |
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int src1_step = (int)(src1_.step/src1_.elemSize()); |
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int src2_step = (int)(src2_.step/src2_.elemSize()); |
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int dst_step = (int)(dst_.step/dst_.elemSize()); |
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size_t local_thread[] = {32, 8, 1}; |
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size_t global_thread[] = {src1_.cols, src1_.rows, 1}; |
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String kernel_name = "diffSignKernel"; |
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vector< pair<size_t, const void*> > args; |
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args.push_back(make_pair(sizeof(cl_mem), (void*)&src1_.data)); |
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args.push_back(make_pair(sizeof(cl_mem), (void*)&src2_.data)); |
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args.push_back(make_pair(sizeof(cl_mem), (void*)&dst_.data)); |
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args.push_back(make_pair(sizeof(cl_int), (void*)&src1_.rows)); |
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args.push_back(make_pair(sizeof(cl_int), (void*)&src1_.cols)); |
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args.push_back(make_pair(sizeof(cl_int), (void*)&dst_step)); |
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args.push_back(make_pair(sizeof(cl_int), (void*)&src1_step)); |
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args.push_back(make_pair(sizeof(cl_int), (void*)&src2_step)); |
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openCLExecuteKernel(clCxt, &superres_btvl1, kernel_name, global_thread, local_thread, args, -1, -1); |
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} |
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void btv_l1_device_ocl::calcBtvRegularization(const oclMat& src, oclMat& dst, int ksize) |
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{ |
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Context* clCxt = Context::getContext(); |
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oclMat src_ = src.reshape(1); |
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oclMat dst_ = dst.reshape(1); |
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size_t local_thread[] = {32, 8, 1}; |
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size_t global_thread[] = {src.cols, src.rows, 1}; |
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int src_step = (int)(src_.step/src_.elemSize()); |
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int dst_step = (int)(dst_.step/dst_.elemSize()); |
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String kernel_name = "calcBtvRegularizationKernel"; |
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vector< pair<size_t, const void*> > args; |
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int cn = src.oclchannels(); |
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args.push_back(make_pair(sizeof(cl_mem), (void*)&src_.data)); |
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args.push_back(make_pair(sizeof(cl_mem), (void*)&dst_.data)); |
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args.push_back(make_pair(sizeof(cl_int), (void*)&src_step)); |
