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Merged the trunk r8589:8653 - all changes related to build warnings

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This commit is contained in:
Andrey Kamaev
2012-06-15 13:04:17 +00:00
parent 73c152abc4
commit bd0e0b5800
438 changed files with 20374 additions and 19674 deletions
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modules/gpu/src/color.cpp
+1 -151
View File
@@ -52,157 +52,7 @@ void cv::gpu::swapChannels(GpuMat&, const int[], Stream&) { throw_nogpu(); }
#else /* !defined (HAVE_CUDA) */
namespace cv { namespace gpu { namespace device
{
#define OPENCV_GPU_DECLARE_CVTCOLOR_ONE(name) \
void name(const DevMem2Db& src, const DevMem2Db& dst, cudaStream_t stream);
#define OPENCV_GPU_DECLARE_CVTCOLOR_ALL(name) \
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(name ## _8u) \
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(name ## _16u) \
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(name ## _32f)
#define OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(name) \
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(name ## _8u) \
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(name ## _32f) \
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(name ## _full_8u) \
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(name ## _full_32f)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgr_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgr_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgr_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgra_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgra_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgra_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgr_to_bgr555)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgr_to_bgr565)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(rgb_to_bgr555)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(rgb_to_bgr565)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgra_to_bgr555)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgra_to_bgr565)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(rgba_to_bgr555)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(rgba_to_bgr565)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgr555_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgr565_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgr555_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgr565_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgr555_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgr565_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgr555_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgr565_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(gray_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(gray_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(gray_to_bgr555)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(gray_to_bgr565)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgr555_to_gray)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgr565_to_gray)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgb_to_gray)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgr_to_gray)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgba_to_gray)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgra_to_gray)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgb_to_yuv)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgba_to_yuv)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgb_to_yuv4)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgba_to_yuv4)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgr_to_yuv)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgra_to_yuv)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgr_to_yuv4)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgra_to_yuv4)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(yuv_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(yuv_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(yuv4_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(yuv4_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(yuv_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(yuv_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(yuv4_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(yuv4_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgb_to_YCrCb)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgba_to_YCrCb)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgb_to_YCrCb4)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgba_to_YCrCb4)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgr_to_YCrCb)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgra_to_YCrCb)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgr_to_YCrCb4)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgra_to_YCrCb4)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(YCrCb_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(YCrCb_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(YCrCb4_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(YCrCb4_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(YCrCb_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(YCrCb_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(YCrCb4_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(YCrCb4_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgb_to_xyz)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgba_to_xyz)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgb_to_xyz4)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgba_to_xyz4)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgr_to_xyz)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgra_to_xyz)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgr_to_xyz4)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgra_to_xyz4)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(xyz_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(xyz4_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(xyz_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(xyz4_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(xyz_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(xyz4_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(xyz_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(xyz4_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(rgb_to_hsv)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(rgba_to_hsv)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(rgb_to_hsv4)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(rgba_to_hsv4)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(bgr_to_hsv)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(bgra_to_hsv)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(bgr_to_hsv4)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(bgra_to_hsv4)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hsv_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hsv_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hsv4_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hsv4_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hsv_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hsv_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hsv4_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hsv4_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(rgb_to_hls)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(rgba_to_hls)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(rgb_to_hls4)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(rgba_to_hls4)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(bgr_to_hls)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(bgra_to_hls)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(bgr_to_hls4)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(bgra_to_hls4)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hls_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hls_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hls4_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hls4_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hls_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hls_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hls4_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hls4_to_bgra)
#undef OPENCV_GPU_DECLARE_CVTCOLOR_ONE
#undef OPENCV_GPU_DECLARE_CVTCOLOR_ALL
#undef OPENCV_GPU_DECLARE_CVTCOLOR_8U32F
}}}
#include <cvt_colot_internal.h>
using namespace ::cv::gpu::device;
namespace
modules/gpu/src/cuda/color.cu
+4 -3
View File
@@ -40,9 +40,10 @@
//
//M*/
#include "internal_shared.hpp"
#include "opencv2/gpu/device/transform.hpp"
#include "opencv2/gpu/device/color.hpp"
#include <internal_shared.hpp>
#include <opencv2/gpu/device/transform.hpp>
#include <opencv2/gpu/device/color.hpp>
#include <cvt_colot_internal.h>
namespace cv { namespace gpu { namespace device
{
modules/gpu/src/cuda/matrix_reductions.cu
+15 -1
View File
@@ -87,7 +87,9 @@ namespace cv { namespace gpu { namespace device
__device__ __forceinline__ bool operator()(int y, int x) const
{
return true;
}
}
__device__ __forceinline__ MaskTrue(){}
__device__ __forceinline__ MaskTrue(const MaskTrue& mask_){}
};
//////////////////////////////////////////////////////////////////////////////
@@ -1795,6 +1797,9 @@ namespace cv { namespace gpu { namespace device
return 0;
}
__device__ __forceinline__ SumReductor(const SumReductor& other){}
__device__ __forceinline__ SumReductor(){}
__device__ __forceinline__ S operator ()(volatile S a, volatile S b) const
{
return a + b;
@@ -1813,6 +1818,9 @@ namespace cv { namespace gpu { namespace device
return 0;
}
__device__ __forceinline__ AvgReductor(const AvgReductor& other){}
__device__ __forceinline__ AvgReductor(){}
__device__ __forceinline__ S operator ()(volatile S a, volatile S b) const
{
return a + b;
@@ -1831,6 +1839,9 @@ namespace cv { namespace gpu { namespace device
return numeric_limits<S>::max();
}
__device__ __forceinline__ MinReductor(const MinReductor& other){}
__device__ __forceinline__ MinReductor(){}
template <typename T> __device__ __forceinline__ T operator ()(volatile T a, volatile T b) const
{
return saturate_cast<T>(::min(a, b));
@@ -1853,6 +1864,9 @@ namespace cv { namespace gpu { namespace device
return numeric_limits<S>::min();
}
__device__ __forceinline__ MaxReductor(const MaxReductor& other){}
__device__ __forceinline__ MaxReductor(){}
template <typename T> __device__ __forceinline__ int operator ()(volatile T a, volatile T b) const
{
return ::max(a, b);
modules/gpu/src/cuda/surf.cu
+3 -3
View File
@@ -116,7 +116,7 @@ namespace cv { namespace gpu { namespace device
template <int N> __device__ float icvCalcHaarPatternSum(const float src[][5], int oldSize, int newSize, int y, int x)
{
#if __CUDA_ARCH__ >= 200
#if __CUDA_ARCH__ && __CUDA_ARCH__ >= 200
typedef double real_t;
#else
typedef float real_t;
@@ -248,7 +248,7 @@ namespace cv { namespace gpu { namespace device
template <typename Mask>
__global__ void icvFindMaximaInLayer(const PtrStepf det, const PtrStepf trace, int4* maxPosBuffer, unsigned int* maxCounter)
{
#if __CUDA_ARCH__ >= 110
#if __CUDA_ARCH__ && __CUDA_ARCH__ >= 110
extern __shared__ float N9[];
@@ -371,7 +371,7 @@ namespace cv { namespace gpu { namespace device
float* featureX, float* featureY, int* featureLaplacian, int* featureOctave, float* featureSize, float* featureHessian,
unsigned int* featureCounter)
{
#if __CUDA_ARCH__ >= 110
