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https://github.com/opencv/opencv.git
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refactored gpu::matchTemplate (converted it into Algorithm)
This commit is contained in:
Vladislav Vinogradov
@@ -47,7 +47,7 @@ using namespace cv::gpu;
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#if !defined (HAVE_CUDA) || !defined (HAVE_OPENCV_GPUARITHM) || defined (CUDA_DISABLER)
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void cv::gpu::matchTemplate(const GpuMat&, const GpuMat&, GpuMat&, int, Stream&) { throw_no_cuda(); }
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Ptr<gpu::TemplateMatching> cv::gpu::createTemplateMatching(int, int, Size) { throw_no_cuda(); return Ptr<gpu::TemplateMatching>(); }
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#else
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@@ -137,11 +137,8 @@ namespace cv { namespace gpu { namespace cudev
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}
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}}}
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using namespace ::cv::gpu::cudev::match_template;
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namespace
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{
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// Evaluates optimal template's area threshold. If
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// template's area is less than the threshold, we use naive match
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// template version, otherwise FFT-based (if available)
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@@ -149,135 +146,317 @@ namespace
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{
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switch (method)
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{
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case cv::TM_CCORR:
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case TM_CCORR:
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if (depth == CV_32F) return 250;
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if (depth == CV_8U) return 300;
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break;
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case cv::TM_SQDIFF:
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case TM_SQDIFF:
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if (depth == CV_8U) return 300;
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break;
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}
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CV_Error(cv::Error::StsBadArg, "getTemplateThreshold: unsupported match template mode");
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CV_Error(Error::StsBadArg, "unsupported match template mode");
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return 0;
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}
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///////////////////////////////////////////////////////////////
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// CCORR_32F
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void matchTemplate_CCORR_32F(
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const GpuMat& image, const GpuMat& templ, GpuMat& result, MatchTemplateBuf &buf, Stream& stream)
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class Match_CCORR_32F : public TemplateMatching
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{
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result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F);
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if (templ.size().area() < getTemplateThreshold(cv::TM_CCORR, CV_32F))
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public:
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explicit Match_CCORR_32F(Size user_block_size);
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void match(InputArray image, InputArray templ, OutputArray result, Stream& stream = Stream::Null());
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private:
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Ptr<gpu::Convolution> conv_;
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GpuMat result_;
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};
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Match_CCORR_32F::Match_CCORR_32F(Size user_block_size)
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{
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conv_ = gpu::createConvolution(user_block_size);
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}
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void Match_CCORR_32F::match(InputArray _image, InputArray _templ, OutputArray _result, Stream& _stream)
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{
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using namespace cv::gpu::cudev::match_template;
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GpuMat image = _image.getGpuMat();
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GpuMat templ = _templ.getGpuMat();
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CV_Assert( image.depth() == CV_32F );
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CV_Assert( image.type() == templ.type() );
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CV_Assert( image.cols >= templ.cols && image.rows >= templ.rows );
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cudaStream_t stream = StreamAccessor::getStream(_stream);
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_result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32FC1);
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GpuMat result = _result.getGpuMat();
