--- /dev/null
+/*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.
+// Copyright (C) 2013, OpenCV Foundation, 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*/
+
+#pragma once
+
+#ifndef __OPENCV_CUDEV_GRID_MINMAXLOC_DETAIL_HPP__
+#define __OPENCV_CUDEV_GRID_MINMAXLOC_DETAIL_HPP__
+
+#include "../../common.hpp"
+#include "../../util/vec_traits.hpp"
+#include "../../util/type_traits.hpp"
+#include "../../util/limits.hpp"
+#include "../../block/reduce.hpp"
+
+namespace cv { namespace cudev {
+
+namespace grid_minmaxloc_detail
+{
+ template <int BLOCK_SIZE, class SrcPtr, typename ResType, class MaskPtr>
+ __global__ void minMaxLoc_pass_1(const SrcPtr src, ResType* minVal, ResType* maxVal, int* minLoc, int* maxLoc, const MaskPtr mask, const int rows, const int cols, const int patch_y, const int patch_x)
+ {
+ __shared__ ResType sMinVal[BLOCK_SIZE];
+ __shared__ ResType sMaxVal[BLOCK_SIZE];
+ __shared__ uint sMinLoc[BLOCK_SIZE];
+ __shared__ uint sMaxLoc[BLOCK_SIZE];
+
+ const int x0 = blockIdx.x * blockDim.x * patch_x + threadIdx.x;
+ const int y0 = blockIdx.y * blockDim.y * patch_y + threadIdx.y;
+
+ ResType myMin = numeric_limits<ResType>::max();
+ ResType myMax = -numeric_limits<ResType>::max();
+ int myMinLoc = -1;
+ int myMaxLoc = -1;
+
+ for (int i = 0, y = y0; i < patch_y && y < rows; ++i, y += blockDim.y)
+ {
+ for (int j = 0, x = x0; j < patch_x && x < cols; ++j, x += blockDim.x)
+ {
+ if (mask(y, x))
+ {
+ const ResType srcVal = src(y, x);
+
+ if (srcVal < myMin)
+ {
+ myMin = srcVal;
+ myMinLoc = y * cols + x;
+ }
+
+ if (srcVal > myMax)
+ {
+ myMax = srcVal;
+ myMaxLoc = y * cols + x;
+ }
+ }
+ }
+ }
+
+ const int tid = threadIdx.y * blockDim.x + threadIdx.x;
+
+ blockReduceKeyVal<BLOCK_SIZE>(smem_tuple(sMinVal, sMaxVal), tie(myMin, myMax),
+ smem_tuple(sMinLoc, sMaxLoc), tie(myMinLoc, myMaxLoc),
+ tid,
+ make_tuple(less<ResType>(), greater<ResType>()));
+
+ const int bid = blockIdx.y * gridDim.x + blockIdx.x;
+
+ if (tid == 0)
+ {
+ minVal[bid] = myMin;
+ maxVal[bid] = myMax;
+ minLoc[bid] = myMinLoc;
+ maxLoc[bid] = myMaxLoc;
+ }
+ }
+
+ template <int BLOCK_SIZE, typename T>
+ __global__ void minMaxLoc_pass_2(T* minMal, T* maxVal, int* minLoc, int* maxLoc, int count)
+ {
+ __shared__ T sMinVal[BLOCK_SIZE];
+ __shared__ T sMaxVal[BLOCK_SIZE];
+ __shared__ int sMinLoc[BLOCK_SIZE];
+ __shared__ int sMaxLoc[BLOCK_SIZE];
+
+ const int idx = ::min(threadIdx.x, count - 1);
+
+ T myMin = minMal[idx];
+ T myMax = maxVal[idx];
+ int myMinLoc = minLoc[idx];
+ int myMaxLoc = maxLoc[idx];
+
+ blockReduceKeyVal<BLOCK_SIZE>(smem_tuple(sMinVal, sMaxVal), tie(myMin, myMax),
+ smem_tuple(sMinLoc, sMaxLoc), tie(myMinLoc, myMaxLoc),
+ threadIdx.x,
+ make_tuple(less<T>(), greater<T>()));
+
+ if (threadIdx.x == 0)
+ {
+ minMal[0] = myMin;
+ maxVal[0] = myMax;
+ minLoc[0] = myMinLoc;
+ maxLoc[0] = myMaxLoc;
+ }
+ }
+
+ template <class Policy>
+ void getLaunchCfg(int rows, int cols, dim3& block, dim3& grid)
+ {
+ block = dim3(Policy::block_size_x, Policy::block_size_y);
+ grid = dim3(divUp(cols, block.x * Policy::patch_size_x), divUp(rows, block.y * Policy::patch_size_y));
+
+ grid.x = ::min(grid.x, block.x);
+ grid.y = ::min(grid.y, block.y);
+ }
+
+ template <class Policy, class SrcPtr, typename ResType, class MaskPtr>