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args.push_back(make_pair(sizeof(cl_int), (void*)&dst_step)); |
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args.push_back(make_pair(sizeof(cl_int), (void*)&src.rows)); |
|
||||||
args.push_back(make_pair(sizeof(cl_int), (void*)&src.cols)); |
|
||||||
args.push_back(make_pair(sizeof(cl_int), (void*)&ksize)); |
|
||||||
args.push_back(make_pair(sizeof(cl_int), (void*)&cn)); |
|
||||||
args.push_back(make_pair(sizeof(cl_mem), (void*)&c_btvRegWeights.data)); |
|
||||||
|
|
||||||
openCLExecuteKernel(clCxt, &superres_btvl1, kernel_name, global_thread, local_thread, args, -1, -1); |
|
||||||
} |
|
||||||
|
|
||||||
namespace |
|
||||||
{ |
|
||||||
void calcRelativeMotions(const vector<pair<oclMat, oclMat> >& forwardMotions, const vector<pair<oclMat, oclMat> >& backwardMotions, |
|
||||||
vector<pair<oclMat, oclMat> >& relForwardMotions, vector<pair<oclMat, oclMat> >& relBackwardMotions, |
|
||||||
int baseIdx, Size size) |
|
||||||
{ |
|
||||||
const int count = static_cast<int>(forwardMotions.size()); |
|
||||||
|
|
||||||
relForwardMotions.resize(count); |
|
||||||
relForwardMotions[baseIdx].first.create(size, CV_32FC1); |
|
||||||
relForwardMotions[baseIdx].first.setTo(Scalar::all(0)); |
|
||||||
relForwardMotions[baseIdx].second.create(size, CV_32FC1); |
|
||||||
relForwardMotions[baseIdx].second.setTo(Scalar::all(0)); |
|
||||||
|
|
||||||
relBackwardMotions.resize(count); |
|
||||||
relBackwardMotions[baseIdx].first.create(size, CV_32FC1); |
|
||||||
relBackwardMotions[baseIdx].first.setTo(Scalar::all(0)); |
|
||||||
relBackwardMotions[baseIdx].second.create(size, CV_32FC1); |
|
||||||
relBackwardMotions[baseIdx].second.setTo(Scalar::all(0)); |
|
||||||
|
|
||||||
for (int i = baseIdx - 1; i >= 0; --i) |
|
||||||
{ |
|
||||||
ocl::add(relForwardMotions[i + 1].first, forwardMotions[i].first, relForwardMotions[i].first); |
|
||||||
ocl::add(relForwardMotions[i + 1].second, forwardMotions[i].second, relForwardMotions[i].second); |
|
||||||
|
|
||||||
ocl::add(relBackwardMotions[i + 1].first, backwardMotions[i + 1].first, relBackwardMotions[i].first); |
|
||||||
ocl::add(relBackwardMotions[i + 1].second, backwardMotions[i + 1].second, relBackwardMotions[i].second); |
|
||||||
} |
|
||||||
|
|
||||||
for (int i = baseIdx + 1; i < count; ++i) |
|
||||||
{ |
|
||||||
ocl::add(relForwardMotions[i - 1].first, backwardMotions[i].first, relForwardMotions[i].first); |
|
||||||
ocl::add(relForwardMotions[i - 1].second, backwardMotions[i].second, relForwardMotions[i].second); |
|
||||||
|
|
||||||
ocl::add(relBackwardMotions[i - 1].first, forwardMotions[i - 1].first, relBackwardMotions[i].first); |
|
||||||
ocl::add(relBackwardMotions[i - 1].second, forwardMotions[i - 1].second, relBackwardMotions[i].second); |
|
||||||
} |
|
||||||
} |
|
||||||
|
|
||||||
void upscaleMotions(const vector<pair<oclMat, oclMat> >& lowResMotions, vector<pair<oclMat, oclMat> >& highResMotions, int scale) |
|
||||||
{ |
|
||||||
highResMotions.resize(lowResMotions.size()); |
|
||||||
|
|
||||||
for (size_t i = 0; i < lowResMotions.size(); ++i) |
|
||||||
{ |
|
||||||
ocl::resize(lowResMotions[i].first, highResMotions[i].first, Size(), scale, scale, INTER_LINEAR); |
|
||||||
ocl::resize(lowResMotions[i].second, highResMotions[i].second, Size(), scale, scale, INTER_LINEAR); |
|
||||||
|
|
||||||
ocl::multiply(scale, highResMotions[i].first, highResMotions[i].first); |
|