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if (templ.size().area() < getTemplateThreshold(TM_CCORR, CV_32F))
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{
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matchTemplateNaive_CCORR_32F(image, templ, result, image.channels(), StreamAccessor::getStream(stream));
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matchTemplateNaive_CCORR_32F(image, templ, result, image.channels(), stream);
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return;
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}
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Ptr<gpu::Convolution> conv = gpu::createConvolution(buf.user_block_size);
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if (image.channels() == 1)
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{
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conv->convolve(image.reshape(1), templ.reshape(1), result, true, stream);
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conv_->convolve(image.reshape(1), templ.reshape(1), result, true, _stream);
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}
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else
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{
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GpuMat result_;
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conv->convolve(image.reshape(1), templ.reshape(1), result_, true, stream);
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extractFirstChannel_32F(result_, result, image.channels(), StreamAccessor::getStream(stream));
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conv_->convolve(image.reshape(1), templ.reshape(1), result_, true, _stream);
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extractFirstChannel_32F(result_, result, image.channels(), stream);
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}
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}
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///////////////////////////////////////////////////////////////
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// CCORR_8U
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void matchTemplate_CCORR_8U(
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const GpuMat& image, const GpuMat& templ, GpuMat& result, MatchTemplateBuf &buf, Stream& stream)
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class Match_CCORR_8U : public TemplateMatching
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{
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if (templ.size().area() < getTemplateThreshold(cv::TM_CCORR, CV_8U))
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public:
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explicit Match_CCORR_8U(Size user_block_size) : match32F_(user_block_size)
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{
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result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F);
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}
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void match(InputArray image, InputArray templ, OutputArray result, Stream& stream = Stream::Null());
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private:
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GpuMat imagef_, templf_;
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Match_CCORR_32F match32F_;
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};
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void Match_CCORR_8U::match(InputArray _image, InputArray _templ, OutputArray _result, Stream& stream)
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{
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using namespace cv::gpu::cudev::match_template;
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GpuMat image = _image.getGpuMat();
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GpuMat templ = _templ.getGpuMat();
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CV_Assert( image.depth() == CV_8U );
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CV_Assert( image.type() == templ.type() );
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CV_Assert( image.cols >= templ.cols && image.rows >= templ.rows );
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if (templ.size().area() < getTemplateThreshold(TM_CCORR, CV_8U))
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{
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_result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32FC1);
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GpuMat result = _result.getGpuMat();
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matchTemplateNaive_CCORR_8U(image, templ, result, image.channels(), StreamAccessor::getStream(stream));
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return;
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}
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image.convertTo(buf.imagef, CV_32F, stream);
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templ.convertTo(buf.templf, CV_32F, stream);
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image.convertTo(imagef_, CV_32F, stream);
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templ.convertTo(templf_, CV_32F, stream);
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matchTemplate_CCORR_32F(buf.imagef, buf.templf, result, buf, stream);
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match32F_.match(imagef_, templf_, _result, stream);
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}
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///////////////////////////////////////////////////////////////
