138 lines
4.7 KiB
C++
138 lines
4.7 KiB
C++
/*
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* Copyright 1993-2010 NVIDIA Corporation. All rights reserved.
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*
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* NVIDIA Corporation and its licensors retain all intellectual
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* property and proprietary rights in and to this software and
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* related documentation and any modifications thereto.
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* Any use, reproduction, disclosure, or distribution of this
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* software and related documentation without an express license
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* agreement from NVIDIA Corporation is strictly prohibited.
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*/
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#if !defined CUDA_DISABLER
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#include "TestHypothesesGrow.h"
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#include "NCVHaarObjectDetection.hpp"
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TestHypothesesGrow::TestHypothesesGrow(std::string testName_, NCVTestSourceProvider<Ncv32u> &src_,
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Ncv32u rectWidth_, Ncv32u rectHeight_, Ncv32f rectScale_,
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Ncv32u maxLenSrc_, Ncv32u lenSrc_, Ncv32u maxLenDst_, Ncv32u lenDst_)
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:
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NCVTestProvider(testName_),
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src(src_),
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rectWidth(rectWidth_),
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rectHeight(rectHeight_),
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rectScale(rectScale_),
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maxLenSrc(maxLenSrc_),
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lenSrc(lenSrc_),
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maxLenDst(maxLenDst_),
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lenDst(lenDst_)
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{
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}
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bool TestHypothesesGrow::toString(std::ofstream &strOut)
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{
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strOut << "rectWidth=" << rectWidth << std::endl;
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strOut << "rectHeight=" << rectHeight << std::endl;
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strOut << "rectScale=" << rectScale << std::endl;
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strOut << "maxLenSrc=" << maxLenSrc << std::endl;
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strOut << "lenSrc=" << lenSrc << std::endl;
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strOut << "maxLenDst=" << maxLenDst << std::endl;
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strOut << "lenDst=" << lenDst << std::endl;
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return true;
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}
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bool TestHypothesesGrow::init()
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{
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return true;
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}
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bool TestHypothesesGrow::process()
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{
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NCVStatus ncvStat;
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bool rcode = false;
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NCVVectorAlloc<Ncv32u> h_vecSrc(*this->allocatorCPU.get(), this->maxLenSrc);
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ncvAssertReturn(h_vecSrc.isMemAllocated(), false);
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NCVVectorAlloc<Ncv32u> d_vecSrc(*this->allocatorGPU.get(), this->maxLenSrc);
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ncvAssertReturn(d_vecSrc.isMemAllocated(), false);
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NCVVectorAlloc<NcvRect32u> h_vecDst(*this->allocatorCPU.get(), this->maxLenDst);
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ncvAssertReturn(h_vecDst.isMemAllocated(), false);
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NCVVectorAlloc<NcvRect32u> d_vecDst(*this->allocatorGPU.get(), this->maxLenDst);
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ncvAssertReturn(d_vecDst.isMemAllocated(), false);
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NCVVectorAlloc<NcvRect32u> h_vecDst_d(*this->allocatorCPU.get(), this->maxLenDst);
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ncvAssertReturn(h_vecDst_d.isMemAllocated(), false);
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NCV_SET_SKIP_COND(this->allocatorGPU.get()->isCounting());
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NCV_SKIP_COND_BEGIN
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ncvAssertReturn(this->src.fill(h_vecSrc), false);
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memset(h_vecDst.ptr(), 0, h_vecDst.length() * sizeof(NcvRect32u));
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NCVVectorReuse<Ncv32u> h_vecDst_as32u(h_vecDst.getSegment(), lenDst * sizeof(NcvRect32u) / sizeof(Ncv32u));
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ncvAssertReturn(h_vecDst_as32u.isMemReused(), false);
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ncvAssertReturn(this->src.fill(h_vecDst_as32u), false);
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memcpy(h_vecDst_d.ptr(), h_vecDst.ptr(), h_vecDst.length() * sizeof(NcvRect32u));
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NCV_SKIP_COND_END
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ncvStat = h_vecSrc.copySolid(d_vecSrc, 0);
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ncvAssertReturn(ncvStat == NCV_SUCCESS, false);
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ncvStat = h_vecDst.copySolid(d_vecDst, 0);
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ncvAssertReturn(ncvStat == NCV_SUCCESS, false);
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ncvAssertCUDAReturn(cudaStreamSynchronize(0), false);
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Ncv32u h_outElemNum_d = 0;
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Ncv32u h_outElemNum_h = 0;
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NCV_SKIP_COND_BEGIN
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h_outElemNum_d = this->lenDst;
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ncvStat = ncvGrowDetectionsVector_device(d_vecSrc, this->lenSrc,
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d_vecDst, h_outElemNum_d, this->maxLenDst,
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this->rectWidth, this->rectHeight, this->rectScale, 0);
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ncvAssertReturn(ncvStat == NCV_SUCCESS, false);
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ncvStat = d_vecDst.copySolid(h_vecDst_d, 0);
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ncvAssertReturn(ncvStat == NCV_SUCCESS, false);
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ncvAssertCUDAReturn(cudaStreamSynchronize(0), false);
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h_outElemNum_h = this->lenDst;
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ncvStat = ncvGrowDetectionsVector_host(h_vecSrc, this->lenSrc,
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h_vecDst, h_outElemNum_h, this->maxLenDst,
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this->rectWidth, this->rectHeight, this->rectScale);
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ncvAssertReturn(ncvStat == NCV_SUCCESS, false);
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NCV_SKIP_COND_END
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//bit-to-bit check
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bool bLoopVirgin = true;
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NCV_SKIP_COND_BEGIN
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if (h_outElemNum_d != h_outElemNum_h)
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{
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bLoopVirgin = false;
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}
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else
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{
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if (memcmp(h_vecDst.ptr(), h_vecDst_d.ptr(), this->maxLenDst * sizeof(NcvRect32u)))
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{
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bLoopVirgin = false;
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}
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}
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NCV_SKIP_COND_END
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if (bLoopVirgin)
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{
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rcode = true;
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}
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return rcode;
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}
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bool TestHypothesesGrow::deinit()
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{
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return true;
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}
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#endif /* CUDA_DISABLER */ |