||||||
ocl::multiply(scale, highResMotions[i].second, highResMotions[i].second); |
|
||||||
} |
|
||||||
} |
|
||||||
|
|
||||||
void buildMotionMaps(const pair<oclMat, oclMat>& forwardMotion, const pair<oclMat, oclMat>& backwardMotion, |
|
||||||
pair<oclMat, oclMat>& forwardMap, pair<oclMat, oclMat>& backwardMap) |
|
||||||
{ |
|
||||||
forwardMap.first.create(forwardMotion.first.size(), CV_32FC1); |
|
||||||
forwardMap.second.create(forwardMotion.first.size(), CV_32FC1); |
|
||||||
|
|
||||||
backwardMap.first.create(forwardMotion.first.size(), CV_32FC1); |
|
||||||
backwardMap.second.create(forwardMotion.first.size(), CV_32FC1); |
|
||||||
|
|
||||||
btv_l1_device_ocl::buildMotionMaps(forwardMotion.first, forwardMotion.second, |
|
||||||
backwardMotion.first, backwardMotion.second, |
|
||||||
forwardMap.first, forwardMap.second, |
|
||||||
backwardMap.first, backwardMap.second); |
|
||||||
} |
|
||||||
|
|
||||||
void upscale(const oclMat& src, oclMat& dst, int scale) |
|
||||||
{ |
|
||||||
CV_Assert( src.channels() == 1 || src.channels() == 3 || src.channels() == 4 ); |
|
||||||
|
|
||||||
btv_l1_device_ocl::upscale(src, dst, scale); |
|
||||||
} |
|
||||||
|
|
||||||
void diffSign(const oclMat& src1, const oclMat& src2, oclMat& dst) |
|
||||||
{ |
|
||||||
dst.create(src1.size(), src1.type()); |
|
||||||
|
|
||||||
btv_l1_device_ocl::diffSign(src1, src2, dst); |
|
||||||
} |
|
||||||
|
|
||||||
void calcBtvWeights(int btvKernelSize, double alpha, vector<float>& btvWeights) |
|
||||||
{ |
|
||||||
const size_t size = btvKernelSize * btvKernelSize; |
|
||||||
|
|
||||||
btvWeights.resize(size); |
|
||||||
|
|
||||||
const int ksize = (btvKernelSize - 1) / 2; |
|
||||||
const float alpha_f = static_cast<float>(alpha); |
|
||||||
|
|
||||||
for (int m = 0, ind = 0; m <= ksize; ++m) |
|
||||||
{ |
|
||||||
for (int l = ksize; l + m >= 0; --l, ++ind) |
|
||||||
btvWeights[ind] = pow(alpha_f, std::abs(m) + std::abs(l)); |
|
||||||
} |
|
||||||
|
|
||||||
btvWeights_ = &btvWeights[0]; |
|
||||||
btvWeights_size = size; |
|
||||||
Mat btvWeights_mheader(1, static_cast<int>(size), CV_32FC1, btvWeights_); |
|
||||||
c_btvRegWeights = btvWeights_mheader; |
|
||||||
} |
|
||||||
|
|
||||||
void calcBtvRegularization(const oclMat& src, oclMat& dst, int btvKernelSize) |
|
||||||
{ |
|
||||||
dst.create(src.size(), src.type()); |
|
||||||
|
|
||||||
const int ksize = (btvKernelSize - 1) / 2; |
|
||||||
|
|
||||||
btv_l1_device_ocl::calcBtvRegularization(src, dst, ksize); |
|
||||||
} |
|
||||||
|
|
||||||
class BTVL1_OCL_Base |
|
||||||
{ |
|
||||||
public: |
|
||||||
BTVL1_OCL_Base(); |
|
||||||
|
|
||||||
void process(const vector<oclMat>& src, oclMat& dst, |
|
||||||
const vector<pair<oclMat, oclMat> >& forwardMotions, const vector<pair<oclMat, oclMat> >& backwardMotions, |
|
||||||
int baseIdx); |
|
||||||
|
|
||||||
void collectGarbage(); |
|
||||||
|
|
||||||
protected: |
|
||||||
int scale_; |
|
||||||
int iterations_; |
|
||||||
double lambda_; |
|
||||||
double tau_; |
|
||||||
double alpha_; |
|
||||||
int btvKernelSize_; |
|
||||||
int blurKernelSize_; |
|
||||||
double blurSigma_; |
|
||||||
Ptr<DenseOpticalFlowExt> opticalFlow_; |
|
||||||
|
|
||||||
private: |
|
||||||
vector<Ptr<cv::ocl::FilterEngine_GPU> > filters_; |
|
||||||
int curBlurKernelSize_; |
|
||||||
double curBlurSigma_; |
|
||||||
int curSrcType_; |
|
||||||
|
|
||||||