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// CCORR_NORMED_8U
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void matchTemplate_CCORR_NORMED_8U(
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const GpuMat& image, const GpuMat& templ, GpuMat& result, MatchTemplateBuf &buf, Stream& stream)
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class Match_CCORR_NORMED_8U : public TemplateMatching
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{
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matchTemplate_CCORR_8U(image, templ, result, buf, stream);
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public:
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explicit Match_CCORR_NORMED_8U(Size user_block_size) : match_CCORR_(user_block_size)
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{
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}
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buf.image_sqsums.resize(1);
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gpu::sqrIntegral(image.reshape(1), buf.image_sqsums[0], stream);
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void match(InputArray image, InputArray templ, OutputArray result, Stream& stream = Stream::Null());
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unsigned long long templ_sqsum = (unsigned long long)gpu::sqrSum(templ.reshape(1))[0];
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normalize_8U(templ.cols, templ.rows, buf.image_sqsums[0], templ_sqsum, result, image.channels(), StreamAccessor::getStream(stream));
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private:
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Match_CCORR_8U match_CCORR_;
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GpuMat image_sqsums_;
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GpuMat intBuffer_;
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};
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void Match_CCORR_NORMED_8U::match(InputArray _image, InputArray _templ, OutputArray _result, Stream& stream)
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{
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using namespace cv::gpu::cudev::match_template;
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GpuMat image = _image.getGpuMat();
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GpuMat templ = _templ.getGpuMat();
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CV_Assert( image.depth() == CV_8U );
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CV_Assert( image.type() == templ.type() );
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CV_Assert( image.cols >= templ.cols && image.rows >= templ.rows );
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match_CCORR_.match(image, templ, _result, stream);
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GpuMat result = _result.getGpuMat();
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gpu::sqrIntegral(image.reshape(1), image_sqsums_, intBuffer_, stream);
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unsigned long long templ_sqsum = (unsigned long long) gpu::sqrSum(templ.reshape(1))[0];
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normalize_8U(templ.cols, templ.rows, image_sqsums_, templ_sqsum, result, image.channels(), StreamAccessor::getStream(stream));
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}
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///////////////////////////////////////////////////////////////
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// SQDIFF_32F
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void matchTemplate_SQDIFF_32F(
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const GpuMat& image, const GpuMat& templ, GpuMat& result, MatchTemplateBuf &buf, Stream& stream)
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class Match_SQDIFF_32F : public TemplateMatching
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{
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(void)buf;
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result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F);
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public:
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void match(InputArray image, InputArray templ, OutputArray result, Stream& stream = Stream::Null());
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};
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void Match_SQDIFF_32F::match(InputArray _image, InputArray _templ, OutputArray _result, Stream& stream)
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{
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using namespace cv::gpu::cudev::match_template;
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GpuMat image = _image.getGpuMat();
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GpuMat templ = _templ.getGpuMat();
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CV_Assert( image.depth() == CV_32F );
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CV_Assert( image.type() == templ.type() );
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CV_Assert( image.cols >= templ.cols && image.rows >= templ.rows );
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_result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32FC1);
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GpuMat result = _result.getGpuMat();
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matchTemplateNaive_SQDIFF_32F(image, templ, result, image.channels(), StreamAccessor::getStream(stream));
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}
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///////////////////////////////////////////////////////////////
