diff --git a/modules/gpu/include/opencv2/gpu/gpu.hpp b/modules/gpu/include/opencv2/gpu/gpu.hpp index 56758ce47..0ac16e2b1 100644 --- a/modules/gpu/include/opencv2/gpu/gpu.hpp +++ b/modules/gpu/include/opencv2/gpu/gpu.hpp @@ -656,7 +656,34 @@ namespace cv //! computes convolution (or cross-correlation) of two images using discrete Fourier transform //! supports source images of 32FC1 type only //! result matrix will have 32FC1 type - CV_EXPORTS void convolve(const GpuMat& image, const GpuMat& templ, GpuMat& result, bool ccorr=false); + CV_EXPORTS void convolve(const GpuMat& image, const GpuMat& templ, GpuMat& result, + bool ccorr=false); + + struct CV_EXPORTS ConvolveBuf; + + //! buffered version + CV_EXPORTS void convolve(const GpuMat& image, const GpuMat& templ, GpuMat& result, + bool ccorr, ConvolveBuf& buf); + + struct CV_EXPORTS ConvolveBuf + { + ConvolveBuf() {} + ConvolveBuf(Size image_size, Size templ_size) + { create(image_size, templ_size); } + void create(Size image_size, Size templ_size); + + private: + static Size estimateBlockSize(Size result_size, Size templ_size); + friend void convolve(const GpuMat&, const GpuMat&, GpuMat&, bool, ConvolveBuf&); + + Size result_size; + Size block_size; + Size dft_size; + int spect_len; + + GpuMat image_spect, templ_spect, result_spect; + GpuMat image_block, templ_block, result_data; + }; //! computes the proximity map for the raster template and the image where the template is searched for CV_EXPORTS void matchTemplate(const GpuMat& image, const GpuMat& templ, GpuMat& result, int method); diff --git a/modules/gpu/src/imgproc_gpu.cpp b/modules/gpu/src/imgproc_gpu.cpp index bf8e7f6d8..3b866c945 100644 --- a/modules/gpu/src/imgproc_gpu.cpp +++ b/modules/gpu/src/imgproc_gpu.cpp @@ -77,7 +77,9 @@ void cv::gpu::cornerMinEigenVal(const GpuMat&, GpuMat&, int, int, int) { throw_n void cv::gpu::mulSpectrums(const GpuMat&, const GpuMat&, GpuMat&, int, bool) { throw_nogpu(); } void cv::gpu::mulAndScaleSpectrums(const GpuMat&, const GpuMat&, GpuMat&, int, float, bool) { throw_nogpu(); } void cv::gpu::dft(const GpuMat&, GpuMat&, Size, int) { throw_nogpu(); } +void cv::gpu::ConvolveBuf::create(Size, Size) { throw_nogpu(); } void cv::gpu::convolve(const GpuMat&, const GpuMat&, GpuMat&, bool) { throw_nogpu(); } +void cv::gpu::convolve(const GpuMat&, const GpuMat&, GpuMat&, bool, ConvolveBuf&) { throw_nogpu(); } #else /* !defined (HAVE_CUDA) */ @@ -1211,36 +1213,65 @@ void cv::gpu::dft(const GpuMat& src, GpuMat& dst, Size dft_size, int flags) } ////////////////////////////////////////////////////////////////////////////// -// crossCorr +// convolve -namespace + +void cv::gpu::ConvolveBuf::create(Size image_size, Size templ_size) { - // Estimates optimal block size - void convolveOptBlockSize(int w, int h, int tw, int th, int& bw, int& bh) - { - int major, minor; - getComputeCapability(getDevice(), major, minor); + result_size = Size(image_size.width - templ_size.width + 1, + image_size.height - templ_size.height + 1); + block_size = estimateBlockSize(result_size, templ_size); - int scale = 40; - int bh_min = 1024; - int bw_min = 1024; + dft_size.width = getOptimalDFTSize(block_size.width + templ_size.width - 1); + dft_size.height = getOptimalDFTSize(block_size.width + templ_size.height - 1); + createContinuous(dft_size, CV_32F, image_block); + createContinuous(dft_size, CV_32F, templ_block); + createContinuous(dft_size, CV_32F, result_data); - // Check whether we use Fermi generation or newer GPU - if (major >= 2) - { - bh_min = 2048; - bw_min = 2048; - } + spect_len = dft_size.height * (dft_size.width / 2 + 1); + createContinuous(1, spect_len, CV_32FC2, image_spect); + createContinuous(1, spect_len, CV_32FC2, templ_spect); + createContinuous(1, spect_len, CV_32FC2, result_spect); - bw = std::max(tw * scale, bw_min); - bh = std::max(th * scale, bh_min); - bw = std::min(bw, w); - bh = std::min(bh, h); - } + block_size.width = std::min(dft_size.width - templ_size.width + 1, result_size.width); + block_size.height = std::min(dft_size.height - templ_size.height + 1, result_size.height); } -void cv::gpu::convolve(const GpuMat& image, const GpuMat& templ, GpuMat& result, bool ccorr) +Size cv::gpu::ConvolveBuf::estimateBlockSize(Size