#if __CUDA_ARCH__ && __CUDA_ARCH__ >= 110
const int4 maxPos = maxPosBuffer[blockIdx.x];
modules/gpu/src/cvt_colot_internal.h
+197
View File
@@ -0,0 +1,197 @@
/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of the copyright holders may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#ifndef __cvt_color_internal_h__
#define __cvt_color_internal_h__
namespace cv { namespace gpu { namespace device
{
#define OPENCV_GPU_DECLARE_CVTCOLOR_ONE(name) \
void name(const DevMem2Db& src, const DevMem2Db& dst, cudaStream_t stream);
#define OPENCV_GPU_DECLARE_CVTCOLOR_ALL(name) \
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(name ## _8u) \
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(name ## _16u) \
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(name ## _32f)
#define OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(name) \
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(name ## _8u) \
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(name ## _32f) \
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(name ## _full_8u) \
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(name ## _full_32f)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgr_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgr_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgr_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgra_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgra_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgra_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgr_to_bgr555)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgr_to_bgr565)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(rgb_to_bgr555)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(rgb_to_bgr565)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgra_to_bgr555)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgra_to_bgr565)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(rgba_to_bgr555)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(rgba_to_bgr565)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgr555_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgr565_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgr555_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgr565_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgr555_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgr565_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgr555_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgr565_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(gray_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(gray_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(gray_to_bgr555)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(gray_to_bgr565)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgr555_to_gray)
OPENCV_GPU_DECLARE_CVTCOLOR_ONE(bgr565_to_gray)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgb_to_gray)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgr_to_gray)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgba_to_gray)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgra_to_gray)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgb_to_yuv)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgba_to_yuv)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgb_to_yuv4)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgba_to_yuv4)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgr_to_yuv)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgra_to_yuv)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgr_to_yuv4)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgra_to_yuv4)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(yuv_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(yuv_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(yuv4_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(yuv4_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(yuv_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(yuv_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(yuv4_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(yuv4_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgb_to_YCrCb)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgba_to_YCrCb)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgb_to_YCrCb4)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgba_to_YCrCb4)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgr_to_YCrCb)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgra_to_YCrCb)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgr_to_YCrCb4)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgra_to_YCrCb4)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(YCrCb_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(YCrCb_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(YCrCb4_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(YCrCb4_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(YCrCb_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(YCrCb_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(YCrCb4_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(YCrCb4_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgb_to_xyz)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgba_to_xyz)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgb_to_xyz4)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(rgba_to_xyz4)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgr_to_xyz)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgra_to_xyz)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgr_to_xyz4)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(bgra_to_xyz4)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(xyz_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(xyz4_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(xyz_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(xyz4_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(xyz_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(xyz4_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(xyz_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_ALL(xyz4_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(rgb_to_hsv)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(rgba_to_hsv)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(rgb_to_hsv4)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(rgba_to_hsv4)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(bgr_to_hsv)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(bgra_to_hsv)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(bgr_to_hsv4)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(bgra_to_hsv4)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hsv_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hsv_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hsv4_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hsv4_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hsv_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hsv_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hsv4_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hsv4_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(rgb_to_hls)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(rgba_to_hls)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(rgb_to_hls4)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(rgba_to_hls4)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(bgr_to_hls)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(bgra_to_hls)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(bgr_to_hls4)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(bgra_to_hls4)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hls_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hls_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hls4_to_rgb)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hls4_to_rgba)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hls_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hls_to_bgra)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hls4_to_bgr)
OPENCV_GPU_DECLARE_CVTCOLOR_8U32F(hls4_to_bgra)
#undef OPENCV_GPU_DECLARE_CVTCOLOR_ONE
#undef OPENCV_GPU_DECLARE_CVTCOLOR_ALL
#undef OPENCV_GPU_DECLARE_CVTCOLOR_8U32F
}}}
#endif
modules/gpu/src/nvidia/NCVHaarObjectDetection.cu
+2 -2
View File
@@ -231,7 +231,7 @@ __device__ Ncv32u d_outMaskPosition;
__device__ void compactBlockWriteOutAnchorParallel(Ncv32u threadPassFlag, Ncv32u threadElem, Ncv32u *vectorOut)
{
#if __CUDA_ARCH__ >= 110
#if __CUDA_ARCH__ && __CUDA_ARCH__ >= 110
__shared__ Ncv32u shmem[NUM_THREADS_ANCHORSPARALLEL * 2];
__shared__ Ncv32u numPassed;
@@ -587,7 +587,7 @@ __global__ void applyHaarClassifierClassifierParallel(Ncv32u *d_IImg, Ncv32u IIm
}
else
{
#if __CUDA_ARCH__ >= 110
#if __CUDA_ARCH__ && __CUDA_ARCH__ >= 110
if (bPass && !threadIdx.x)
{
Ncv32u outMaskOffset = atomicAdd(&d_outMaskPosition, 1);
modules/gpu/src/nvidia/core/NCV.hpp
+17 -15
View File
@@ -142,7 +142,7 @@ struct NcvRect8u
Ncv8u width;
Ncv8u height;
__host__ __device__ NcvRect8u() : x(0), y(0), width(0), height(0) {};
__host__ __device__ NcvRect8u(Ncv8u x, Ncv8u y, Ncv8u width, Ncv8u height) : x(x), y(y), width(width), height(height) {}
__host__ __device__ NcvRect8u(Ncv8u x_, Ncv8u y_, Ncv8u width_, Ncv8u height_) : x(x_), y(y_), width(width_), height(height_) {}
};
@@ -153,7 +153,8 @@ struct NcvRect32s
Ncv32s width; ///< Rectangle width.
Ncv32s height; ///< Rectangle height.
__host__ __device__ NcvRect32s() : x(0), y(0), width(0), height(0) {};
__host__ __device__ NcvRect32s(Ncv32s x, Ncv32s y, Ncv32s width, Ncv32s height) : x(x), y(y), width(width), height(height) {}
__host__ __device__ NcvRect32s(Ncv32s x_, Ncv32s y_, Ncv32s width_, Ncv32s height_)
: x(x_), y(y_), width(width_), height(height_) {}
};
@@ -164,7 +165,8 @@ struct NcvRect32u
Ncv32u width; ///< Rectangle width.
Ncv32u height; ///< Rectangle height.
__host__ __device__ NcvRect32u() : x(0), y(0), width(0), height(0) {};
__host__ __device__ NcvRect32u(Ncv32u x, Ncv32u y, Ncv32u width, Ncv32u height) : x(x), y(y), width(width), height(height) {}
__host__ __device__ NcvRect32u(Ncv32u x_, Ncv32u y_, Ncv32u width_, Ncv32u height_)
: x(x_), y(y_), width(width_), height(height_) {}
};
@@ -173,7 +175,7 @@ struct NcvSize32s
Ncv32s width; ///< Rectangle width.
Ncv32s height; ///< Rectangle height.
__host__ __device__ NcvSize32s() : width(0), height(0) {};
__host__ __device__ NcvSize32s(Ncv32s width, Ncv32s height) : width(width), height(height) {}
__host__ __device__ NcvSize32s(Ncv32s width_, Ncv32s height_) : width(width_), height(height_) {}
};
@@ -182,7 +184,7 @@ struct NcvSize32u
Ncv32u width; ///< Rectangle width.
Ncv32u height; ///< Rectangle height.
__host__ __device__ NcvSize32u() : width(0), height(0) {};
__host__ __device__ NcvSize32u(Ncv32u width, Ncv32u height) : width(width), height(height) {}
__host__ __device__ NcvSize32u(Ncv32u width_, Ncv32u height_) : width(width_), height(height_) {}
__host__ __device__ bool operator == (const NcvSize32u &another) const {return this->width == another.width && this->height == another.height;}
};
@@ -192,7 +194,7 @@ struct NcvPoint2D32s
Ncv32s x; ///< Point X.
Ncv32s y; ///< Point Y.
__host__ __device__ NcvPoint2D32s() : x(0), y(0) {};
__host__ __device__ NcvPoint2D32s(Ncv32s x, Ncv32s y) : x(x), y(y) {}
__host__ __device__ NcvPoint2D32s(Ncv32s x_, Ncv32s y_) : x(x_), y(y_) {}
};
@@ -201,7 +203,7 @@ struct NcvPoint2D32u
Ncv32u x; ///< Point X.
Ncv32u y; ///< Point Y.