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// SQDIFF_8U
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void matchTemplate_SQDIFF_8U(
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const GpuMat& image, const GpuMat& templ, GpuMat& result, MatchTemplateBuf &buf, Stream& stream)
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class Match_SQDIFF_8U : public TemplateMatching
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{
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if (templ.size().area() < getTemplateThreshold(cv::TM_SQDIFF, CV_8U))
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public:
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explicit Match_SQDIFF_8U(Size user_block_size) : match_CCORR_(user_block_size)
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{
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result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32F);
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}
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void match(InputArray image, InputArray templ, OutputArray result, Stream& stream = Stream::Null());
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private:
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GpuMat image_sqsums_;
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GpuMat intBuffer_;
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Match_CCORR_8U match_CCORR_;
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};
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void Match_SQDIFF_8U::match(InputArray _image, InputArray _templ, OutputArray _result, Stream& stream)
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{
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using namespace cv::gpu::cudev::match_template;
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GpuMat image = _image.getGpuMat();
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GpuMat templ = _templ.getGpuMat();
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CV_Assert( image.depth() == CV_8U );
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CV_Assert( image.type() == templ.type() );
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CV_Assert( image.cols >= templ.cols && image.rows >= templ.rows );
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if (templ.size().area() < getTemplateThreshold(TM_SQDIFF, CV_8U))
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{
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_result.create(image.rows - templ.rows + 1, image.cols - templ.cols + 1, CV_32FC1);
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GpuMat result = _result.getGpuMat();
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matchTemplateNaive_SQDIFF_8U(image, templ, result, image.channels(), StreamAccessor::getStream(stream));
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return;
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}
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buf.image_sqsums.resize(1);
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gpu::sqrIntegral(image.reshape(1), buf.image_sqsums[0], stream);
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gpu::sqrIntegral(image.reshape(1), image_sqsums_, intBuffer_, stream);
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unsigned long long templ_sqsum = (unsigned long long)gpu::sqrSum(templ.reshape(1))[0];
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unsigned long long templ_sqsum = (unsigned long long) gpu::sqrSum(templ.reshape(1))[0];
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matchTemplate_CCORR_8U(image, templ, result, buf, stream);
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matchTemplatePrepared_SQDIFF_8U(templ.cols, templ.rows, buf.image_sqsums[0], templ_sqsum, result, image.channels(), StreamAccessor::getStream(stream));
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match_CCORR_.match(image, templ, _result, stream);
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GpuMat result = _result.getGpuMat();
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matchTemplatePrepared_SQDIFF_8U(templ.cols, templ.rows, image_sqsums_, templ_sqsum, result, image.channels(), StreamAccessor::getStream(stream));
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}
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///////////////////////////////////////////////////////////////
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// SQDIFF_NORMED_8U
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void matchTemplate_SQDIFF_NORMED_8U(
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const GpuMat& image, const GpuMat& templ, GpuMat& result, MatchTemplateBuf &buf, Stream& stream)
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class Match_SQDIFF_NORMED_8U : public TemplateMatching
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{
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buf.image_sqsums.resize(1);
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gpu::sqrIntegral(image.reshape(1), buf.image_sqsums[0], stream);
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public:
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explicit Match_SQDIFF_NORMED_8U(Size user_block_size) : match_CCORR_(user_block_size)
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{
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}
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unsigned long long templ_sqsum = (unsigned long long)gpu::sqrSum(templ.reshape(1))[0];
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void match(InputArray image, InputArray templ, OutputArray result, Stream& stream = Stream::Null());