vector<float> btvWeights_; |
|
||||||
int curBtvKernelSize_; |
|
||||||
double curAlpha_; |
|
||||||
|
|
||||||
vector<pair<oclMat, oclMat> > lowResForwardMotions_; |
|
||||||
vector<pair<oclMat, oclMat> > lowResBackwardMotions_; |
|
||||||
|
|
||||||
vector<pair<oclMat, oclMat> > highResForwardMotions_; |
|
||||||
vector<pair<oclMat, oclMat> > highResBackwardMotions_; |
|
||||||
|
|
||||||
vector<pair<oclMat, oclMat> > forwardMaps_; |
|
||||||
vector<pair<oclMat, oclMat> > backwardMaps_; |
|
||||||
|
|
||||||
oclMat highRes_; |
|
||||||
|
|
||||||
vector<oclMat> diffTerms_; |
|
||||||
oclMat a_, b_, c_, d_; |
|
||||||
oclMat regTerm_; |
|
||||||
}; |
|
||||||
|
|
||||||
BTVL1_OCL_Base::BTVL1_OCL_Base() |
|
||||||
{ |
|
||||||
scale_ = 4; |
|
||||||
iterations_ = 180; |
|
||||||
lambda_ = 0.03; |
|
||||||
tau_ = 1.3; |
|
||||||
alpha_ = 0.7; |
|
||||||
btvKernelSize_ = 7; |
|
||||||
blurKernelSize_ = 5; |
|
||||||
blurSigma_ = 0.0; |
|
||||||
opticalFlow_ = createOptFlow_Farneback_OCL(); |
|
||||||
|
|
||||||
curBlurKernelSize_ = -1; |
|
||||||
curBlurSigma_ = -1.0; |
|
||||||
curSrcType_ = -1; |
|
||||||
|
|
||||||
curBtvKernelSize_ = -1; |
|
||||||
curAlpha_ = -1.0; |
|
||||||
} |
|
||||||
|
|
||||||
void BTVL1_OCL_Base::process(const vector<oclMat>& src, oclMat& dst, |
|
||||||
const vector<pair<oclMat, oclMat> >& forwardMotions, const vector<pair<oclMat, oclMat> >& backwardMotions, |
|
||||||
int baseIdx) |
|
||||||
{ |
|
||||||
CV_Assert( scale_ > 1 ); |
|
||||||
CV_Assert( iterations_ > 0 ); |
|
||||||
CV_Assert( tau_ > 0.0 ); |
|
||||||
CV_Assert( alpha_ > 0.0 ); |
|
||||||
CV_Assert( btvKernelSize_ > 0 && btvKernelSize_ <= 16 ); |
|
||||||
CV_Assert( blurKernelSize_ > 0 ); |
|
||||||
CV_Assert( blurSigma_ >= 0.0 ); |
|
||||||
|
|
||||||
// update blur filter and btv weights
|
|
||||||
|
|
||||||
if (filters_.size() != src.size() || blurKernelSize_ != curBlurKernelSize_ || blurSigma_ != curBlurSigma_ || src[0].type() != curSrcType_) |
|
||||||
{ |
|
||||||
filters_.resize(src.size()); |
|
||||||
for (size_t i = 0; i < src.size(); ++i) |
|
||||||
filters_[i] = cv::ocl::createGaussianFilter_GPU(src[0].type(), Size(blurKernelSize_, blurKernelSize_), blurSigma_); |
|
||||||
curBlurKernelSize_ = blurKernelSize_; |
|
||||||
curBlurSigma_ = blurSigma_; |
|
||||||
curSrcType_ = src[0].type(); |
|
||||||
} |
|
||||||
|
|
||||||
if (btvWeights_.empty() || btvKernelSize_ != curBtvKernelSize_ || alpha_ != curAlpha_) |
|
||||||
{ |
|
||||||
calcBtvWeights(btvKernelSize_, alpha_, btvWeights_); |
|
||||||
curBtvKernelSize_ = btvKernelSize_; |
|
||||||
curAlpha_ = alpha_; |
|
||||||
} |
|
||||||
|
|
||||||
// calc motions between input frames
|
|
||||||
|
|
||||||
calcRelativeMotions(forwardMotions, backwardMotions, |
|
||||||
lowResForwardMotions_, lowResBackwardMotions_, |
|
||||||
baseIdx, src[0].size()); |
|
||||||
|
|
||||||
upscaleMotions(lowResForwardMotions_, highResForwardMotions_, scale_); |
|
||||||
upscaleMotions(lowResBackwardMotions_, highResBackwardMotions_, scale_); |
|
||||||
|
|
||||||
forwardMaps_.resize(highResForwardMotions_.size()); |
|
||||||
backwardMaps_.resize(highResForwardMotions_.size()); |
|
||||||
for (size_t i = 0; i < highResForwardMotions_.size(); ++i) |
|
||||||
{ |
|
||||||
buildMotionMaps(highResForwardMotions_[i], highResBackwardMotions_[i], forwardMaps_[i], backwardMaps_[i]); |
|
||||||
} |
|
||||||
// initial estimation
|
|
||||||
|
|