__host__ __device__ NcvPoint2D32u() : x(0), y(0) {};
__host__ __device__ NcvPoint2D32u(Ncv32u x, Ncv32u y) : x(x), y(y) {}
__host__ __device__ NcvPoint2D32u(Ncv32u x_, Ncv32u y_) : x(x_), y(y_) {}
};
@@ -625,9 +627,9 @@ class NCVVectorAlloc : public NCVVector<T>
public:
NCVVectorAlloc(INCVMemAllocator &allocator, Ncv32u length)
NCVVectorAlloc(INCVMemAllocator &allocator_, Ncv32u length)
:
allocator(allocator)
allocator(allocator_)
{
NCVStatus ncvStat;
@@ -839,7 +841,7 @@ class NCVMatrixAlloc : public NCVMatrix<T>
NCVMatrixAlloc& operator=(const NCVMatrixAlloc &);
public:
NCVMatrixAlloc(INCVMemAllocator &allocator, Ncv32u width, Ncv32u height, Ncv32u pitch=0)
NCVMatrixAlloc(INCVMemAllocator &allocator, Ncv32u width, Ncv32u height, Ncv32u _pitch=0)
:
allocator(allocator)
{
@@ -851,12 +853,12 @@ public:
Ncv32u widthBytes = width * sizeof(T);
Ncv32u pitchBytes = alignUp(widthBytes, allocator.alignment());
if (pitch != 0)
if (_pitch != 0)
{
ncvAssertPrintReturn(pitch >= pitchBytes &&
(pitch & (allocator.alignment() - 1)) == 0,
ncvAssertPrintReturn(_pitch >= pitchBytes &&
(_pitch & (allocator.alignment() - 1)) == 0,
"NCVMatrixAlloc ctor:: incorrect pitch passed", );
pitchBytes = pitch;
pitchBytes = _pitch;
}
Ncv32u requiredAllocSize = pitchBytes * height;
@@ -1020,4 +1022,4 @@ NCV_EXPORTS NCVStatus ncvDrawRects_32u_device(Ncv32u *d_dst, Ncv32u dstStride, N
#endif // _ncv_hpp_
#endif // _ncv_hpp_
modules/gpu/src/nvidia/core/NCVRuntimeTemplates.hpp
+1 -1
View File
@@ -41,7 +41,7 @@
#ifndef _ncvruntimetemplates_hpp_
#define _ncvruntimetemplates_hpp_
#if _MSC_VER >= 1200
#if defined _MSC_VER &&_MSC_VER >= 1200
#pragma warning( disable: 4800 )
#endif
modules/gpu/src/opencv2/gpu/device/datamov_utils.hpp
+1 -1
View File
@@ -47,7 +47,7 @@
namespace cv { namespace gpu { namespace device
{
#if __CUDA_ARCH__ >= 200
#if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 200
// for Fermi memory space is detected automatically
template <typename T> struct ForceGlob
modules/gpu/src/opencv2/gpu/device/detail/color_detail.hpp
+176 -14
View File
@@ -63,6 +63,7 @@ namespace cv { namespace gpu { namespace device
static __device__ __forceinline__ T max() { return numeric_limits<T>::max(); }
static __device__ __forceinline__ T half() { return (T)(max()/2 + 1); }
};
template<> struct ColorChannel<float>
{
typedef float worktype_f;
@@ -73,14 +74,17 @@ namespace cv { namespace gpu { namespace device
template <typename T> static __device__ __forceinline__ void setAlpha(typename TypeVec<T, 3>::vec_type& vec, T val)
{
}
template <typename T> static __device__ __forceinline__ void setAlpha(typename TypeVec<T, 4>::vec_type& vec, T val)
{
vec.w = val;
}
template <typename T> static __device__ __forceinline__ T getAlpha(const typename TypeVec<T, 3>::vec_type& vec)
{
return ColorChannel<T>::max();
}
template <typename T> static __device__ __forceinline__ T getAlpha(const typename TypeVec<T, 4>::vec_type& vec)
{
return vec.w;
@@ -101,7 +105,8 @@ namespace cv { namespace gpu { namespace device
namespace color_detail
{
template <typename T, int scn, int dcn, int bidx> struct RGB2RGB : unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>
template <typename T, int scn, int dcn, int bidx> struct RGB2RGB
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>
{
__device__ typename TypeVec<T, dcn>::vec_type operator()(const typename TypeVec<T, scn>::vec_type& src) const
{
@@ -114,6 +119,12 @@ namespace cv { namespace gpu { namespace device
return dst;
}
__device__ __forceinline__ RGB2RGB()
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>(){}
__device__ __forceinline__ RGB2RGB(const RGB2RGB& other_)
:unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>(){}
};
template <> struct RGB2RGB<uchar, 4, 4, 2> : unary_function<uint, uint>
@@ -129,6 +140,9 @@ namespace cv { namespace gpu { namespace device
return dst;
}
__device__ __forceinline__ RGB2RGB():unary_function<uint, uint>(){}
__device__ __forceinline__ RGB2RGB(const RGB2RGB& other_):unary_function<uint, uint>(){}
};
}
@@ -153,6 +167,7 @@ namespace cv { namespace gpu { namespace device
{
return (ushort)(((&src.x)[bidx] >> 3) | ((src.y & ~3) << 3) | (((&src.x)[bidx^2] & ~7) << 8));
}
static __device__ __forceinline__ ushort cvt(uint src)
{
uint b = 0xffu & (src >> (bidx * 8));
@@ -161,12 +176,14 @@ namespace cv { namespace gpu { namespace device
return (ushort)((b >> 3) | ((g & ~3) << 3) | ((r & ~7) << 8));
}
};
template<int bidx> struct RGB2RGB5x5Converter<5, bidx>
{
static __device__ __forceinline__ ushort cvt(const uchar3& src)
{
return (ushort)(((&src.x)[bidx] >> 3) | ((src.y & ~7) << 2) | (((&src.x)[bidx^2] & ~7) << 7));
}
static __device__ __forceinline__ ushort cvt(uint src)
{
uint b = 0xffu & (src >> (bidx * 8));
@@ -178,19 +195,27 @@ namespace cv { namespace gpu { namespace device
};
template<int scn, int bidx, int green_bits> struct RGB2RGB5x5;
template<int bidx, int green_bits> struct RGB2RGB5x5<3, bidx,green_bits> : unary_function<uchar3, ushort>
{
__device__ __forceinline__ ushort operator()(const uchar3& src) const
{
return RGB2RGB5x5Converter<green_bits, bidx>::cvt(src);
}
__device__ __forceinline__ RGB2RGB5x5():unary_function<uchar3, ushort>(){}
__device__ __forceinline__ RGB2RGB5x5(const RGB2RGB5x5& other_):unary_function<uchar3, ushort>(){}
};
template<int bidx, int green_bits> struct RGB2RGB5x5<4, bidx,green_bits> : unary_function<uint, ushort>
{
__device__ __forceinline__ ushort operator()(uint src) const
{
return RGB2RGB5x5Converter<green_bits, bidx>::cvt(src);
}
__device__ __forceinline__ RGB2RGB5x5():unary_function<uint, ushort>(){}
__device__ __forceinline__ RGB2RGB5x5(const RGB2RGB5x5& other_):unary_function<uint, ushort>(){}
};
}
@@ -207,6 +232,7 @@ namespace cv { namespace gpu { namespace device
namespace color_detail
{
template <int green_bits, int bidx> struct RGB5x52RGBConverter;
template <int bidx> struct RGB5x52RGBConverter<5, bidx>
{
static __device__ __forceinline__ void cvt(uint src, uchar3& dst)
@@ -215,6 +241,7 @@ namespace cv { namespace gpu { namespace device
dst.y = (src >> 2) & ~7;
(&dst.x)[bidx ^ 2] = (src >> 7) & ~7;
}
static __device__ __forceinline__ void cvt(uint src, uint& dst)
{
dst = 0;
@@ -225,6 +252,7 @@ namespace cv { namespace gpu { namespace device
dst |= ((src & 0x8000) * 0xffu) << 24;
}
};
template <int bidx> struct RGB5x52RGBConverter<6, bidx>
{
static __device__ __forceinline__ void cvt(uint src, uchar3& dst)
@@ -233,6 +261,7 @@ namespace cv { namespace gpu { namespace device
dst.y = (src >> 3) & ~3;
(&dst.x)[bidx ^ 2] = (src >> 8) & ~7;
}
static __device__ __forceinline__ void cvt(uint src, uint& dst)
{
dst = 0xffu << 24;
@@ -244,6 +273,7 @@ namespace cv { namespace gpu { namespace device
};
template <int dcn, int bidx, int green_bits> struct RGB5x52RGB;
template <int bidx, int green_bits> struct RGB5x52RGB<3, bidx, green_bits> : unary_function<ushort, uchar3>
{
__device__ __forceinline__ uchar3 operator()(ushort src) const
@@ -252,7 +282,11 @@ namespace cv { namespace gpu { namespace device
RGB5x52RGBConverter<green_bits, bidx>::cvt(src, dst);
return dst;
}
__device__ __forceinline__ RGB5x52RGB():unary_function<ushort, uchar3>(){}
__device__ __forceinline__ RGB5x52RGB(const RGB5x52RGB& other_):unary_function<ushort, uchar3>(){}
};
template <int bidx, int green_bits> struct RGB5x52RGB<4, bidx, green_bits> : unary_function<ushort, uint>
{
__device__ __forceinline__ uint operator()(ushort src) const
@@ -261,6 +295,8 @@ namespace cv { namespace gpu { namespace device
RGB5x52RGBConverter<green_bits, bidx>::cvt(src, dst);
return dst;
}
__device__ __forceinline__ RGB5x52RGB():unary_function<ushort, uint>(){}
__device__ __forceinline__ RGB5x52RGB(const RGB5x52RGB& other_):unary_function<ushort, uint>(){}
};
}
@@ -289,7 +325,11 @@ namespace cv { namespace gpu { namespace device
return dst;
}
__device__ __forceinline__ Gray2RGB():unary_function<T, typename TypeVec<T, dcn>::vec_type>(){}
__device__ __forceinline__ Gray2RGB(const Gray2RGB& other_)
: unary_function<T, typename TypeVec<T, dcn>::vec_type>(){}
};
template <> struct Gray2RGB<uchar, 4> : unary_function<uchar, uint>
{