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matchTemplate_CCORR_8U(image, templ, result, buf, stream);
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matchTemplatePrepared_SQDIFF_NORMED_8U(templ.cols, templ.rows, buf.image_sqsums[0], templ_sqsum, result, image.channels(), StreamAccessor::getStream(stream));
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private:
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GpuMat image_sqsums_;
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GpuMat intBuffer_;
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Match_CCORR_8U match_CCORR_;
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};
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void Match_SQDIFF_NORMED_8U::match(InputArray _image, InputArray _templ, OutputArray _result, Stream& stream)
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{
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using namespace cv::gpu::cudev::match_template;
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GpuMat image = _image.getGpuMat();
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GpuMat templ = _templ.getGpuMat();
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CV_Assert( image.depth() == CV_8U );
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CV_Assert( image.type() == templ.type() );
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CV_Assert( image.cols >= templ.cols && image.rows >= templ.rows );
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gpu::sqrIntegral(image.reshape(1), image_sqsums_, intBuffer_, stream);
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unsigned long long templ_sqsum = (unsigned long long) gpu::sqrSum(templ.reshape(1))[0];
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match_CCORR_.match(image, templ, _result, stream);
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GpuMat result = _result.getGpuMat();
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matchTemplatePrepared_SQDIFF_NORMED_8U(templ.cols, templ.rows, image_sqsums_, templ_sqsum, result, image.channels(), StreamAccessor::getStream(stream));
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}
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///////////////////////////////////////////////////////////////
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// CCOFF_8U
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void matchTemplate_CCOFF_8U(
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const GpuMat& image, const GpuMat& templ, GpuMat& result, MatchTemplateBuf &buf, Stream& stream)
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class Match_CCOEFF_8U : public TemplateMatching
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{
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matchTemplate_CCORR_8U(image, templ, result, buf, stream);
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public:
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explicit Match_CCOEFF_8U(Size user_block_size) : match_CCORR_(user_block_size)
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{
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}
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void match(InputArray image, InputArray templ, OutputArray result, Stream& stream = Stream::Null());
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private:
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GpuMat intBuffer_;
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std::vector<GpuMat> images_;
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std::vector<GpuMat> image_sums_;
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Match_CCORR_8U match_CCORR_;
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};
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void Match_CCOEFF_8U::match(InputArray _image, InputArray _templ, OutputArray _result, Stream& stream)
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{
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using namespace cv::gpu::cudev::match_template;
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GpuMat image = _image.getGpuMat();
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GpuMat templ = _templ.getGpuMat();
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CV_Assert( image.depth() == CV_8U );
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CV_Assert( image.type() == templ.type() );
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CV_Assert( image.cols >= templ.cols && image.rows >= templ.rows );
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match_CCORR_.match(image, templ, _result, stream);
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GpuMat result = _result.getGpuMat();
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if (image.channels() == 1)
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{
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buf.image_sums.resize(1);
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gpu::integral(image, buf.image_sums[0], stream);
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image_sums_.resize(1);
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gpu::integral(image, image_sums_[0], intBuffer_, stream);
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unsigned int templ_sum = (unsigned int)gpu::sum(templ)[0];
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matchTemplatePrepared_CCOFF_8U(templ.cols, templ.rows, buf.image_sums[0], templ_sum, result, StreamAccessor::getStream(stream));
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unsigned int templ_sum = (unsigned int) gpu::sum(templ)[0];
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matchTemplatePrepared_CCOFF_8U(templ.cols, templ.rows, image_sums_[0], templ_sum, result, StreamAccessor::getStream(stream));
