Open Source Computer Vision Library
https://opencv.org/
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249 lines
10 KiB
249 lines
10 KiB
/*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) 2000-2008, Intel Corporation, all rights reserved. |
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// Copyright (C) 2009, Willow Garage 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 "precomp.hpp" |
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#if !defined HAVE_CUDA || defined(CUDA_DISABLER) |
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void cv::gpu::pyrDown(const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); } |
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void cv::gpu::pyrUp(const GpuMat&, GpuMat&, Stream&) { throw_nogpu(); } |
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void cv::gpu::ImagePyramid::build(const GpuMat&, int, Stream&) { throw_nogpu(); } |
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void cv::gpu::ImagePyramid::getLayer(GpuMat&, Size, Stream&) const { throw_nogpu(); } |
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#else // HAVE_CUDA |
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////////////////////////////////////////////////////////////////////////////// |
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// pyrDown |
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namespace cv { namespace gpu { namespace device |
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{ |
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namespace imgproc |
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{ |
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template <typename T> void pyrDown_gpu(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream); |
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} |
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}}} |
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void cv::gpu::pyrDown(const GpuMat& src, GpuMat& dst, Stream& stream) |
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{ |
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using namespace cv::gpu::device::imgproc; |
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typedef void (*func_t)(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream); |
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static const func_t funcs[6][4] = |
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{ |
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{pyrDown_gpu<uchar> , 0 /*pyrDown_gpu<uchar2>*/ , pyrDown_gpu<uchar3> , pyrDown_gpu<uchar4> }, |
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{0 /*pyrDown_gpu<schar>*/, 0 /*pyrDown_gpu<schar2>*/ , 0 /*pyrDown_gpu<schar3>*/, 0 /*pyrDown_gpu<schar4>*/}, |
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{pyrDown_gpu<ushort> , 0 /*pyrDown_gpu<ushort2>*/, pyrDown_gpu<ushort3> , pyrDown_gpu<ushort4> }, |
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{pyrDown_gpu<short> , 0 /*pyrDown_gpu<short2>*/ , pyrDown_gpu<short3> , pyrDown_gpu<short4> }, |
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{0 /*pyrDown_gpu<int>*/ , 0 /*pyrDown_gpu<int2>*/ , 0 /*pyrDown_gpu<int3>*/ , 0 /*pyrDown_gpu<int4>*/ }, |
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{pyrDown_gpu<float> , 0 /*pyrDown_gpu<float2>*/ , pyrDown_gpu<float3> , pyrDown_gpu<float4> } |
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}; |
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CV_Assert(src.depth() <= CV_32F && src.channels() <= 4); |
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const func_t func = funcs[src.depth()][src.channels() - 1]; |
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CV_Assert(func != 0); |
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dst.create((src.rows + 1) / 2, (src.cols + 1) / 2, src.type()); |
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func(src, dst, StreamAccessor::getStream(stream)); |
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} |
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////////////////////////////////////////////////////////////////////////////// |
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// pyrUp |
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namespace cv { namespace gpu { namespace device |
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{ |
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namespace imgproc |
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{ |
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template <typename T> void pyrUp_gpu(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream); |
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} |
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}}} |
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void cv::gpu::pyrUp(const GpuMat& src, GpuMat& dst, Stream& stream) |
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{ |
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using namespace cv::gpu::device::imgproc; |
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typedef void (*func_t)(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream); |
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static const func_t funcs[6][4] = |
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{ |
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{pyrUp_gpu<uchar> , 0 /*pyrUp_gpu<uchar2>*/ , pyrUp_gpu<uchar3> , pyrUp_gpu<uchar4> }, |