||||||
const Size lowResSize = src[0].size(); |
|
||||||
const Size highResSize(lowResSize.width * scale_, lowResSize.height * scale_); |
|
||||||
|
|
||||||
ocl::resize(src[baseIdx], highRes_, highResSize, 0, 0, INTER_LINEAR); |
|
||||||
|
|
||||||
// iterations
|
|
||||||
|
|
||||||
diffTerms_.resize(src.size()); |
|
||||||
bool d_inited = false; |
|
||||||
a_.create(highRes_.size(), highRes_.type()); |
|
||||||
b_.create(highRes_.size(), highRes_.type()); |
|
||||||
c_.create(lowResSize, highRes_.type()); |
|
||||||
d_.create(highRes_.rows, highRes_.cols, highRes_.type()); |
|
||||||
for (int i = 0; i < iterations_; ++i) |
|
||||||
{ |
|
||||||
if(!d_inited) |
|
||||||
{ |
|
||||||
d_.setTo(0); |
|
||||||
d_inited = true; |
|
||||||
} |
|
||||||
for (size_t k = 0; k < src.size(); ++k) |
|
||||||
{ |
|
||||||
diffTerms_[k].create(highRes_.size(), highRes_.type()); |
|
||||||
// a = M * Ih
|
|
||||||
ocl::remap(highRes_, a_, backwardMaps_[k].first, backwardMaps_[k].second, INTER_NEAREST, BORDER_CONSTANT, Scalar()); |
|
||||||
// b = HM * Ih
|
|
||||||
filters_[k]->apply(a_, b_, Rect(0,0,-1,-1)); |
|
||||||
// c = DHF * Ih
|
|
||||||
ocl::resize(b_, c_, lowResSize, 0, 0, INTER_NEAREST); |
|
||||||
|
|
||||||
diffSign(src[k], c_, c_); |
|
||||||
|
|
||||||
// a = Dt * diff
|
|
||||||
upscale(c_, d_, scale_); |
|
||||||
// b = HtDt * diff
|
|
||||||
filters_[k]->apply(d_, b_, Rect(0,0,-1,-1)); |
|
||||||
// diffTerm = MtHtDt * diff
|
|
||||||
ocl::remap(b_, diffTerms_[k], forwardMaps_[k].first, forwardMaps_[k].second, INTER_NEAREST, BORDER_CONSTANT, Scalar()); |
|
||||||
} |
|
||||||
|
|
||||||
if (lambda_ > 0) |
|
||||||
{ |
|
||||||
calcBtvRegularization(highRes_, regTerm_, btvKernelSize_); |
|
||||||
ocl::addWeighted(highRes_, 1.0, regTerm_, -tau_ * lambda_, 0.0, highRes_); |
|
||||||
} |
|
||||||
|
|
||||||
for (size_t k = 0; k < src.size(); ++k) |
|
||||||
{ |
|
||||||
ocl::addWeighted(highRes_, 1.0, diffTerms_[k], tau_, 0.0, highRes_); |
|
||||||
} |
|
||||||
} |
|
||||||
|
|
||||||
Rect inner(btvKernelSize_, btvKernelSize_, highRes_.cols - 2 * btvKernelSize_, highRes_.rows - 2 * btvKernelSize_); |
|
||||||
highRes_(inner).copyTo(dst); |
|
||||||
} |
|
||||||
|
|
||||||
void BTVL1_OCL_Base::collectGarbage() |
|
||||||
{ |
|
||||||
filters_.clear(); |
|
||||||
|
|
||||||
lowResForwardMotions_.clear(); |
|
||||||
lowResBackwardMotions_.clear(); |
|
||||||
|
|
||||||
highResForwardMotions_.clear(); |
|
||||||
highResBackwardMotions_.clear(); |
|
||||||
|
|
||||||
forwardMaps_.clear(); |
|
||||||
backwardMaps_.clear(); |
|
||||||
|
|
||||||
highRes_.release(); |
|
||||||
|
|
||||||
diffTerms_.clear(); |
|
||||||
a_.release(); |
|
||||||
b_.release(); |
|
||||||
c_.release(); |
|
||||||
regTerm_.release(); |
|
||||||
c_btvRegWeights.release(); |
|
||||||
} |
|
||||||
|
|
||||||
////////////////////////////////////////////////////////////
|
|
||||||
|
|
||||||
class BTVL1_OCL : public SuperResolution, private BTVL1_OCL_Base |
|
||||||
{ |
|
||||||
public: |
|
||||||
AlgorithmInfo* info() const; |
|
||||||
|
|
||||||
BTVL1_OCL(); |
|
||||||
|
|
||||||
void collectGarbage(); |
|
||||||
|
|
||||||
protected: |
|
||||||
void initImpl(Ptr<FrameSource>& frameSource); |
|
||||||
void processImpl(Ptr<FrameSource>& frameSource, OutputArray output); |
|
||||||
|
|
||||||
private: |
|
||||||
int temporalAreaRadius_; |
|
||||||
|
|
||||||
void readNextFrame(Ptr<FrameSource>& frameSource); |
