mirror of https://github.com/opencv/opencv.git
Vladislav Vinogradov
13 years ago
parent
484fe1d598
commit
6397fa5b38
11 changed files with 658 additions and 607 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) 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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#ifndef HAVE_CUDA |
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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(DevMem2Db src, DevMem2Db 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)(DevMem2Db src, DevMem2Db 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(DevMem2Db src, DevMem2Db 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)(DevMem2Db src, DevMem2Db 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(DevMem2Db src, DevMem2Db dst, cudaStream_t stream); |
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template <typename T> void kernelInterpolateFrom1_gpu(DevMem2Db src, DevMem2Db 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)(DevMem2Db src, DevMem2Db 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)(DevMem2Db src, DevMem2Db 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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@ -0,0 +1,126 @@ |
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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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// Intel License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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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#ifdef HAVE_CUDA |
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////////////////////////////////////////////////////////
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// pyrDown
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PARAM_TEST_CASE(PyrDown, cv::gpu::DeviceInfo, cv::Size, MatType, UseRoi) |
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{ |
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cv::gpu::DeviceInfo devInfo; |
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cv::Size size; |
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int type; |
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bool useRoi; |
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virtual void SetUp() |
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{ |
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devInfo = GET_PARAM(0); |
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size = GET_PARAM(1); |
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type = GET_PARAM(2); |
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useRoi = GET_PARAM(3); |
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cv::gpu::setDevice(devInfo.deviceID()); |
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} |
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}; |
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TEST_P(PyrDown, Accuracy) |
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{ |
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cv::Mat src = randomMat(size, type); |
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cv::gpu::GpuMat dst = createMat(cv::Size((size.width + 1) / 2, (size.height + 1) / 2), type, useRoi); |
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cv::gpu::pyrDown(loadMat(src, useRoi), dst); |
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cv::Mat dst_gold; |
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cv::pyrDown(src, dst_gold); |
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EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-4 : 1.0); |
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} |
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INSTANTIATE_TEST_CASE_P(GPU_ImgProc, PyrDown, testing::Combine( |
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ALL_DEVICES, |
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DIFFERENT_SIZES, |
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testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4), MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)), |
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WHOLE_SUBMAT)); |
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////////////////////////////////////////////////////////
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// pyrUp
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PARAM_TEST_CASE(PyrUp, cv::gpu::DeviceInfo, cv::Size, MatType, UseRoi) |
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{ |
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cv::gpu::DeviceInfo devInfo; |
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cv::Size size; |
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int type; |
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bool useRoi; |
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virtual void SetUp() |
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{ |
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devInfo = GET_PARAM(0); |
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size = GET_PARAM(1); |
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type = GET_PARAM(2); |
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useRoi = GET_PARAM(3); |
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cv::gpu::setDevice(devInfo.deviceID()); |
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} |
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}; |
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TEST_P(PyrUp, Accuracy) |
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{ |
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cv::Mat src = randomMat(size, type); |
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cv::gpu::GpuMat dst = createMat(cv::Size(size.width * 2, size.height * 2), type, useRoi); |
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cv::gpu::pyrUp(loadMat(src, useRoi), dst); |
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cv::Mat dst_gold; |
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cv::pyrUp(src, dst_gold); |
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EXPECT_MAT_NEAR(dst_gold, dst, src.depth() == CV_32F ? 1e-4 : 1.0); |
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} |
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INSTANTIATE_TEST_CASE_P(GPU_ImgProc, PyrUp, testing::Combine( |
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ALL_DEVICES, |
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DIFFERENT_SIZES, |
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testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4), MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)), |
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WHOLE_SUBMAT)); |
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#endif // HAVE_CUDA
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