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}
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else
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{
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gpu::split(image, buf.images);
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buf.image_sums.resize(buf.images.size());
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gpu::split(image, images_);
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image_sums_.resize(images_.size());
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for (int i = 0; i < image.channels(); ++i)
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gpu::integral(buf.images[i], buf.image_sums[i], stream);
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gpu::integral(images_[i], image_sums_[i], intBuffer_, stream);
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Scalar templ_sum = gpu::sum(templ);
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@@ -285,60 +464,91 @@ namespace
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{
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case 2:
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matchTemplatePrepared_CCOFF_8UC2(
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templ.cols, templ.rows, buf.image_sums[0], buf.image_sums[1],
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(unsigned int)templ_sum[0], (unsigned int)templ_sum[1],
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templ.cols, templ.rows, image_sums_[0], image_sums_[1],
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(unsigned int) templ_sum[0], (unsigned int) templ_sum[1],
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result, StreamAccessor::getStream(stream));
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break;
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case 3:
|
||||
matchTemplatePrepared_CCOFF_8UC3(
|
||||
templ.cols, templ.rows, buf.image_sums[0], buf.image_sums[1], buf.image_sums[2],
|
||||
(unsigned int)templ_sum[0], (unsigned int)templ_sum[1], (unsigned int)templ_sum[2],
|
||||
templ.cols, templ.rows, image_sums_[0], image_sums_[1], image_sums_[2],
|
||||
(unsigned int) templ_sum[0], (unsigned int) templ_sum[1], (unsigned int) templ_sum[2],
|
||||
result, StreamAccessor::getStream(stream));
|
||||
break;
|
||||
case 4:
|
||||
matchTemplatePrepared_CCOFF_8UC4(
|
||||
templ.cols, templ.rows, buf.image_sums[0], buf.image_sums[1], buf.image_sums[2], buf.image_sums[3],
|
||||
(unsigned int)templ_sum[0], (unsigned int)templ_sum[1], (unsigned int)templ_sum[2],
|
||||
(unsigned int)templ_sum[3], result, StreamAccessor::getStream(stream));
|
||||
templ.cols, templ.rows, image_sums_[0], image_sums_[1], image_sums_[2], image_sums_[3],
|
||||
(unsigned int) templ_sum[0], (unsigned int) templ_sum[1], (unsigned int) templ_sum[2], (unsigned int) templ_sum[3],
|
||||
result, StreamAccessor::getStream(stream));
|
||||
break;
|
||||
default:
|
||||
CV_Error(cv::Error::StsBadArg, "matchTemplate: unsupported number of channels");
|
||||
CV_Error(Error::StsBadArg, "unsupported number of channels");
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
///////////////////////////////////////////////////////////////
|
||||
// CCOFF_NORMED_8U
|
||||
|
||||
void matchTemplate_CCOFF_NORMED_8U(
|
||||
const GpuMat& image, const GpuMat& templ, GpuMat& result, MatchTemplateBuf &buf, Stream& stream)
|
||||
class Match_CCOEFF_NORMED_8U : public TemplateMatching
|
||||
{
|
||||
image.convertTo(buf.imagef, CV_32F, stream);
|
||||
templ.convertTo(buf.templf, CV_32F, stream);
|
||||
public:
|
||||
explicit Match_CCOEFF_NORMED_8U(Size user_block_size) : match_CCORR_32F_(user_block_size)
|
||||
{
|
||||
}
|
||||
|
||||
matchTemplate_CCORR_32F(buf.imagef, buf.templf, result, buf, stream);
|
||||
void match(InputArray image, InputArray templ, OutputArray result, Stream& stream = Stream::Null());
|
||||
|
||||
private:
|
||||
GpuMat imagef_, templf_;
|
||||
Match_CCORR_32F match_CCORR_32F_;
|
||||
GpuMat intBuffer_;
|
||||
std::vector<GpuMat> images_;
|
||||
std::vector<GpuMat> image_sums_;
|
||||
std::vector<GpuMat> image_sqsums_;
|
||||
};
|
||||
|
||||
void Match_CCOEFF_NORMED_8U::match(InputArray _image, InputArray _templ, OutputArray _result, Stream& stream)
|
||||
{
|
||||
using namespace cv::gpu::cudev::match_template;
|
||||
|
||||
GpuMat image = _image.getGpuMat();
|
||||
GpuMat templ = _templ.getGpuMat();
|
||||
|
||||
CV_Assert( image.depth() == CV_8U );
|
||||
CV_Assert( image.type() == templ.type() );
|
||||
CV_Assert( image.cols >= templ.cols && image.rows >= templ.rows );
|
||||
|
||||
image.convertTo(imagef_, CV_32F, stream);
|
||||
templ.convertTo(templf_, CV_32F, stream);
|
||||
|
||||
match_CCORR_32F_.match(imagef_, templf_, _result, stream);
|
||||
GpuMat result = _result.getGpuMat();
|
||||
|
||||
if (image.channels() == 1)
|
||||
{
|
||||
buf.image_sums.resize(1);
|
||||
gpu::integral(image, buf.image_sums[0], stream);
|
||||
buf.image_sqsums.resize(1);
|
||||
gpu::sqrIntegral(image, buf.image_sqsums[0], stream);
|
||||
image_sums_.resize(1);
|
||||
gpu::integral(image, image_sums_[0], intBuffer_, stream);
|
||||
|
||||
unsigned int templ_sum = (unsigned int)gpu::sum(templ)[0];
|
||||
unsigned long long templ_sqsum = (unsigned long long)gpu::sqrSum(templ)[0];
|
||||
image_sqsums_.resize(1);
|
||||
gpu::sqrIntegral(image, image_sqsums_[0], intBuffer_, stream);
|
||||
|
||||
unsigned int templ_sum = (unsigned int) gpu::sum(templ)[0];
|
||||
unsigned long long templ_sqsum = (unsigned long long) gpu::sqrSum(templ)[0];
|
||||
|
||||
matchTemplatePrepared_CCOFF_NORMED_8U(
|
||||
templ.cols, templ.rows, buf.image_sums[0], buf.image_sqsums[0],