__device__ __forceinline__ uint operator()(uint src) const
@@ -302,6 +342,8 @@ namespace cv { namespace gpu { namespace device
return dst;
}
__device__ __forceinline__ Gray2RGB():unary_function<uchar, uint>(){}
__device__ __forceinline__ Gray2RGB(const Gray2RGB& other_):unary_function<uchar, uint>(){}
};
}
@@ -325,6 +367,7 @@ namespace cv { namespace gpu { namespace device
return (ushort)((t >> 3) | ((t & ~3) << 3) | ((t & ~7) << 8));
}
};
template<> struct Gray2RGB5x5Converter<5>
{
static __device__ __forceinline__ ushort cvt(uint t)
@@ -340,6 +383,9 @@ namespace cv { namespace gpu { namespace device
{
return Gray2RGB5x5Converter<green_bits>::cvt(src);
}
__device__ __forceinline__ Gray2RGB5x5():unary_function<uchar, ushort>(){}
__device__ __forceinline__ Gray2RGB5x5(const Gray2RGB5x5& other_):unary_function<uchar, ushort>(){}
};
}
@@ -365,6 +411,7 @@ namespace cv { namespace gpu { namespace device
return (uchar)CV_DESCALE(((t << 3) & 0xf8) * B2Y + ((t >> 3) & 0xfc) * G2Y + ((t >> 8) & 0xf8) * R2Y, yuv_shift);
}
};
template <> struct RGB5x52GrayConverter<5>
{
static __device__ __forceinline__ uchar cvt(uint t)
@@ -379,6 +426,8 @@ namespace cv { namespace gpu { namespace device
{
return RGB5x52GrayConverter<green_bits>::cvt(src);
}
__device__ __forceinline__ RGB5x52Gray() : unary_function<ushort, uchar>(){}
__device__ __forceinline__ RGB5x52Gray(const RGB5x52Gray& other_) : unary_function<ushort, uchar>(){}
};
}
@@ -398,6 +447,7 @@ namespace cv { namespace gpu { namespace device
{
return (T)CV_DESCALE((unsigned)(src[bidx] * B2Y + src[1] * G2Y + src[bidx^2] * R2Y), yuv_shift);
}
template <int bidx> static __device__ __forceinline__ uchar RGB2GrayConvert(uint src)
{
uint b = 0xffu & (src >> (bidx * 8));
@@ -405,6 +455,7 @@ namespace cv { namespace gpu { namespace device
uint r = 0xffu & (src >> ((bidx ^ 2) * 8));
return CV_DESCALE((uint)(b * B2Y + g * G2Y + r * R2Y), yuv_shift);
}
template <int bidx> static __device__ __forceinline__ float RGB2GrayConvert(const float* src)
{
return src[bidx] * 0.114f + src[1] * 0.587f + src[bidx^2] * 0.299f;
@@ -416,13 +467,19 @@ namespace cv { namespace gpu { namespace device
{
return RGB2GrayConvert<bidx>(&src.x);
}
__device__ __forceinline__ RGB2Gray() : unary_function<typename TypeVec<T, scn>::vec_type, T>(){}
__device__ __forceinline__ RGB2Gray(const RGB2Gray& other_)
: unary_function<typename TypeVec<T, scn>::vec_type, T>(){}
};
template <int bidx> struct RGB2Gray<uchar, 4, bidx> : unary_function<uint, uchar>
{
__device__ __forceinline__ uchar operator()(uint src) const
{
return RGB2GrayConvert<bidx>(src);
}
__device__ __forceinline__ RGB2Gray() : unary_function<uint, uchar>(){}
__device__ __forceinline__ RGB2Gray(const RGB2Gray& other_) : unary_function<uint, uchar>(){}
};
}
@@ -463,7 +520,8 @@ namespace cv { namespace gpu { namespace device
dst.z = (src[bidx] - dst.x) * c_RGB2YUVCoeffs_f[4] + ColorChannel<float>::half();
}
template <typename T, int scn, int dcn, int bidx> struct RGB2YUV : unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>
template <typename T, int scn, int dcn, int bidx> struct RGB2YUV
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>
{
__device__ __forceinline__ typename TypeVec<T, dcn>::vec_type operator ()(const typename TypeVec<T, scn>::vec_type& src) const
{
@@ -471,6 +529,10 @@ namespace cv { namespace gpu { namespace device
RGB2YUVConvert<bidx>(&src.x, dst);
return dst;
}
__device__ __forceinline__ RGB2YUV()
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>(){}
__device__ __forceinline__ RGB2YUV(const RGB2YUV& other_)
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>(){}
};
}
@@ -492,13 +554,17 @@ namespace cv { namespace gpu { namespace device
template <int bidx, typename T, typename D> static __device__ void YUV2RGBConvert(const T& src, D* dst)
{
const int b = src.x + CV_DESCALE((src.z - ColorChannel<D>::half()) * c_YUV2RGBCoeffs_i[3], yuv_shift);
const int g = src.x + CV_DESCALE((src.z - ColorChannel<D>::half()) * c_YUV2RGBCoeffs_i[2] + (src.y - ColorChannel<D>::half()) * c_YUV2RGBCoeffs_i[1], yuv_shift);
const int g = src.x + CV_DESCALE((src.z - ColorChannel<D>::half()) * c_YUV2RGBCoeffs_i[2]
+ (src.y - ColorChannel<D>::half()) * c_YUV2RGBCoeffs_i[1], yuv_shift);
const int r = src.x + CV_DESCALE((src.y - ColorChannel<D>::half()) * c_YUV2RGBCoeffs_i[0], yuv_shift);
dst[bidx] = saturate_cast<D>(b);
dst[1] = saturate_cast<D>(g);
dst[bidx^2] = saturate_cast<D>(r);
}
template <int bidx> static __device__ uint YUV2RGBConvert(uint src)
{
const int x = 0xff & (src);
@@ -506,7 +572,10 @@ namespace cv { namespace gpu { namespace device
const int z = 0xff & (src >> 16);
const int b = x + CV_DESCALE((z - ColorChannel<uchar>::half()) * c_YUV2RGBCoeffs_i[3], yuv_shift);
const int g = x + CV_DESCALE((z - ColorChannel<uchar>::half()) * c_YUV2RGBCoeffs_i[2] + (y - ColorChannel<uchar>::half()) * c_YUV2RGBCoeffs_i[1], yuv_shift);
const int g = x + CV_DESCALE((z - ColorChannel<uchar>::half()) * c_YUV2RGBCoeffs_i[2]
+ (y - ColorChannel<uchar>::half()) * c_YUV2RGBCoeffs_i[1], yuv_shift);
const int r = x + CV_DESCALE((y - ColorChannel<uchar>::half()) * c_YUV2RGBCoeffs_i[0], yuv_shift);
uint dst = 0xffu << 24;
@@ -517,14 +586,19 @@ namespace cv { namespace gpu { namespace device
return dst;
}
template <int bidx, typename T> static __device__ __forceinline__ void YUV2RGBConvert(const T& src, float* dst)
{
dst[bidx] = src.x + (src.z - ColorChannel<float>::half()) * c_YUV2RGBCoeffs_f[3];
dst[1] = src.x + (src.z - ColorChannel<float>::half()) * c_YUV2RGBCoeffs_f[2] + (src.y - ColorChannel<float>::half()) * c_YUV2RGBCoeffs_f[1];
dst[1] = src.x + (src.z - ColorChannel<float>::half()) * c_YUV2RGBCoeffs_f[2]
+ (src.y - ColorChannel<float>::half()) * c_YUV2RGBCoeffs_f[1];
dst[bidx^2] = src.x + (src.y - ColorChannel<float>::half()) * c_YUV2RGBCoeffs_f[0];
}
template <typename T, int scn, int dcn, int bidx> struct YUV2RGB : unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>
template <typename T, int scn, int dcn, int bidx> struct YUV2RGB
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>
{
__device__ __forceinline__ typename TypeVec<T, dcn>::vec_type operator ()(const typename TypeVec<T, scn>::vec_type& src) const
{
@@ -535,13 +609,20 @@ namespace cv { namespace gpu { namespace device
return dst;
}
__device__ __forceinline__ YUV2RGB()
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>(){}
__device__ __forceinline__ YUV2RGB(const YUV2RGB& other_)
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>(){}
};
template <int bidx> struct YUV2RGB<uchar, 4, 4, bidx> : unary_function<uint, uint>
{
__device__ __forceinline__ uint operator ()(uint src) const
{
return YUV2RGBConvert<bidx>(src);
}
__device__ __forceinline__ YUV2RGB() : unary_function<uint, uint>(){}
__device__ __forceinline__ YUV2RGB(const YUV2RGB& other_) : unary_function<uint, uint>(){}
};
}
@@ -574,6 +655,7 @@ namespace cv { namespace gpu { namespace device
dst.y = saturate_cast<T>(Cr);
dst.z = saturate_cast<T>(Cb);
}
template <int bidx> static __device__ uint RGB2YCrCbConvert(uint src)
{
const int delta = ColorChannel<uchar>::half() * (1 << yuv_shift);
@@ -590,6 +672,7 @@ namespace cv { namespace gpu { namespace device
return dst;
}
template <int bidx, typename D> static __device__ __forceinline__ void RGB2YCrCbConvert(const float* src, D& dst)
{
dst.x = src[0] * c_RGB2YCrCbCoeffs_f[bidx^2] + src[1] * c_RGB2YCrCbCoeffs_f[1] + src[2] * c_RGB2YCrCbCoeffs_f[bidx];
@@ -597,7 +680,8 @@ namespace cv { namespace gpu { namespace device
dst.z = (src[bidx] - dst.x) * c_RGB2YCrCbCoeffs_f[4] + ColorChannel<float>::half();
}
template <typename T, int scn, int dcn, int bidx> struct RGB2YCrCb : unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>
template <typename T, int scn, int dcn, int bidx> struct RGB2YCrCb
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>
{
__device__ __forceinline__ typename TypeVec<T, dcn>::vec_type operator ()(const typename TypeVec<T, scn>::vec_type& src) const
{
@@ -605,13 +689,21 @@ namespace cv { namespace gpu { namespace device
RGB2YCrCbConvert<bidx>(&src.x, dst);
return dst;
}