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{0 /*pyrUp_gpu<schar>*/, 0 /*pyrUp_gpu<schar2>*/ , 0 /*pyrUp_gpu<schar3>*/, 0 /*pyrUp_gpu<schar4>*/}, |
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{pyrUp_gpu<ushort> , 0 /*pyrUp_gpu<ushort2>*/, pyrUp_gpu<ushort3> , pyrUp_gpu<ushort4> }, |
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{pyrUp_gpu<short> , 0 /*pyrUp_gpu<short2>*/ , pyrUp_gpu<short3> , pyrUp_gpu<short4> }, |
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{0 /*pyrUp_gpu<int>*/ , 0 /*pyrUp_gpu<int2>*/ , 0 /*pyrUp_gpu<int3>*/ , 0 /*pyrUp_gpu<int4>*/ }, |
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{pyrUp_gpu<float> , 0 /*pyrUp_gpu<float2>*/ , pyrUp_gpu<float3> , pyrUp_gpu<float4> } |
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}; |
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CV_Assert(src.depth() <= CV_32F && src.channels() <= 4); |
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const func_t func = funcs[src.depth()][src.channels() - 1]; |
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CV_Assert(func != 0); |
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dst.create(src.rows * 2, src.cols * 2, src.type()); |
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func(src, dst, StreamAccessor::getStream(stream)); |
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} |
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////////////////////////////////////////////////////////////////////////////// |
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// ImagePyramid |
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namespace cv { namespace gpu { namespace device |
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{ |
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namespace pyramid |
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{ |
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template <typename T> void kernelDownsampleX2_gpu(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream); |
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template <typename T> void kernelInterpolateFrom1_gpu(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream); |
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} |
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}}} |
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void cv::gpu::ImagePyramid::build(const GpuMat& img, int numLayers, Stream& stream) |
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{ |
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using namespace cv::gpu::device::pyramid; |
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typedef void (*func_t)(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream); |
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static const func_t funcs[6][4] = |
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{ |
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{kernelDownsampleX2_gpu<uchar1> , 0 /*kernelDownsampleX2_gpu<uchar2>*/ , kernelDownsampleX2_gpu<uchar3> , kernelDownsampleX2_gpu<uchar4> }, |
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{0 /*kernelDownsampleX2_gpu<char1>*/ , 0 /*kernelDownsampleX2_gpu<char2>*/ , 0 /*kernelDownsampleX2_gpu<char3>*/ , 0 /*kernelDownsampleX2_gpu<char4>*/ }, |
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{kernelDownsampleX2_gpu<ushort1> , 0 /*kernelDownsampleX2_gpu<ushort2>*/, kernelDownsampleX2_gpu<ushort3> , kernelDownsampleX2_gpu<ushort4> }, |
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{0 /*kernelDownsampleX2_gpu<short1>*/ , 0 /*kernelDownsampleX2_gpu<short2>*/ , 0 /*kernelDownsampleX2_gpu<short3>*/, 0 /*kernelDownsampleX2_gpu<short4>*/}, |
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{0 /*kernelDownsampleX2_gpu<int1>*/ , 0 /*kernelDownsampleX2_gpu<int2>*/ , 0 /*kernelDownsampleX2_gpu<int3>*/ , 0 /*kernelDownsampleX2_gpu<int4>*/ }, |
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{kernelDownsampleX2_gpu<float1> , 0 /*kernelDownsampleX2_gpu<float2>*/ , kernelDownsampleX2_gpu<float3> , kernelDownsampleX2_gpu<float4> } |
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}; |
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CV_Assert(img.depth() <= CV_32F && img.channels() <= 4); |
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const func_t func = funcs[img.depth()][img.channels() - 1]; |
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CV_Assert(func != 0); |
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layer0_ = img; |
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Size szLastLayer = img.size(); |
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nLayers_ = 1; |
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if (numLayers <= 0) |
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numLayers = 255; //it will cut-off when any of the dimensions goes 1 |
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pyramid_.resize(numLayers); |
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for (int i = 0; i < numLayers - 1; ++i) |
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{ |
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Size szCurLayer(szLastLayer.width / 2, szLastLayer.height / 2); |
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if (szCurLayer.width == 0 || szCurLayer.height == 0) |
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break; |
