291 lines
12 KiB
C++
291 lines
12 KiB
C++
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#ifndef OPENCV_CUDALEGACY_HPP
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#define OPENCV_CUDALEGACY_HPP
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#include "opencv2/core/cuda.hpp"
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#include "opencv2/cudalegacy/NCV.hpp"
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#include "opencv2/cudalegacy/NPP_staging.hpp"
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#include "opencv2/cudalegacy/NCVPyramid.hpp"
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#include "opencv2/cudalegacy/NCVHaarObjectDetection.hpp"
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#include "opencv2/cudalegacy/NCVBroxOpticalFlow.hpp"
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#include "opencv2/video/background_segm.hpp"
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/**
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@addtogroup cuda
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@{
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@defgroup cudalegacy Legacy support
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@}
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*/
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namespace cv { namespace cuda {
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//! @addtogroup cudalegacy
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//! @{
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//
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// ImagePyramid
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//
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class CV_EXPORTS ImagePyramid : public Algorithm
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{
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public:
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virtual void getLayer(OutputArray outImg, Size outRoi, Stream& stream = Stream::Null()) const = 0;
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};
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CV_EXPORTS Ptr<ImagePyramid> createImagePyramid(InputArray img, int nLayers = -1, Stream& stream = Stream::Null());
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//
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// GMG
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//
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/** @brief Background/Foreground Segmentation Algorithm.
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The class discriminates between foreground and background pixels by building and maintaining a model
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of the background. Any pixel which does not fit this model is then deemed to be foreground. The
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class implements algorithm described in @cite Gold2012 .
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*/
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class CV_EXPORTS BackgroundSubtractorGMG : public cv::BackgroundSubtractor
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{
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public:
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using cv::BackgroundSubtractor::apply;
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virtual void apply(InputArray image, OutputArray fgmask, double learningRate, Stream& stream) = 0;
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virtual int getMaxFeatures() const = 0;
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virtual void setMaxFeatures(int maxFeatures) = 0;
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virtual double getDefaultLearningRate() const = 0;
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virtual void setDefaultLearningRate(double lr) = 0;
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virtual int getNumFrames() const = 0;
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virtual void setNumFrames(int nframes) = 0;
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virtual int getQuantizationLevels() const = 0;
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virtual void setQuantizationLevels(int nlevels) = 0;
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virtual double getBackgroundPrior() const = 0;
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virtual void setBackgroundPrior(double bgprior) = 0;
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virtual int getSmoothingRadius() const = 0;
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virtual void setSmoothingRadius(int radius) = 0;
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virtual double getDecisionThreshold() const = 0;
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virtual void setDecisionThreshold(double thresh) = 0;
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virtual bool getUpdateBackgroundModel() const = 0;
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virtual void setUpdateBackgroundModel(bool update) = 0;
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virtual double getMinVal() const = 0;
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virtual void setMinVal(double val) = 0;
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virtual double getMaxVal() const = 0;
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virtual void setMaxVal(double val) = 0;
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};
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/** @brief Creates GMG Background Subtractor
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@param initializationFrames Number of frames of video to use to initialize histograms.
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@param decisionThreshold Value above which pixel is determined to be FG.
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*/
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CV_EXPORTS Ptr<cuda::BackgroundSubtractorGMG>
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createBackgroundSubtractorGMG(int initializationFrames = 120, double decisionThreshold = 0.8);
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//
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// FGD
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//
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/** @brief The class discriminates between foreground and background pixels by building and maintaining a model
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of the background.
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Any pixel which does not fit this model is then deemed to be foreground. The class implements
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algorithm described in @cite FGD2003 .
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@sa BackgroundSubtractor
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*/
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class CV_EXPORTS BackgroundSubtractorFGD : public cv::BackgroundSubtractor
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{
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public:
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/** @brief Returns the output foreground regions calculated by findContours.
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@param foreground_regions Output array (CPU memory).
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*/
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virtual void getForegroundRegions(OutputArrayOfArrays foreground_regions) = 0;
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};
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struct CV_EXPORTS FGDParams
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{
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int Lc; //!< Quantized levels per 'color' component. Power of two, typically 32, 64 or 128.
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int N1c; //!< Number of color vectors used to model normal background color variation at a given pixel.
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int N2c; //!< Number of color vectors retained at given pixel. Must be > N1c, typically ~ 5/3 of N1c.
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//!< Used to allow the first N1c vectors to adapt over time to changing background.
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int Lcc; //!< Quantized levels per 'color co-occurrence' component. Power of two, typically 16, 32 or 64.
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int N1cc; //!< Number of color co-occurrence vectors used to model normal background color variation at a given pixel.
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int N2cc; //!< Number of color co-occurrence vectors retained at given pixel. Must be > N1cc, typically ~ 5/3 of N1cc.
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//!< Used to allow the first N1cc vectors to adapt over time to changing background.
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bool is_obj_without_holes; //!< If TRUE we ignore holes within foreground blobs. Defaults to TRUE.
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int perform_morphing; //!< Number of erode-dilate-erode foreground-blob cleanup iterations.
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//!< These erase one-pixel junk blobs and merge almost-touching blobs. Default value is 1.
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float alpha1; //!< How quickly we forget old background pixel values seen. Typically set to 0.1.
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float alpha2; //!< "Controls speed of feature learning". Depends on T. Typical value circa 0.005.
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float alpha3; //!< Alternate to alpha2, used (e.g.) for quicker initial convergence. Typical value 0.1.
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float delta; //!< Affects color and color co-occurrence quantization, typically set to 2.