|
||||||
void processFrame(int idx); |
|
||||||
|
|
||||||
oclMat curFrame_; |
|
||||||
oclMat prevFrame_; |
|
||||||
|
|
||||||
vector<oclMat> frames_; |
|
||||||
vector<pair<oclMat, oclMat> > forwardMotions_; |
|
||||||
vector<pair<oclMat, oclMat> > backwardMotions_; |
|
||||||
vector<oclMat> outputs_; |
|
||||||
|
|
||||||
int storePos_; |
|
||||||
int procPos_; |
|
||||||
int outPos_; |
|
||||||
|
|
||||||
vector<oclMat> srcFrames_; |
|
||||||
vector<pair<oclMat, oclMat> > srcForwardMotions_; |
|
||||||
vector<pair<oclMat, oclMat> > srcBackwardMotions_; |
|
||||||
oclMat finalOutput_; |
|
||||||
}; |
|
||||||
|
|
||||||
CV_INIT_ALGORITHM(BTVL1_OCL, "SuperResolution.BTVL1_OCL", |
|
||||||
obj.info()->addParam(obj, "scale", obj.scale_, false, 0, 0, "Scale factor."); |
|
||||||
obj.info()->addParam(obj, "iterations", obj.iterations_, false, 0, 0, "Iteration count."); |
|
||||||
obj.info()->addParam(obj, "tau", obj.tau_, false, 0, 0, "Asymptotic value of steepest descent method."); |
|
||||||
obj.info()->addParam(obj, "lambda", obj.lambda_, false, 0, 0, "Weight parameter to balance data term and smoothness term."); |
|
||||||
obj.info()->addParam(obj, "alpha", obj.alpha_, false, 0, 0, "Parameter of spacial distribution in Bilateral-TV."); |
|
||||||
obj.info()->addParam(obj, "btvKernelSize", obj.btvKernelSize_, false, 0, 0, "Kernel size of Bilateral-TV filter."); |
|
||||||
obj.info()->addParam(obj, "blurKernelSize", obj.blurKernelSize_, false, 0, 0, "Gaussian blur kernel size."); |
|
||||||
obj.info()->addParam(obj, "blurSigma", obj.blurSigma_, false, 0, 0, "Gaussian blur sigma."); |
|
||||||
obj.info()->addParam(obj, "temporalAreaRadius", obj.temporalAreaRadius_, false, 0, 0, "Radius of the temporal search area."); |
|
||||||
obj.info()->addParam<DenseOpticalFlowExt>(obj, "opticalFlow", obj.opticalFlow_, false, 0, 0, "Dense optical flow algorithm.")) |
|
||||||
|
|
||||||
BTVL1_OCL::BTVL1_OCL() |
|
||||||
{ |
|
||||||
temporalAreaRadius_ = 4; |
|
||||||
} |
|
||||||
|
|
||||||
void BTVL1_OCL::collectGarbage() |
|
||||||
{ |
|
||||||
curFrame_.release(); |
|
||||||
prevFrame_.release(); |
|
||||||
|
|
||||||
frames_.clear(); |
|
||||||
forwardMotions_.clear(); |
|
||||||
backwardMotions_.clear(); |
|
||||||
outputs_.clear(); |
|
||||||
|
|
||||||
srcFrames_.clear(); |
|
||||||
srcForwardMotions_.clear(); |
|
||||||
srcBackwardMotions_.clear(); |
|
||||||
finalOutput_.release(); |
|
||||||
|
|
||||||
SuperResolution::collectGarbage(); |
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BTVL1_OCL_Base::collectGarbage(); |
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} |
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|
|
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void BTVL1_OCL::initImpl(Ptr<FrameSource>& frameSource) |
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{ |
|
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const int cacheSize = 2 * temporalAreaRadius_ + 1; |
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|
|
||||||
frames_.resize(cacheSize); |
|
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forwardMotions_.resize(cacheSize); |
|
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backwardMotions_.resize(cacheSize); |
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outputs_.resize(cacheSize); |
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|
|
||||||