|
||||
templ.cols, templ.rows, image_sums_[0], image_sqsums_[0],
|
||||
templ_sum, templ_sqsum, result, StreamAccessor::getStream(stream));
|
||||
}
|
||||
else
|
||||
{
|
||||
gpu::split(image, buf.images);
|
||||
buf.image_sums.resize(buf.images.size());
|
||||
buf.image_sqsums.resize(buf.images.size());
|
||||
gpu::split(image, images_);
|
||||
|
||||
image_sums_.resize(images_.size());
|
||||
image_sqsums_.resize(images_.size());
|
||||
for (int i = 0; i < image.channels(); ++i)
|
||||
{
|
||||
gpu::integral(buf.images[i], buf.image_sums[i], stream);
|
||||
gpu::sqrIntegral(buf.images[i], buf.image_sqsums[i], stream);
|
||||
gpu::integral(images_[i], image_sums_[i], intBuffer_, stream);
|
||||
gpu::sqrIntegral(images_[i], image_sqsums_[i], intBuffer_, stream);
|
||||
}
|
||||
|
||||
Scalar templ_sum = gpu::sum(templ);
|
||||
@@ -349,8 +559,8 @@ namespace
|
||||
case 2:
|
||||
matchTemplatePrepared_CCOFF_NORMED_8UC2(
|
||||
templ.cols, templ.rows,
|
||||
buf.image_sums[0], buf.image_sqsums[0],
|
||||
buf.image_sums[1], buf.image_sqsums[1],
|
||||
image_sums_[0], image_sqsums_[0],
|
||||
image_sums_[1], image_sqsums_[1],
|
||||
(unsigned int)templ_sum[0], (unsigned long long)templ_sqsum[0],
|
||||
(unsigned int)templ_sum[1], (unsigned long long)templ_sqsum[1],
|
||||
result, StreamAccessor::getStream(stream));
|
||||
@@ -358,9 +568,9 @@ namespace
|
||||
case 3:
|
||||
matchTemplatePrepared_CCOFF_NORMED_8UC3(
|
||||
templ.cols, templ.rows,
|
||||
buf.image_sums[0], buf.image_sqsums[0],
|
||||
buf.image_sums[1], buf.image_sqsums[1],
|
||||
buf.image_sums[2], buf.image_sqsums[2],
|
||||
image_sums_[0], image_sqsums_[0],
|
||||
image_sums_[1], image_sqsums_[1],
|
||||
image_sums_[2], image_sqsums_[2],
|
||||
(unsigned int)templ_sum[0], (unsigned long long)templ_sqsum[0],
|
||||
(unsigned int)templ_sum[1], (unsigned long long)templ_sqsum[1],
|
||||
(unsigned int)templ_sum[2], (unsigned long long)templ_sqsum[2],
|
||||
@@ -369,10 +579,10 @@ namespace
|
||||
case 4:
|
||||
matchTemplatePrepared_CCOFF_NORMED_8UC4(
|
||||
templ.cols, templ.rows,
|
||||
buf.image_sums[0], buf.image_sqsums[0],
|
||||
buf.image_sums[1], buf.image_sqsums[1],
|
||||
buf.image_sums[2], buf.image_sqsums[2],
|
||||
buf.image_sums[3], buf.image_sqsums[3],
|
||||
image_sums_[0], image_sqsums_[0],
|
||||
image_sums_[1], image_sqsums_[1],
|
||||
image_sums_[2], image_sqsums_[2],
|
||||
image_sums_[3], image_sqsums_[3],
|
||||
(unsigned int)templ_sum[0], (unsigned long long)templ_sqsum[0],
|
||||
(unsigned int)templ_sum[1], (unsigned long long)templ_sqsum[1],
|
||||
(unsigned int)templ_sum[2], (unsigned long long)templ_sqsum[2],
|
||||
@@ -380,46 +590,60 @@ namespace
|
||||
result, StreamAccessor::getStream(stream));
|
||||
break;
|
||||
default:
|
||||
CV_Error(cv::Error::StsBadArg, "matchTemplate: unsupported number of channels");
|
||||
CV_Error(Error::StsBadArg, "unsupported number of channels");
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
void cv::gpu::matchTemplate(const GpuMat& image, const GpuMat& templ, GpuMat& result, int method, Stream& stream)
|
||||
Ptr<gpu::TemplateMatching> cv::gpu::createTemplateMatching(int srcType, int method, Size user_block_size)
|
||||
{
|
||||
MatchTemplateBuf buf;
|
||||
matchTemplate(image, templ, result, method, buf, stream);
|
||||
}
|
||||
const int sdepth = CV_MAT_DEPTH(srcType);
|
||||
|
||||
CV_Assert( sdepth == CV_8U || sdepth == CV_32F );
|
||||
|
||||
void cv::gpu::matchTemplate(
|
||||
const GpuMat& image, const GpuMat& templ, GpuMat& result, int method,
|
||||
MatchTemplateBuf &buf, Stream& stream)
|
||||
{
|
||||
CV_Assert(image.type() == templ.type());
|
||||
CV_Assert(image.cols >= templ.cols && image.rows >= templ.rows);
|
||||
|
||||
typedef void (*Caller)(const GpuMat&, const GpuMat&, GpuMat&, MatchTemplateBuf&, Stream& stream);
|
||||
|
||||
static const Caller callers8U[] = { ::matchTemplate_SQDIFF_8U, ::matchTemplate_SQDIFF_NORMED_8U,
|
||||
::matchTemplate_CCORR_8U, ::matchTemplate_CCORR_NORMED_8U,
|
||||
::matchTemplate_CCOFF_8U, ::matchTemplate_CCOFF_NORMED_8U };
|
||||
static const Caller callers32F[] = { ::matchTemplate_SQDIFF_32F, 0,
|
||||
::matchTemplate_CCORR_32F, 0, 0, 0 };
|
||||
|
||||
const Caller* callers = 0;
|
||||
switch (image.depth())
|
||||
if (sdepth == CV_32F)
|
||||
{
|
||||
case CV_8U: callers = callers8U; break;
|
||||
case CV_32F: callers = callers32F; break;
|
||||
default: CV_Error(cv::Error::StsBadArg, "matchTemplate: unsupported data type");
|
||||
}
|
||||
switch (method)
|
||||
{
|
||||
case TM_SQDIFF:
|
||||
return new Match_SQDIFF_32F;
|
||||
|
||||
Caller caller = callers[method];
|
||||
CV_Assert(caller);
|
||||
caller(image, templ, result, buf, stream);
|
||||
case TM_CCORR:
|
||||
return new Match_CCORR_32F(user_block_size);
|
||||
|
||||
default:
|
||||
CV_Error( Error::StsBadFlag, "Unsopported method" );
|
||||
return Ptr<gpu::TemplateMatching>();
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
switch (method)
|
||||
{
|
||||
case TM_SQDIFF:
|
||||
return new Match_SQDIFF_8U(user_block_size);
|
||||
|
||||
case TM_SQDIFF_NORMED:
|
||||
return new Match_SQDIFF_NORMED_8U(user_block_size);
|
||||
|
||||
case TM_CCORR:
|
||||
return new Match_CCORR_8U(user_block_size);
|
||||
|
||||
case TM_CCORR_NORMED:
|
||||
return new Match_CCORR_NORMED_8U(user_block_size);
|
||||
|
||||
case TM_CCOEFF:
|
||||
return new Match_CCOEFF_8U(user_block_size);
|
||||
|
||||
case TM_CCOEFF_NORMED:
|
||||
return new Match_CCOEFF_NORMED_8U(user_block_size);
|
||||
|
||||
default:
|
||||
CV_Error( Error::StsBadFlag, "Unsopported method" );
|
||||
return Ptr<gpu::TemplateMatching>();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
#endif
|
||||
|
||||
Reference in New Issue
Block a user