__device__ __forceinline__ RGB2YCrCb()
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>(){}
__device__ __forceinline__ RGB2YCrCb(const RGB2YCrCb& other_)
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>(){}
};
template <int bidx> struct RGB2YCrCb<uchar, 4, 4, bidx> : unary_function<uint, uint>
{
__device__ __forceinline__ uint operator ()(uint src) const
{
return RGB2YCrCbConvert<bidx>(src);
}
__device__ __forceinline__ RGB2YCrCb() : unary_function<uint, uint>(){}
__device__ __forceinline__ RGB2YCrCb(const RGB2YCrCb& other_) : unary_function<uint, uint>(){}
};
}
@@ -640,6 +732,7 @@ namespace cv { namespace gpu { namespace device
dst[1] = saturate_cast<D>(g);
dst[bidx^2] = saturate_cast<D>(r);
}
template <int bidx> static __device__ uint YCrCb2RGBConvert(uint src)
{
const int x = 0xff & (src);
@@ -658,6 +751,7 @@ namespace cv { namespace gpu { namespace device
return dst;
}
template <int bidx, typename T> __device__ __forceinline__ void YCrCb2RGBConvert(const T& src, float* dst)
{
dst[bidx] = src.x + (src.z - ColorChannel<float>::half()) * c_YCrCb2RGBCoeffs_f[3];
@@ -665,7 +759,8 @@ namespace cv { namespace gpu { namespace device
dst[bidx^2] = src.x + (src.y - ColorChannel<float>::half()) * c_YCrCb2RGBCoeffs_f[0];
}
template <typename T, int scn, int dcn, int bidx> struct YCrCb2RGB : unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>
template <typename T, int scn, int dcn, int bidx> struct YCrCb2RGB
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>
{
__device__ __forceinline__ typename TypeVec<T, dcn>::vec_type operator ()(const typename TypeVec<T, scn>::vec_type& src) const
{
@@ -676,13 +771,20 @@ namespace cv { namespace gpu { namespace device
return dst;
}
__device__ __forceinline__ YCrCb2RGB()
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>(){}
__device__ __forceinline__ YCrCb2RGB(const YCrCb2RGB& other_)
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>(){}
};
template <int bidx> struct YCrCb2RGB<uchar, 4, 4, bidx> : unary_function<uint, uint>
{
__device__ __forceinline__ uint operator ()(uint src) const
{
return YCrCb2RGBConvert<bidx>(src);
}
__device__ __forceinline__ YCrCb2RGB() : unary_function<uint, uint>(){}
__device__ __forceinline__ YCrCb2RGB(const YCrCb2RGB& other_) : unary_function<uint, uint>(){}
};
}
@@ -709,6 +811,7 @@ namespace cv { namespace gpu { namespace device
dst.y = saturate_cast<T>(CV_DESCALE(src[bidx^2] * c_RGB2XYZ_D65i[3] + src[1] * c_RGB2XYZ_D65i[4] + src[bidx] * c_RGB2XYZ_D65i[5], xyz_shift));
dst.z = saturate_cast<T>(CV_DESCALE(src[bidx^2] * c_RGB2XYZ_D65i[6] + src[1] * c_RGB2XYZ_D65i[7] + src[bidx] * c_RGB2XYZ_D65i[8], xyz_shift));
}
template <int bidx> static __device__ __forceinline__ uint RGB2XYZConvert(uint src)
{
const uint b = 0xffu & (src >> (bidx * 8));
@@ -727,6 +830,7 @@ namespace cv { namespace gpu { namespace device
return dst;
}
template <int bidx, typename D> static __device__ __forceinline__ void RGB2XYZConvert(const float* src, D& dst)
{
dst.x = src[bidx^2] * c_RGB2XYZ_D65f[0] + src[1] * c_RGB2XYZ_D65f[1] + src[bidx] * c_RGB2XYZ_D65f[2];
@@ -734,7 +838,8 @@ namespace cv { namespace gpu { namespace device
dst.z = src[bidx^2] * c_RGB2XYZ_D65f[6] + src[1] * c_RGB2XYZ_D65f[7] + src[bidx] * c_RGB2XYZ_D65f[8];
}
template <typename T, int scn, int dcn, int bidx> struct RGB2XYZ : unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>
template <typename T, int scn, int dcn, int bidx> struct RGB2XYZ
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>
{
__device__ __forceinline__ typename TypeVec<T, dcn>::vec_type operator()(const typename TypeVec<T, scn>::vec_type& src) const
{
@@ -744,13 +849,20 @@ namespace cv { namespace gpu { namespace device
return dst;
}
__device__ __forceinline__ RGB2XYZ()
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>(){}
__device__ __forceinline__ RGB2XYZ(const RGB2XYZ& other_)
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>(){}
};
template <int bidx> struct RGB2XYZ<uchar, 4, 4, bidx> : unary_function<uint, uint>
{
__device__ __forceinline__ uint operator()(uint src) const
{
return RGB2XYZConvert<bidx>(src);
}
__device__ __forceinline__ RGB2XYZ() : unary_function<uint, uint>(){}
__device__ __forceinline__ RGB2XYZ(const RGB2XYZ& other_) : unary_function<uint, uint>(){}
};
}
@@ -775,6 +887,7 @@ namespace cv { namespace gpu { namespace device
dst[1] = saturate_cast<D>(CV_DESCALE(src.x * c_XYZ2sRGB_D65i[3] + src.y * c_XYZ2sRGB_D65i[4] + src.z * c_XYZ2sRGB_D65i[5], xyz_shift));
dst[bidx] = saturate_cast<D>(CV_DESCALE(src.x * c_XYZ2sRGB_D65i[6] + src.y * c_XYZ2sRGB_D65i[7] + src.z * c_XYZ2sRGB_D65i[8], xyz_shift));
}
template <int bidx> static __device__ __forceinline__ uint XYZ2RGBConvert(uint src)
{
const int x = 0xff & src;
@@ -793,6 +906,7 @@ namespace cv { namespace gpu { namespace device
return dst;
}
template <int bidx, typename T> static __device__ __forceinline__ void XYZ2RGBConvert(const T& src, float* dst)
{
dst[bidx^2] = src.x * c_XYZ2sRGB_D65f[0] + src.y * c_XYZ2sRGB_D65f[1] + src.z * c_XYZ2sRGB_D65f[2];
@@ -800,7 +914,8 @@ namespace cv { namespace gpu { namespace device
dst[bidx] = src.x * c_XYZ2sRGB_D65f[6] + src.y * c_XYZ2sRGB_D65f[7] + src.z * c_XYZ2sRGB_D65f[8];
}
template <typename T, int scn, int dcn, int bidx> struct XYZ2RGB : unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>
template <typename T, int scn, int dcn, int bidx> struct XYZ2RGB
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>
{
__device__ __forceinline__ typename TypeVec<T, dcn>::vec_type operator()(const typename TypeVec<T, scn>::vec_type& src) const
{
@@ -811,13 +926,20 @@ namespace cv { namespace gpu { namespace device
return dst;
}
__device__ __forceinline__ XYZ2RGB()
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>(){}
__device__ __forceinline__ XYZ2RGB(const XYZ2RGB& other_)
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>(){}
};
template <int bidx> struct XYZ2RGB<uchar, 4, 4, bidx> : unary_function<uint, uint>
{
__device__ __forceinline__ uint operator()(uint src) const
{
return XYZ2RGBConvert<bidx>(src);
}
__device__ __forceinline__ XYZ2RGB() : unary_function<uint, uint>(){}
__device__ __forceinline__ XYZ2RGB(const XYZ2RGB& other_) : unary_function<uint, uint>(){}
};
}
@@ -867,6 +989,7 @@ namespace cv { namespace gpu { namespace device
dst.y = (uchar)s;
dst.z = (uchar)v;
}
template <int bidx, int hr> static __device__ uint RGB2HSVConvert(uint src)
{
const int hsv_shift = 12;
@@ -902,6 +1025,7 @@ namespace cv { namespace gpu { namespace device
return dst;
}
template <int bidx, int hr, typename D> static __device__ void RGB2HSVConvert(const float* src, D& dst)
{
const float hscale = hr * (1.f / 360.f);
@@ -931,7 +1055,8 @@ namespace cv { namespace gpu { namespace device
dst.z = v;
}
template <typename T, int scn, int dcn, int bidx, int hr> struct RGB2HSV : unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>
template <typename T, int scn, int dcn, int bidx, int hr> struct RGB2HSV
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>
{
__device__ __forceinline__ typename TypeVec<T, dcn>::vec_type operator()(const typename TypeVec<T, scn>::vec_type& src) const
{
@@ -941,13 +1066,20 @@ namespace cv { namespace gpu { namespace device
return dst;
}
__device__ __forceinline__ RGB2HSV()
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>(){}
__device__ __forceinline__ RGB2HSV(const RGB2HSV& other_)
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>(){}
};
template <int bidx, int hr> struct RGB2HSV<uchar, 4, 4, bidx, hr> : unary_function<uint, uint>
{
__device__ __forceinline__ uint operator()(uint src) const
{
return RGB2HSVConvert<bidx, hr>(src);
}
__device__ __forceinline__ RGB2HSV():unary_function<uint, uint>(){}
__device__ __forceinline__ RGB2HSV(const RGB2HSV& other_):unary_function<uint, uint>(){}
};
}
@@ -1023,6 +1155,7 @@ namespace cv { namespace gpu { namespace device
dst[1] = g;
dst[bidx^2] = r;
}
template <int bidx, int HR, typename T> static __device__ void HSV2RGBConvert(const T& src, uchar* dst)
{
float3 buf;
@@ -1037,6 +1170,7 @@ namespace cv { namespace gpu { namespace device
dst[1] = saturate_cast<uchar>(buf.y * 255.f);
dst[2] = saturate_cast<uchar>(buf.z * 255.f);