result_size, Size templ_size) +{ + int major, minor; + getComputeCapability(getDevice(), major, minor); + + int scale = 40; + Size bsize_min(1024, 1024); + + // Check whether we use Fermi generation or newer GPU + if (major >= 2) + { + bsize_min.width = 2048; + bsize_min.height = 2048; + } + + Size bsize(std::max(templ_size.width * scale, bsize_min.width), + std::max(templ_size.height * scale, bsize_min.height)); + + bsize.width = std::min(bsize.width, result_size.width); + bsize.height = std::min(bsize.height, result_size.height); + return bsize; +} + + +void cv::gpu::convolve(const GpuMat& image, const GpuMat& templ, GpuMat& result, + bool ccorr) +{ + ConvolveBuf buf; + convolve(image, templ, result, ccorr, buf); +} + + +void cv::gpu::convolve(const GpuMat& image, const GpuMat& templ, GpuMat& result, + bool ccorr, ConvolveBuf& buf) { StaticAssert::check(); StaticAssert::check(); @@ -1248,32 +1279,25 @@ void cv::gpu::convolve(const GpuMat& image, const GpuMat& templ, GpuMat& result, CV_Assert(image.type() == CV_32F); CV_Assert(templ.type() == CV_32F); - result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F); + buf.create(image.size(), templ.size()); + result.create(buf.result_size, CV_32F); - Size block_size; - convolveOptBlockSize(result.cols, result.rows, templ.cols, templ.rows, - block_size.width, block_size.height); + Size& block_size = buf.block_size; + Size& dft_size = buf.dft_size; + int& spect_len = buf.spect_len; - Size dft_size; - dft_size.width = getOptimalDFTSize(block_size.width + templ.cols - 1); - dft_size.height = getOptimalDFTSize(block_size.width + templ.rows - 1); + GpuMat& image_block = buf.image_block; + GpuMat& templ_block = buf.templ_block; + GpuMat& result_data = buf.result_data; - block_size.width = std::min(dft_size.width - templ.cols + 1, result.cols); - block_size.height = std::min(dft_size.height - templ.rows + 1, result.rows); - - int spect_len = dft_size.height * (dft_size.width / 2 + 1); - GpuMat image_spect = createContinuous(1, spect_len, CV_32FC2); - GpuMat templ_spect = createContinuous(1, spect_len, CV_32FC2); - GpuMat result_spect = createContinuous(1, spect_len, CV_32FC2); + GpuMat& image_spect = buf.image_spect; + GpuMat& templ_spect = buf.templ_spect; + GpuMat& result_spect = buf.result_spect; cufftHandle planR2C, planC2R; cufftSafeCall(cufftPlan2d(&planC2R, dft_size.height, dft_size.width, CUFFT_C2R)); cufftSafeCall(cufftPlan2d(&planR2C, dft_size.height, dft_size.width, CUFFT_R2C)); - GpuMat image_block = createContinuous(dft_size, CV_32F); - GpuMat templ_block = createContinuous(dft_size, CV_32F); - GpuMat result_data = createContinuous(dft_size, CV_32F); - GpuMat templ_roi(templ.size(), CV_32F, templ.data, templ.step); copyMakeBorder(templ_roi, templ_block, 0, templ_block.rows - templ_roi.rows, 0, templ_block.cols - templ_roi.cols, 0); @@ -1288,9 +1312,10 @@ void cv::gpu::convolve(const GpuMat& image, const GpuMat& templ, GpuMat& result, { Size image_roi_size(std::min(x + dft_size.width, image.cols) - x, std::min(y + dft_size.height, image.rows) - y); - GpuMat image_roi(image_roi_size, CV_32F, (void*)(image.ptr(y) + x), image.step); - copyMakeBorder(image_roi, image_block, 0, image_block.rows - image_roi.rows, 0, - image_block.cols - image_roi.cols, 0); + GpuMat image_roi(image_roi_size, CV_32F, (void*)(image.ptr(y) + x), + image.step); + copyMakeBorder(image_roi, image_block, 0, image_block.rows - image_roi.rows, + 0, image_block.cols - image_roi.cols, 0); cufftSafeCall(cufftExecR2C(planR2C, image_block.ptr(), image_spect.ptr())); @@ -1301,8 +1326,10 @@ void cv::gpu::convolve(const GpuMat& image, const GpuMat& templ, GpuMat& result, Size result_roi_size(std::min(x + block_size.width, result.cols) - x, std::min(y + block_size.height, result.rows) - y); - GpuMat result_roi(result_roi_size, result.type(), (void*)(result.ptr(y) + x), result.step); - GpuMat result_block(result_roi_size, result_data.type(), result_data.ptr(), result_data.step); + GpuMat result_roi(result_roi_size, result.type(), + (void*)(result.ptr(y) + x), result.step); + GpuMat result_block(result_roi_size, result_data.type(), + result_data.ptr(), result_data.step); result_block.copyTo(result_roi); } }