+ __host__ void minMaxLoc(const SrcPtr& src, ResType* minVal, ResType* maxVal, int* minLoc, int* maxLoc, const MaskPtr& mask, int rows, int cols, cudaStream_t stream)
+ {
+ dim3 block, grid;
+ getLaunchCfg<Policy>(cols, rows, block, grid);
+
+ const int patch_x = divUp(divUp(cols, grid.x), block.x);
+ const int patch_y = divUp(divUp(rows, grid.y), block.y);
+
+ minMaxLoc_pass_1<Policy::block_size_x * Policy::block_size_y><<<grid, block, 0, stream>>>(src, minVal, maxVal, minLoc, maxLoc, mask, rows, cols, patch_y, patch_x);
+ CV_CUDEV_SAFE_CALL( cudaGetLastError() );
+
+ minMaxLoc_pass_2<Policy::block_size_x * Policy::block_size_y><<<1, Policy::block_size_x * Policy::block_size_y, 0, stream>>>(minVal, maxVal, minLoc, maxLoc, grid.x * grid.y);
+ CV_CUDEV_SAFE_CALL( cudaGetLastError() );
+
+ if (stream == 0)
+ CV_CUDEV_SAFE_CALL( cudaDeviceSynchronize() );
+ }
+}
+
+}}
+
+#endif
#include "../ptr2d/mask.hpp"
#include "../ptr2d/transform.hpp"
#include "detail/reduce.hpp"
+#include "detail/minmaxloc.hpp"
namespace cv { namespace cudev {
}
template <class Policy, class SrcPtr, typename ResType, class MaskPtr>
+__host__ void gridMinMaxLoc_(const SrcPtr& src, GpuMat_<ResType>& valBuf, GpuMat_<int>& locBuf, const MaskPtr& mask, Stream& stream = Stream::Null())
+{
+ const int rows = getRows(src);
+ const int cols = getCols(src);
+
+ CV_Assert( getRows(mask) == rows && getCols(mask) == cols );
+
+ dim3 grid, block;
+ grid_minmaxloc_detail::getLaunchCfg<Policy>(rows, cols, block, grid);
+
+ valBuf.create(2, grid.x * grid.y);
+ locBuf.create(2, grid.x * grid.y);
+
+ grid_minmaxloc_detail::minMaxLoc<Policy>(shrinkPtr(src),
+ valBuf[0], valBuf[1], locBuf[0], locBuf[1],
+ shrinkPtr(mask),
+ rows, cols,
+ StreamAccessor::getStream(stream));
+}
+
+template <class Policy, class SrcPtr, typename ResType>
+__host__ void gridMinMaxLoc_(const SrcPtr& src, GpuMat_<ResType>& valBuf, GpuMat_<int>& locBuf, Stream& stream = Stream::Null())
+{
+ const int rows = getRows(src);
+ const int cols = getCols(src);
+
+ dim3 grid, block;
+ grid_minmaxloc_detail::getLaunchCfg<Policy>(rows, cols, block, grid);
+
+ valBuf.create(2, grid.x * grid.y);
+ locBuf.create(2, grid.x * grid.y);
+
+ grid_minmaxloc_detail::minMaxLoc<Policy>(shrinkPtr(src),
+ valBuf[0], valBuf[1], locBuf[0], locBuf[1],
+ WithOutMask(),
+ rows, cols,
+ StreamAccessor::getStream(stream));
+}
+
+template <class Policy, class SrcPtr, typename ResType, class MaskPtr>
__host__ void gridCountNonZero_(const SrcPtr& src, GpuMat_<ResType>& dst, const MaskPtr& mask, Stream& stream = Stream::Null())
{
dst.create(1, 1);
}
template <class SrcPtr, typename ResType, class MaskPtr>
+__host__ void gridMinMaxLoc(const SrcPtr& src, GpuMat_<ResType>& valBuf, GpuMat_<int>& locBuf, const MaskPtr& mask, Stream& stream = Stream::Null())
+{
+ gridMinMaxLoc_<DefaultGlobReducePolicy>(src, valBuf, locBuf, mask, stream);
+}
+
+template <class SrcPtr, typename ResType>
+__host__ void gridMinMaxLoc(const SrcPtr& src, GpuMat_<ResType>& valBuf, GpuMat_<int>& locBuf, Stream& stream = Stream::Null())
+{
+ gridMinMaxLoc_<DefaultGlobReducePolicy>(src, valBuf, locBuf, stream);
+}
+
+template <class SrcPtr, typename ResType, class MaskPtr>
__host__ void gridCountNonZero(const SrcPtr& src, GpuMat_<ResType>& dst, const MaskPtr& mask, Stream& stream = Stream::Null())
{
gridCountNonZero_<DefaultGlobReducePolicy>(src, dst, mask, stream);
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