}
template <int bidx, int hr> static __device__ uint HSV2RGBConvert(uint src)
{
float3 buf;
@@ -1056,7 +1190,8 @@ namespace cv { namespace gpu { namespace device
return dst;
}
template <typename T, int scn, int dcn, int bidx, int hr> struct HSV2RGB : unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>
template <typename T, int scn, int dcn, int bidx, int hr> struct HSV2RGB
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>
{
__device__ __forceinline__ typename TypeVec<T, dcn>::vec_type operator()(const typename TypeVec<T, scn>::vec_type& src) const
{
@@ -1067,13 +1202,20 @@ namespace cv { namespace gpu { namespace device
return dst;
}
__device__ __forceinline__ HSV2RGB()
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>(){}
__device__ __forceinline__ HSV2RGB(const HSV2RGB& other_)
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>(){}
};
template <int bidx, int hr> struct HSV2RGB<uchar, 4, 4, bidx, hr> : unary_function<uint, uint>
{
__device__ __forceinline__ uint operator()(uint src) const
{
return HSV2RGBConvert<bidx, hr>(src);
}
__device__ __forceinline__ HSV2RGB():unary_function<uint, uint>(){}
__device__ __forceinline__ HSV2RGB(const HSV2RGB& other_):unary_function<uint, uint>(){}
};
}
@@ -1149,6 +1291,7 @@ namespace cv { namespace gpu { namespace device
dst.y = l;
dst.z = s;
}
template <int bidx, int hr, typename D> static __device__ void RGB2HLSConvert(const uchar* src, D& dst)
{
float3 buf;
@@ -1163,6 +1306,7 @@ namespace cv { namespace gpu { namespace device
dst.y = saturate_cast<uchar>(buf.y*255.f);
dst.z = saturate_cast<uchar>(buf.z*255.f);
}
template <int bidx, int hr> static __device__ uint RGB2HLSConvert(uint src)
{
float3 buf;
@@ -1182,7 +1326,8 @@ namespace cv { namespace gpu { namespace device
return dst;
}
template <typename T, int scn, int dcn, int bidx, int hr> struct RGB2HLS : unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>
template <typename T, int scn, int dcn, int bidx, int hr> struct RGB2HLS
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>
{
__device__ __forceinline__ typename TypeVec<T, dcn>::vec_type operator()(const typename TypeVec<T, scn>::vec_type& src) const
{
@@ -1192,13 +1337,20 @@ namespace cv { namespace gpu { namespace device
return dst;
}
__device__ __forceinline__ RGB2HLS()
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>(){}
__device__ __forceinline__ RGB2HLS(const RGB2HLS& other_)
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>(){}
};
template <int bidx, int hr> struct RGB2HLS<uchar, 4, 4, bidx, hr> : unary_function<uint, uint>
{
__device__ __forceinline__ uint operator()(uint src) const
{
return RGB2HLSConvert<bidx, hr>(src);
}
__device__ __forceinline__ RGB2HLS() : unary_function<uint, uint>(){}
__device__ __forceinline__ RGB2HLS(const RGB2HLS& other_) : unary_function<uint, uint>(){}
};
}
@@ -1280,6 +1432,7 @@ namespace cv { namespace gpu { namespace device
dst[1] = g;
dst[bidx^2] = r;
}
template <int bidx, int hr, typename T> static __device__ void HLS2RGBConvert(const T& src, uchar* dst)
{
float3 buf;
@@ -1294,6 +1447,7 @@ namespace cv { namespace gpu { namespace device
dst[1] = saturate_cast<uchar>(buf.y * 255.f);
dst[2] = saturate_cast<uchar>(buf.z * 255.f);
}
template <int bidx, int hr> static __device__ uint HLS2RGBConvert(uint src)
{
float3 buf;
@@ -1313,7 +1467,8 @@ namespace cv { namespace gpu { namespace device
return dst;
}
template <typename T, int scn, int dcn, int bidx, int hr> struct HLS2RGB : unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>
template <typename T, int scn, int dcn, int bidx, int hr> struct HLS2RGB
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>
{
__device__ __forceinline__ typename TypeVec<T, dcn>::vec_type operator()(const typename TypeVec<T, scn>::vec_type& src) const
{
@@ -1324,13 +1479,20 @@ namespace cv { namespace gpu { namespace device
return dst;
}
__device__ __forceinline__ HLS2RGB()
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>(){}
__device__ __forceinline__ HLS2RGB(const HLS2RGB& other_)
: unary_function<typename TypeVec<T, scn>::vec_type, typename TypeVec<T, dcn>::vec_type>(){}
};
template <int bidx, int hr> struct HLS2RGB<uchar, 4, 4, bidx, hr> : unary_function<uint, uint>
{
__device__ __forceinline__ uint operator()(uint src) const
{
return HLS2RGBConvert<bidx, hr>(src);
}
__device__ __forceinline__ HLS2RGB() : unary_function<uint, uint>(){}
__device__ __forceinline__ HLS2RGB(const HLS2RGB& other_) : unary_function<uint, uint>(){}
};
}
modules/gpu/src/opencv2/gpu/device/functional.hpp
+127 -26
View File
@@ -56,158 +56,224 @@ namespace cv { namespace gpu { namespace device
using thrust::binary_function;
// Arithmetic Operations
template <typename T> struct plus : binary_function<T, T, T>
{
__device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a, typename TypeTraits<T>::ParameterType b) const
__device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a,
typename TypeTraits<T>::ParameterType b) const
{
return a + b;
}
__device__ __forceinline__ plus(const plus& other):binary_function<T,T,T>(){}
__device__ __forceinline__ plus():binary_function<T,T,T>(){}
};
template <typename T> struct minus : binary_function<T, T, T>
{
__device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a, typename TypeTraits<T>::ParameterType b) const
__device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a,
typename TypeTraits<T>::ParameterType b) const
{
return a - b;
}
__device__ __forceinline__ minus(const minus& other):binary_function<T,T,T>(){}
__device__ __forceinline__ minus():binary_function<T,T,T>(){}
};
template <typename T> struct multiplies : binary_function<T, T, T>
{
__device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a, typename TypeTraits<T>::ParameterType b) const
__device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a,
typename TypeTraits<T>::ParameterType b) const
{
return a * b;
}
__device__ __forceinline__ multiplies(const multiplies& other):binary_function<T,T,T>(){}
__device__ __forceinline__ multiplies():binary_function<T,T,T>(){}
};
template <typename T> struct divides : binary_function<T, T, T>
{
__device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a, typename TypeTraits<T>::ParameterType b) const
__device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a,
typename TypeTraits<T>::ParameterType b) const
{
return a / b;
}
__device__ __forceinline__ divides(const divides& other):binary_function<T,T,T>(){}
__device__ __forceinline__ divides():binary_function<T,T,T>(){}
};
template <typename T> struct modulus : binary_function<T, T, T>
{
__device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a, typename TypeTraits<T>::ParameterType b) const
__device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a,
typename TypeTraits<T>::ParameterType b) const
{
return a % b;
}
__device__ __forceinline__ modulus(const modulus& other):binary_function<T,T,T>(){}
__device__ __forceinline__ modulus():binary_function<T,T,T>(){}
};
template <typename T> struct negate : unary_function<T, T>
{
__device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a) const
{
return -a;
}
__device__ __forceinline__ negate(const negate& other):unary_function<T,T>(){}
__device__ __forceinline__ negate():unary_function<T,T>(){}
};
// Comparison Operations
template <typename T> struct equal_to : binary_function<T, T, bool>
{
__device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a, typename TypeTraits<T>::ParameterType b) const
__device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a,
typename TypeTraits<T>::ParameterType b) const
{
return a == b;
}
__device__ __forceinline__ equal_to(const equal_to& other):binary_function<T,T,bool>(){}
__device__ __forceinline__ equal_to():binary_function<T,T,bool>(){}
};
template <typename T> struct not_equal_to : binary_function<T, T, bool>
{
__device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a, typename TypeTraits<T>::ParameterType b) const
__device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a,
typename TypeTraits<T>::ParameterType b) const
{
return a != b;
}