storePos_ = -1; |
|
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|
|
||||||
for (int t = -temporalAreaRadius_; t <= temporalAreaRadius_; ++t) |
|
||||||
readNextFrame(frameSource); |
|
||||||
|
|
||||||
for (int i = 0; i <= temporalAreaRadius_; ++i) |
|
||||||
processFrame(i); |
|
||||||
|
|
||||||
procPos_ = temporalAreaRadius_; |
|
||||||
outPos_ = -1; |
|
||||||
} |
|
||||||
|
|
||||||
void BTVL1_OCL::processImpl(Ptr<FrameSource>& frameSource, OutputArray _output) |
|
||||||
{ |
|
||||||
if (outPos_ >= storePos_) |
|
||||||
{ |
|
||||||
if(_output.kind() == _InputArray::OCL_MAT) |
|
||||||
{ |
|
||||||
getOclMatRef(_output).release(); |
|
||||||
} |
|
||||||
else |
|
||||||
{ |
|
||||||
_output.release(); |
|
||||||
} |
|
||||||
return; |
|
||||||
} |
|
||||||
|
|
||||||
readNextFrame(frameSource); |
|
||||||
|
|
||||||
if (procPos_ < storePos_) |
|
||||||
{ |
|
||||||
++procPos_; |
|
||||||
processFrame(procPos_); |
|
||||||
} |
|
||||||
|
|
||||||
++outPos_; |
|
||||||
const oclMat& curOutput = at(outPos_, outputs_); |
|
||||||
|
|
||||||
if (_output.kind() == _InputArray::OCL_MAT) |
|
||||||
curOutput.convertTo(getOclMatRef(_output), CV_8U); |
|
||||||
else |
|
||||||
{ |
|
||||||
curOutput.convertTo(finalOutput_, CV_8U); |
|
||||||
arrCopy(finalOutput_, _output); |
|
||||||
} |
|
||||||
} |
|
||||||
|
|
||||||
void BTVL1_OCL::readNextFrame(Ptr<FrameSource>& frameSource) |
|
||||||
{ |
|
||||||
curFrame_.release(); |
|
||||||
frameSource->nextFrame(curFrame_); |
|
||||||
|
|
||||||
if (curFrame_.empty()) |
|
||||||
return; |
|
||||||
|
|
||||||
++storePos_; |
|
||||||
curFrame_.convertTo(at(storePos_, frames_), CV_32F); |
|
||||||
|
|
||||||
if (storePos_ > 0) |
|
||||||
{ |
|
||||||
pair<oclMat, oclMat>& forwardMotion = at(storePos_ - 1, forwardMotions_); |
|
||||||
pair<oclMat, oclMat>& backwardMotion = at(storePos_, backwardMotions_); |
|
||||||
|
|
||||||
opticalFlow_->calc(prevFrame_, curFrame_, forwardMotion.first, forwardMotion.second); |
|
||||||
opticalFlow_->calc(curFrame_, prevFrame_, backwardMotion.first, backwardMotion.second); |
|
||||||
} |
|
||||||
|
|
||||||
curFrame_.copyTo(prevFrame_); |
|
||||||
} |
|
||||||
|
|
||||||
void BTVL1_OCL::processFrame(int idx) |
|
||||||
{ |
|
||||||
const int startIdx = max(idx - temporalAreaRadius_, 0); |
|
||||||
const int procIdx = idx; |
|
||||||
const int endIdx = min(startIdx + 2 * temporalAreaRadius_, storePos_); |
|
||||||
|
|
||||||
const int count = endIdx - startIdx + 1; |
|
||||||
|
|
||||||
srcFrames_.resize(count); |
|
||||||
srcForwardMotions_.resize(count); |
|
||||||
srcBackwardMotions_.resize(count); |
|
||||||
|
|
||||||
int baseIdx = -1; |
|
||||||
|
|
||||||
for (int i = startIdx, k = 0; i <= endIdx; ++i, ++k) |
|
||||||
{ |
|
||||||
if (i == procIdx) |
|
||||||
baseIdx = k; |
|
||||||
|
|
||||||
srcFrames_[k] = at(i, frames_); |
|
||||||
|
|
||||||
if (i < endIdx) |
|
||||||
srcForwardMotions_[k] = at(i, forwardMotions_); |
|
||||||
if (i > startIdx) |
|
||||||
srcBackwardMotions_[k] = at(i, backwardMotions_); |
|
||||||
} |
|
||||||
|
|
||||||
process(srcFrames_, at(idx, outputs_), srcForwardMotions_, srcBackwardMotions_, baseIdx); |
|
||||||
} |
|
||||||
} |
|
||||||
|
|
||||||
Ptr<SuperResolution> cv::superres::createSuperResolution_BTVL1_OCL() |
|
||||||
{ |
|
||||||
return makePtr<BTVL1_OCL>(); |
|
||||||
} |
|
||||||
#endif |
|
||||||
Loading…
Reference in new issue