/*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*/ #include "opencv2/opencv_modules.hpp" #ifndef HAVE_OPENCV_CUDEV #error "opencv_cudev is required" #else #include "opencv2/cudaarithm.hpp" #include "opencv2/cudev.hpp" #include "opencv2/core/private.cuda.hpp" using namespace cv; using namespace cv::cuda; using namespace cv::cudev; void cv::cuda::magnitude(InputArray _x, InputArray _y, OutputArray _dst, Stream& stream) { GpuMat x = getInputMat(_x, stream); GpuMat y = getInputMat(_y, stream); CV_Assert( x.depth() == CV_32F ); CV_Assert( y.type() == x.type() && y.size() == x.size() ); GpuMat dst = getOutputMat(_dst, x.size(), CV_32FC1, stream); GpuMat_<float> xc(x.reshape(1)); GpuMat_<float> yc(y.reshape(1)); GpuMat_<float> magc(dst.reshape(1)); gridTransformBinary(xc, yc, magc, magnitude_func<float>(), stream); syncOutput(dst, _dst, stream); } void cv::cuda::magnitudeSqr(InputArray _x, InputArray _y, OutputArray _dst, Stream& stream) { GpuMat x = getInputMat(_x, stream); GpuMat y = getInputMat(_y, stream); CV_Assert( x.depth() == CV_32F ); CV_Assert( y.type() == x.type() && y.size() == x.size() ); GpuMat dst = getOutputMat(_dst, x.size(), CV_32FC1, stream); GpuMat_<float> xc(x.reshape(1)); GpuMat_<float> yc(y.reshape(1)); GpuMat_<float> magc(dst.reshape(1)); gridTransformBinary(xc, yc, magc, magnitude_sqr_func<float>(), stream); syncOutput(dst, _dst, stream); } void cv::cuda::phase(InputArray _x, InputArray _y, OutputArray _dst, bool angleInDegrees, Stream& stream) { GpuMat x = getInputMat(_x, stream); GpuMat y = getInputMat(_y, stream); CV_Assert( x.depth() == CV_32F ); CV_Assert( y.type() == x.type() && y.size() == x.size() ); GpuMat dst = getOutputMat(_dst, x.size(), CV_32FC1, stream); GpuMat_<float> xc(x.reshape(1)); GpuMat_<float> yc(y.reshape(1)); GpuMat_<float> anglec(dst.reshape(1)); if (angleInDegrees) gridTransformBinary(xc, yc, anglec, direction_func<float, true>(), stream); else gridTransformBinary(xc, yc, anglec, direction_func<float, false>(), stream); syncOutput(dst, _dst, stream); } void cv::cuda::cartToPolar(InputArray _x, InputArray _y, OutputArray _mag, OutputArray _angle, bool angleInDegrees, Stream& stream) { GpuMat x = getInputMat(_x, stream); GpuMat y = getInputMat(_y, stream); CV_Assert( x.depth() == CV_32F ); CV_Assert( y.type() == x.type() && y.size() == x.size() ); GpuMat mag = getOutputMat(_mag, x.size(), CV_32FC1, stream); GpuMat angle = getOutputMat(_angle, x.size(), CV_32FC1, stream); GpuMat_<float> xc(x.reshape(1)); GpuMat_<float> yc(y.reshape(1)); GpuMat_<float> magc(mag.reshape(1)); GpuMat_<float> anglec(angle.reshape(1)); if (angleInDegrees) { gridTransformTuple(zipPtr(xc, yc), tie(magc, anglec), make_tuple( binaryTupleAdapter<0, 1>(magnitude_func<float>()), binaryTupleAdapter<0, 1>(direction_func<float, true>())), stream); } else { gridTransformTuple(zipPtr(xc, yc), tie(magc, anglec), make_tuple( binaryTupleAdapter<0, 1>(magnitude_func<float>()), binaryTupleAdapter<0, 1>(direction_func<float, false>())), stream); } syncOutput(mag, _mag, stream); syncOutput(angle, _angle, stream); } namespace { template <typename T> struct sincos_op { __device__ __forceinline__ void operator()(T a, T *sptr, T *cptr) const { ::sincos(a, sptr, cptr); } }; template <> struct sincos_op<float> { __device__ __forceinline__ void operator()(float a, float *sptr, float *cptr) const { ::sincosf(a, sptr, cptr); } }; template <typename T, bool useMag> __global__ void polarToCartImpl_(const GlobPtr<T> mag, const GlobPtr<T> angle, GlobPtr<T> xmat, GlobPtr<T> ymat, const T scale, const int rows, const int cols) { const int x = blockDim.x * blockIdx.x + threadIdx.x; const int y = blockDim.y * blockIdx.y + threadIdx.y; if (x >= cols || y >= rows) return; const T mag_val = useMag ? mag(y, x) : static_cast<T>(1.0); const T angle_val = angle(y, x); T sin_a, cos_a; sincos_op<T> op; op(scale * angle_val, &sin_a, &cos_a); xmat(y, x) = mag_val * cos_a; ymat(y, x) = mag_val * sin_a; } template <typename T> void polarToCartImpl(const GpuMat& mag, const GpuMat& angle, GpuMat& x, GpuMat& y, bool angleInDegrees, cudaStream_t& stream) { GpuMat_<T> xc(x.reshape(1)); GpuMat_<T> yc(y.reshape(1)); GpuMat_<T> magc(mag.reshape(1)); GpuMat_<T> anglec(angle.reshape(1)); const dim3 block(32, 8); const dim3 grid(divUp(anglec.cols, block.x), divUp(anglec.rows, block.y)); const T scale = angleInDegrees ? static_cast<T>(CV_PI / 180.0) : static_cast<T>(1.0); if (magc.empty()) polarToCartImpl_<T, false> << <grid, block, 0, stream >> >(shrinkPtr(magc), shrinkPtr(anglec), shrinkPtr(xc), shrinkPtr(yc), scale, anglec.rows, anglec.cols); else polarToCartImpl_<T, true> << <grid, block, 0, stream >> >(shrinkPtr(magc), shrinkPtr(anglec), shrinkPtr(xc), shrinkPtr(yc), scale, anglec.rows, anglec.cols); } } void cv::cuda::polarToCart(InputArray _mag, InputArray _angle, OutputArray _x, OutputArray _y, bool angleInDegrees, Stream& _stream) { typedef void(*func_t)(const GpuMat& mag, const GpuMat& angle, GpuMat& x, GpuMat& y, bool angleInDegrees, cudaStream_t& stream); static const func_t funcs[7] = { 0, 0, 0, 0, 0, polarToCartImpl<float>, polarToCartImpl<double> }; GpuMat mag = getInputMat(_mag, _stream); GpuMat angle = getInputMat(_angle, _stream); CV_Assert(angle.depth() == CV_32F || angle.depth() == CV_64F); CV_Assert( mag.empty() || (mag.type() == angle.type() && mag.size() == angle.size()) ); GpuMat x = getOutputMat(_x, angle.size(), CV_MAKETYPE(angle.depth(), 1), _stream); GpuMat y = getOutputMat(_y, angle.size(), CV_MAKETYPE(angle.depth(), 1), _stream); cudaStream_t stream = StreamAccessor::getStream(_stream); funcs[angle.depth()](mag, angle, x, y, angleInDegrees, stream); CV_CUDEV_SAFE_CALL( cudaGetLastError() ); syncOutput(x, _x, _stream); syncOutput(y, _y, _stream); if (stream == 0) CV_CUDEV_SAFE_CALL( cudaDeviceSynchronize() ); } #endif