__device__ __forceinline__ not_equal_to(const not_equal_to& other):binary_function<T,T,bool>(){}
__device__ __forceinline__ not_equal_to():binary_function<T,T,bool>(){}
};
template <typename T> struct greater : binary_function<T, T, bool>
{
__device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a, typename TypeTraits<T>::ParameterType b) const
__device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a,
typename TypeTraits<T>::ParameterType b) const
{
return a > b;
}
__device__ __forceinline__ greater(const greater& other):binary_function<T,T,bool>(){}
__device__ __forceinline__ greater():binary_function<T,T,bool>(){}
};
template <typename T> struct less : binary_function<T, T, bool>
{
__device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a, typename TypeTraits<T>::ParameterType b) const
__device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a,
typename TypeTraits<T>::ParameterType b) const
{
return a < b;
}
__device__ __forceinline__ less(const less& other):binary_function<T,T,bool>(){}
__device__ __forceinline__ less():binary_function<T,T,bool>(){}
};
template <typename T> struct greater_equal : binary_function<T, T, bool>
{
__device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a, typename TypeTraits<T>::ParameterType b) const
__device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a,
typename TypeTraits<T>::ParameterType b) const
{
return a >= b;
}
__device__ __forceinline__ greater_equal(const greater_equal& other):binary_function<T,T,bool>(){}
__device__ __forceinline__ greater_equal():binary_function<T,T,bool>(){}
};
template <typename T> struct less_equal : binary_function<T, T, bool>
{
__device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a, typename TypeTraits<T>::ParameterType b) const
__device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a,
typename TypeTraits<T>::ParameterType b) const
{
return a <= b;
}
__device__ __forceinline__ less_equal(const less_equal& other):binary_function<T,T,bool>(){}
__device__ __forceinline__ less_equal():binary_function<T,T,bool>(){}
};
// Logical Operations
template <typename T> struct logical_and : binary_function<T, T, bool>
{
__device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a, typename TypeTraits<T>::ParameterType b) const
__device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a,
typename TypeTraits<T>::ParameterType b) const
{
return a && b;
}
__device__ __forceinline__ logical_and(const logical_and& other):binary_function<T,T,bool>(){}
__device__ __forceinline__ logical_and():binary_function<T,T,bool>(){}
};
template <typename T> struct logical_or : binary_function<T, T, bool>
{
__device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a, typename TypeTraits<T>::ParameterType b) const
__device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a,
typename TypeTraits<T>::ParameterType b) const
{
return a || b;
}
__device__ __forceinline__ logical_or(const logical_or& other):binary_function<T,T,bool>(){}
__device__ __forceinline__ logical_or():binary_function<T,T,bool>(){}
};
template <typename T> struct logical_not : unary_function<T, bool>
{
__device__ __forceinline__ bool operator ()(typename TypeTraits<T>::ParameterType a) const
{
return !a;
}
__device__ __forceinline__ logical_not(const logical_not& other):unary_function<T,bool>(){}
__device__ __forceinline__ logical_not():unary_function<T,bool>(){}
};
// Bitwise Operations
template <typename T> struct bit_and : binary_function<T, T, T>
{
__device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a, typename TypeTraits<T>::ParameterType b) const
__device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a,
typename TypeTraits<T>::ParameterType b) const
{
return a & b;
}
__device__ __forceinline__ bit_and(const bit_and& other):binary_function<T,T,T>(){}
__device__ __forceinline__ bit_and():binary_function<T,T,T>(){}
};
template <typename T> struct bit_or : binary_function<T, T, T>
{
__device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a, typename TypeTraits<T>::ParameterType b) const
__device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a,
typename TypeTraits<T>::ParameterType b) const
{
return a | b;
}
__device__ __forceinline__ bit_or(const bit_or& other):binary_function<T,T,T>(){}
__device__ __forceinline__ bit_or():binary_function<T,T,T>(){}
};
template <typename T> struct bit_xor : binary_function<T, T, T>
{
__device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a, typename TypeTraits<T>::ParameterType b) const
__device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType a,
typename TypeTraits<T>::ParameterType b) const
{
return a ^ b;
}
__device__ __forceinline__ bit_xor(const bit_xor& other):binary_function<T,T,T>(){}
__device__ __forceinline__ bit_xor():binary_function<T,T,T>(){}
};
template <typename T> struct bit_not : unary_function<T, T>
{
__device__ __forceinline__ T operator ()(typename TypeTraits<T>::ParameterType v) const
{
return ~v;
}
__device__ __forceinline__ bit_not(const bit_not& other):unary_function<T,T>(){}
__device__ __forceinline__ bit_not():unary_function<T,T>(){}
};
// Generalized Identity Operations
template <typename T> struct identity : unary_function<T, T>
{
__device__ __forceinline__ typename TypeTraits<T>::ParameterType operator()(typename TypeTraits<T>::ParameterType x) const
{
return x;
}
__device__ __forceinline__ identity(const identity& other):unary_function<T,T>(){}
__device__ __forceinline__ identity():unary_function<T,T>(){}
};
template <typename T1, typename T2> struct project1st : binary_function<T1, T2, T1>
@@ -216,13 +282,18 @@ namespace cv { namespace gpu { namespace device
{
return lhs;
}
__device__ __forceinline__ project1st(const project1st& other):binary_function<T1,T2,T1>(){}
__device__ __forceinline__ project1st():binary_function<T1,T2,T1>(){}
};
template <typename T1, typename T2> struct project2nd : binary_function<T1, T2, T2>
{
__device__ __forceinline__ typename TypeTraits<T2>::ParameterType operator()(typename TypeTraits<T1>::ParameterType lhs, typename TypeTraits<T2>::ParameterType rhs) const
{
return rhs;
}
__device__ __forceinline__ project2nd(const project2nd& other):binary_function<T1,T2,T2>(){}
__device__ __forceinline__ project2nd():binary_function<T1,T2,T2>(){}
};
// Min/Max Operations
@@ -231,6 +302,8 @@ namespace cv { namespace gpu { namespace device
template <> struct name<type> : binary_function<type, type, type> \
{ \
__device__ __forceinline__ type operator()(type lhs, type rhs) const {return op(lhs, rhs);} \
__device__ __forceinline__ name(const name& other):binary_function<type, type, type>(){}\
__device__ __forceinline__ name():binary_function<type, type, type>(){}\
};
template <typename T> struct maximum : binary_function<T, T, T>
@@ -239,6 +312,8 @@ namespace cv { namespace gpu { namespace device
{
return lhs < rhs ? rhs : lhs;
}
__device__ __forceinline__ maximum(const maximum& other):binary_function<T, T, T>(){}
__device__ __forceinline__ maximum():binary_function<T, T, T>(){}
};
OPENCV_GPU_IMPLEMENT_MINMAX(maximum, uchar, ::max)
@@ -257,6 +332,8 @@ namespace cv { namespace gpu { namespace device
{
return lhs < rhs ? lhs : rhs;
}
__device__ __forceinline__ minimum(const minimum& other):binary_function<T, T, T>(){}
__device__ __forceinline__ minimum():binary_function<T, T, T>(){}
};
OPENCV_GPU_IMPLEMENT_MINMAX(minimum, uchar, ::min)
@@ -272,7 +349,7 @@ namespace cv { namespace gpu { namespace device
#undef OPENCV_GPU_IMPLEMENT_MINMAX
// Math functions
///bound=========================================
#define OPENCV_GPU_IMPLEMENT_UN_FUNCTOR(name, func) \
template <typename T> struct name ## _func : unary_function<T, float> \
{ \
@@ -342,17 +419,17 @@ namespace cv { namespace gpu { namespace device
};
// Saturate Cast Functor
template <typename T, typename D> struct saturate_cast_func : unary_function<T, D>
{
__device__ __forceinline__ D operator ()(typename TypeTraits<T>::ParameterType v) const
{
return saturate_cast<D>(v);
}
__device__ __forceinline__ saturate_cast_func(const saturate_cast_func& other):unary_function<T, D>(){}
__device__ __forceinline__ saturate_cast_func():unary_function<T, D>(){}
};
// Threshold Functors