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float T; //!< A percentage value which determines when new features can be recognized as new background. (Typically 0.9).
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float minArea; //!< Discard foreground blobs whose bounding box is smaller than this threshold.
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//! default Params
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FGDParams();
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};
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/** @brief Creates FGD Background Subtractor
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@param params Algorithm's parameters. See @cite FGD2003 for explanation.
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*/
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CV_EXPORTS Ptr<cuda::BackgroundSubtractorFGD>
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createBackgroundSubtractorFGD(const FGDParams& params = FGDParams());
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//
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// Optical flow
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//
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//! Calculates optical flow for 2 images using block matching algorithm */
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CV_EXPORTS void calcOpticalFlowBM(const GpuMat& prev, const GpuMat& curr,
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Size block_size, Size shift_size, Size max_range, bool use_previous,
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GpuMat& velx, GpuMat& vely, GpuMat& buf,
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Stream& stream = Stream::Null());
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class CV_EXPORTS FastOpticalFlowBM
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{
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public:
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void operator ()(const GpuMat& I0, const GpuMat& I1, GpuMat& flowx, GpuMat& flowy, int search_window = 21, int block_window = 7, Stream& s = Stream::Null());
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private:
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GpuMat buffer;
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GpuMat extended_I0;
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GpuMat extended_I1;
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};
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/** @brief Interpolates frames (images) using provided optical flow (displacement field).
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@param frame0 First frame (32-bit floating point images, single channel).
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@param frame1 Second frame. Must have the same type and size as frame0 .
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@param fu Forward horizontal displacement.
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@param fv Forward vertical displacement.
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@param bu Backward horizontal displacement.
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@param bv Backward vertical displacement.
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@param pos New frame position.
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@param newFrame Output image.
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@param buf Temporary buffer, will have width x 6\*height size, CV_32FC1 type and contain 6
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GpuMat: occlusion masks for first frame, occlusion masks for second, interpolated forward
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horizontal flow, interpolated forward vertical flow, interpolated backward horizontal flow,
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interpolated backward vertical flow.
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@param stream Stream for the asynchronous version.
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*/
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CV_EXPORTS void interpolateFrames(const GpuMat& frame0, const GpuMat& frame1,
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const GpuMat& fu, const GpuMat& fv,
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const GpuMat& bu, const GpuMat& bv,
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float pos, GpuMat& newFrame, GpuMat& buf,
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Stream& stream = Stream::Null());
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CV_EXPORTS void createOpticalFlowNeedleMap(const GpuMat& u, const GpuMat& v, GpuMat& vertex, GpuMat& colors);
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//
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// Labeling
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//
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//!performs labeling via graph cuts of a 2D regular 4-connected graph.
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CV_EXPORTS void graphcut(GpuMat& terminals, GpuMat& leftTransp, GpuMat& rightTransp, GpuMat& top, GpuMat& bottom, GpuMat& labels,
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GpuMat& buf, Stream& stream = Stream::Null());
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//!performs labeling via graph cuts of a 2D regular 8-connected graph.
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CV_EXPORTS void graphcut(GpuMat& terminals, GpuMat& leftTransp, GpuMat& rightTransp, GpuMat& top, GpuMat& topLeft, GpuMat& topRight,
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GpuMat& bottom, GpuMat& bottomLeft, GpuMat& bottomRight,
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GpuMat& labels,
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GpuMat& buf, Stream& stream = Stream::Null());
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//! compute mask for Generalized Flood fill componetns labeling.
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CV_EXPORTS void connectivityMask(const GpuMat& image, GpuMat& mask, const cv::Scalar& lo, const cv::Scalar& hi, Stream& stream = Stream::Null());
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//! performs connected componnents labeling.
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CV_EXPORTS void labelComponents(const GpuMat& mask, GpuMat& components, int flags = 0, Stream& stream = Stream::Null());
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//
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// Calib3d
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//
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CV_EXPORTS void transformPoints(const GpuMat& src, const Mat& rvec, const Mat& tvec,
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GpuMat& dst, Stream& stream = Stream::Null());
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CV_EXPORTS void projectPoints(const GpuMat& src, const Mat& rvec, const Mat& tvec,
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const Mat& camera_mat, const Mat& dist_coef, GpuMat& dst,
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Stream& stream = Stream::Null());
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/** @brief Finds the object pose from 3D-2D point correspondences.
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@param object Single-row matrix of object points.
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@param image Single-row matrix of image points.
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@param camera_mat 3x3 matrix of intrinsic camera parameters.
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@param dist_coef Distortion coefficients. See undistortPoints for details.
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@param rvec Output 3D rotation vector.
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@param tvec Output 3D translation vector.
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@param use_extrinsic_guess Flag to indicate that the function must use rvec and tvec as an
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initial transformation guess. It is not supported for now.
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@param num_iters Maximum number of RANSAC iterations.
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@param max_dist Euclidean distance threshold to detect whether point is inlier or not.
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@param min_inlier_count Flag to indicate that the function must stop if greater or equal number
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of inliers is achieved. It is not supported for now.
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@param inliers Output vector of inlier indices.
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*/
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CV_EXPORTS void solvePnPRansac(const Mat& object, const Mat& image, const Mat& camera_mat,
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const Mat& dist_coef, Mat& rvec, Mat& tvec, bool use_extrinsic_guess=false,
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int num_iters=100, float max_dist=8.0, int min_inlier_count=100,
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std::vector<int>* inliers=NULL);
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//! @}
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}}
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#endif /* OPENCV_CUDALEGACY_HPP */
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