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ensureSizeIsEnough(szCurLayer, img.type(), pyramid_[i]); |
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nLayers_++; |
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const GpuMat& prevLayer = i == 0 ? layer0_ : pyramid_[i - 1]; |
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func(prevLayer, pyramid_[i], StreamAccessor::getStream(stream)); |
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szLastLayer = szCurLayer; |
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} |
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} |
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void cv::gpu::ImagePyramid::getLayer(GpuMat& outImg, Size outRoi, Stream& stream) const |
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{ |
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using namespace cv::gpu::device::pyramid; |
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typedef void (*func_t)(PtrStepSzb src, PtrStepSzb dst, cudaStream_t stream); |
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static const func_t funcs[6][4] = |
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{ |
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{kernelInterpolateFrom1_gpu<uchar1> , 0 /*kernelInterpolateFrom1_gpu<uchar2>*/ , kernelInterpolateFrom1_gpu<uchar3> , kernelInterpolateFrom1_gpu<uchar4> }, |
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{0 /*kernelInterpolateFrom1_gpu<char1>*/ , 0 /*kernelInterpolateFrom1_gpu<char2>*/ , 0 /*kernelInterpolateFrom1_gpu<char3>*/ , 0 /*kernelInterpolateFrom1_gpu<char4>*/ }, |
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{kernelInterpolateFrom1_gpu<ushort1> , 0 /*kernelInterpolateFrom1_gpu<ushort2>*/, kernelInterpolateFrom1_gpu<ushort3> , kernelInterpolateFrom1_gpu<ushort4> }, |
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{0 /*kernelInterpolateFrom1_gpu<short1>*/, 0 /*kernelInterpolateFrom1_gpu<short2>*/ , 0 /*kernelInterpolateFrom1_gpu<short3>*/, 0 /*kernelInterpolateFrom1_gpu<short4>*/}, |
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{0 /*kernelInterpolateFrom1_gpu<int1>*/ , 0 /*kernelInterpolateFrom1_gpu<int2>*/ , 0 /*kernelInterpolateFrom1_gpu<int3>*/ , 0 /*kernelInterpolateFrom1_gpu<int4>*/ }, |
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{kernelInterpolateFrom1_gpu<float1> , 0 /*kernelInterpolateFrom1_gpu<float2>*/ , kernelInterpolateFrom1_gpu<float3> , kernelInterpolateFrom1_gpu<float4> } |
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}; |
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CV_Assert(outRoi.width <= layer0_.cols && outRoi.height <= layer0_.rows && outRoi.width > 0 && outRoi.height > 0); |
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ensureSizeIsEnough(outRoi, layer0_.type(), outImg); |
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const func_t func = funcs[outImg.depth()][outImg.channels() - 1]; |
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CV_Assert(func != 0); |
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if (outRoi.width == layer0_.cols && outRoi.height == layer0_.rows) |
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{ |
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if (stream) |
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stream.enqueueCopy(layer0_, outImg); |
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else |
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layer0_.copyTo(outImg); |
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} |
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float lastScale = 1.0f; |
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float curScale; |
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GpuMat lastLayer = layer0_; |
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GpuMat curLayer; |
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for (int i = 0; i < nLayers_ - 1; ++i) |
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{ |
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curScale = lastScale * 0.5f; |
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curLayer = pyramid_[i]; |
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if (outRoi.width == curLayer.cols && outRoi.height == curLayer.rows) |
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{ |
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if (stream) |
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stream.enqueueCopy(curLayer, outImg); |
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else |
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curLayer.copyTo(outImg); |
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} |
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if (outRoi.width >= curLayer.cols && outRoi.height >= curLayer.rows) |
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break; |
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lastScale = curScale; |
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lastLayer = curLayer; |
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} |
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func(lastLayer, outImg, StreamAccessor::getStream(stream)); |
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} |
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#endif // HAVE_CUDA
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