template <typename T> struct thresh_binary_func : unary_function<T, T>
{
__host__ __device__ __forceinline__ thresh_binary_func(T thresh_, T maxVal_) : thresh(thresh_), maxVal(maxVal_) {}
@@ -361,10 +438,15 @@ namespace cv { namespace gpu { namespace device
{
return (src > thresh) * maxVal;
}
__device__ __forceinline__ thresh_binary_func(const thresh_binary_func& other)
: unary_function<T, T>(), thresh(other.thresh), maxVal(other.maxVal){}
__device__ __forceinline__ thresh_binary_func():unary_function<T, T>(){}
const T thresh;
const T maxVal;
};
template <typename T> struct thresh_binary_inv_func : unary_function<T, T>
{
__host__ __device__ __forceinline__ thresh_binary_inv_func(T thresh_, T maxVal_) : thresh(thresh_), maxVal(maxVal_) {}
@@ -373,10 +455,15 @@ namespace cv { namespace gpu { namespace device
{
return (src <= thresh) * maxVal;
}
__device__ __forceinline__ thresh_binary_inv_func(const thresh_binary_inv_func& other)
: unary_function<T, T>(), thresh(other.thresh), maxVal(other.maxVal){}
__device__ __forceinline__ thresh_binary_inv_func():unary_function<T, T>(){}
const T thresh;
const T maxVal;
};
template <typename T> struct thresh_trunc_func : unary_function<T, T>
{
explicit __host__ __device__ __forceinline__ thresh_trunc_func(T thresh_, T maxVal_ = 0) : thresh(thresh_) {}
@@ -386,8 +473,14 @@ namespace cv { namespace gpu { namespace device
return minimum<T>()(src, thresh);
}
__device__ __forceinline__ thresh_trunc_func(const thresh_trunc_func& other)
: unary_function<T, T>(), thresh(other.thresh){}
__device__ __forceinline__ thresh_trunc_func():unary_function<T, T>(){}
const T thresh;
};
template <typename T> struct thresh_to_zero_func : unary_function<T, T>
{
explicit __host__ __device__ __forceinline__ thresh_to_zero_func(T thresh_, T maxVal_ = 0) : thresh(thresh_) {}
@@ -396,9 +489,14 @@ namespace cv { namespace gpu { namespace device
{
return (src > thresh) * src;
}
__device__ __forceinline__ thresh_to_zero_func(const thresh_to_zero_func& other)
: unary_function<T, T>(), thresh(other.thresh){}
__device__ __forceinline__ thresh_to_zero_func():unary_function<T, T>(){}
const T thresh;
};
template <typename T> struct thresh_to_zero_inv_func : unary_function<T, T>
{
explicit __host__ __device__ __forceinline__ thresh_to_zero_inv_func(T thresh_, T maxVal_ = 0) : thresh(thresh_) {}
@@ -407,12 +505,15 @@ namespace cv { namespace gpu { namespace device
{
return (src <= thresh) * src;
}
__device__ __forceinline__ thresh_to_zero_inv_func(const thresh_to_zero_inv_func& other)
: unary_function<T, T>(), thresh(other.thresh){}
__device__ __forceinline__ thresh_to_zero_inv_func():unary_function<T, T>(){}
const T thresh;
};
//bound!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! ============>
// Function Object Adaptors
template <typename Predicate> struct unary_negate : unary_function<typename Predicate::argument_type, bool>
{
explicit __host__ __device__ __forceinline__ unary_negate(const Predicate& p) : pred(p) {}
modules/gpu/src/opencv2/gpu/device/saturate_cast.hpp
+7 -7
View File
@@ -84,7 +84,7 @@ namespace cv { namespace gpu { namespace device
}
template<> __device__ __forceinline__ uchar saturate_cast<uchar>(double v)
{
#if __CUDA_ARCH__ >= 130
#if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 130
int iv = __double2int_rn(v);
return saturate_cast<uchar>(iv);
#else
@@ -120,7 +120,7 @@ namespace cv { namespace gpu { namespace device
}
template<> __device__ __forceinline__ schar saturate_cast<schar>(double v)
{
#if __CUDA_ARCH__ >= 130
#if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 130
int iv = __double2int_rn(v);
return saturate_cast<schar>(iv);
#else
@@ -151,7 +151,7 @@ namespace cv { namespace gpu { namespace device
}
template<> __device__ __forceinline__ ushort saturate_cast<ushort>(double v)
{
#if __CUDA_ARCH__ >= 130
#if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 130
int iv = __double2int_rn(v);
return saturate_cast<ushort>(iv);
#else
@@ -178,7 +178,7 @@ namespace cv { namespace gpu { namespace device
}
template<> __device__ __forceinline__ short saturate_cast<short>(double v)
{
#if __CUDA_ARCH__ >= 130
#if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 130
int iv = __double2int_rn(v);
return saturate_cast<short>(iv);
#else
@@ -192,7 +192,7 @@ namespace cv { namespace gpu { namespace device
}
template<> __device__ __forceinline__ int saturate_cast<int>(double v)
{
#if __CUDA_ARCH__ >= 130
#if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 130
return __double2int_rn(v);
#else
return saturate_cast<int>((float)v);
@@ -205,7 +205,7 @@ namespace cv { namespace gpu { namespace device
}
template<> __device__ __forceinline__ uint saturate_cast<uint>(double v)
{
#if __CUDA_ARCH__ >= 130
#if defined __CUDA_ARCH__ && __CUDA_ARCH__ >= 130
return __double2uint_rn(v);
#else
return saturate_cast<uint>((float)v);
@@ -213,4 +213,4 @@ namespace cv { namespace gpu { namespace device
}
}}}
#endif /* __OPENCV_GPU_SATURATE_CAST_HPP__ */
#endif /* __OPENCV_GPU_SATURATE_CAST_HPP__ */
modules/gpu/src/opencv2/gpu/device/transform.hpp
+2 -2
View File
@@ -50,14 +50,14 @@
namespace cv { namespace gpu { namespace device
{
template <typename T, typename D, typename UnOp, typename Mask>
static inline void transform(DevMem2D_<T> src, DevMem2D_<D> dst, UnOp op, Mask mask, cudaStream_t stream)
static inline void transform(DevMem2D_<T> src, DevMem2D_<D> dst, UnOp op, const Mask& mask, cudaStream_t stream)
{
typedef TransformFunctorTraits<UnOp> ft;
transform_detail::TransformDispatcher<VecTraits<T>::cn == 1 && VecTraits<D>::cn == 1 && ft::smart_shift != 1>::call(src, dst, op, mask, stream);
}
template <typename T1, typename T2, typename D, typename BinOp, typename Mask>
static inline void transform(DevMem2D_<T1> src1, DevMem2D_<T2> src2, DevMem2D_<D> dst, BinOp op, Mask mask, cudaStream_t stream)
static inline void transform(DevMem2D_<T1> src1, DevMem2D_<T2> src2, DevMem2D_<D> dst, BinOp op, const Mask& mask, cudaStream_t stream)
{
typedef TransformFunctorTraits<BinOp> ft;
transform_detail::TransformDispatcher<VecTraits<T1>::cn == 1 && VecTraits<T2>::cn == 1 && VecTraits<D>::cn == 1 && ft::smart_shift != 1>::call(src1, src2, dst, op, mask, stream);
modules/gpu/src/opencv2/gpu/device/utility.hpp
+13 -2
View File
@@ -70,6 +70,7 @@ namespace cv { namespace gpu { namespace device
struct SingleMask
{
explicit __host__ __device__ __forceinline__ SingleMask(PtrStepb mask_) : mask(mask_) {}
__host__ __device__ __forceinline__ SingleMask(const SingleMask& mask_): mask(mask_.mask){}
__device__ __forceinline__ bool operator()(int y, int x) const
{
@@ -81,7 +82,10 @@ namespace cv { namespace gpu { namespace device
struct SingleMaskChannels
{
__host__ __device__ __forceinline__ SingleMaskChannels(PtrStepb mask_, int channels_) : mask(mask_), channels(channels_) {}
__host__ __device__ __forceinline__ SingleMaskChannels(PtrStepb mask_, int channels_)
: mask(mask_), channels(channels_) {}
__host__ __device__ __forceinline__ SingleMaskChannels(const SingleMaskChannels& mask_)
:mask(mask_.mask), channels(mask_.channels){}
__device__ __forceinline__ bool operator()(int y, int x) const
{
@@ -94,7 +98,11 @@ namespace cv { namespace gpu { namespace device
struct MaskCollection
{
explicit __host__ __device__ __forceinline__ MaskCollection(PtrStepb* maskCollection_) : maskCollection(maskCollection_) {}
explicit __host__ __device__ __forceinline__ MaskCollection(PtrStepb* maskCollection_)
: maskCollection(maskCollection_) {}
__device__ __forceinline__ MaskCollection(const MaskCollection& masks_)
: maskCollection(masks_.maskCollection), curMask(masks_.curMask){}
__device__ __forceinline__ void next()
{
@@ -117,6 +125,9 @@ namespace cv { namespace gpu { namespace device
struct WithOutMask
{
__device__ __forceinline__ WithOutMask(){}
__device__ __forceinline__ WithOutMask(const WithOutMask& mask){}
__device__ __forceinline__ void next() const
{
}
modules/gpu/src/precomp.hpp
+1 -1
View File
@@ -43,7 +43,7 @@
#ifndef __OPENCV_PRECOMP_H__
#define __OPENCV_PRECOMP_H__
#if _MSC_VER >= 1200
#if defined _MSC_VER && _MSC_VER >= 1200
#pragma warning( disable: 4251 4710 4711 4514 4996 )
#endif