ocl.hpp
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/*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
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//M*/
#ifndef __OPENCV_NONFREE_OCL_HPP__
#define __OPENCV_NONFREE_OCL_HPP__
#include "opencv2/ocl/ocl.hpp"
namespace cv
{
namespace ocl
{
//! Speeded up robust features, port from GPU module.
////////////////////////////////// SURF //////////////////////////////////////////
class CV_EXPORTS SURF_OCL : public cv::Feature2D
{
public:
enum KeypointLayout
{
X_ROW = 0,
Y_ROW,
LAPLACIAN_ROW,
OCTAVE_ROW,
SIZE_ROW,
ANGLE_ROW,
HESSIAN_ROW,
ROWS_COUNT
};
//! the default constructor
SURF_OCL();
//! the full constructor taking all the necessary parameters
explicit SURF_OCL(double _hessianThreshold, int _nOctaves = 4,
int _nOctaveLayers = 2, bool _extended = true, float _keypointsRatio = 0.01f, bool _upright = false);
//! returns the descriptor size in float's (64 or 128)
int descriptorSize() const;
int descriptorType() const;
//! upload host keypoints to device memory
void uploadKeypoints(const vector<cv::KeyPoint> &keypoints, oclMat &keypointsocl);
//! download keypoints from device to host memory
void downloadKeypoints(const oclMat &keypointsocl, vector<KeyPoint> &keypoints);
//! download descriptors from device to host memory
void downloadDescriptors(const oclMat &descriptorsocl, vector<float> &descriptors);
//! finds the keypoints using fast hessian detector used in SURF
//! supports CV_8UC1 images
//! keypoints will have nFeature cols and 6 rows
//! keypoints.ptr<float>(X_ROW)[i] will contain x coordinate of i'th feature
//! keypoints.ptr<float>(Y_ROW)[i] will contain y coordinate of i'th feature
//! keypoints.ptr<float>(LAPLACIAN_ROW)[i] will contain laplacian sign of i'th feature
//! keypoints.ptr<float>(OCTAVE_ROW)[i] will contain octave of i'th feature
//! keypoints.ptr<float>(SIZE_ROW)[i] will contain size of i'th feature
//! keypoints.ptr<float>(ANGLE_ROW)[i] will contain orientation of i'th feature
//! keypoints.ptr<float>(HESSIAN_ROW)[i] will contain response of i'th feature
void operator()(const oclMat &img, const oclMat &mask, oclMat &keypoints);
//! finds the keypoints and computes their descriptors.
//! Optionally it can compute descriptors for the user-provided keypoints and recompute keypoints direction
void operator()(const oclMat &img, const oclMat &mask, oclMat &keypoints, oclMat &descriptors,
bool useProvidedKeypoints = false);
void operator()(const oclMat &img, const oclMat &mask, std::vector<KeyPoint> &keypoints);
void operator()(const oclMat &img, const oclMat &mask, std::vector<KeyPoint> &keypoints, oclMat &descriptors,
bool useProvidedKeypoints = false);
void operator()(const oclMat &img, const oclMat &mask, std::vector<KeyPoint> &keypoints, std::vector<float> &descriptors,
bool useProvidedKeypoints = false);
//! finds the keypoints using fast hessian detector used in SURF
void operator()(InputArray img, InputArray mask,
CV_OUT vector<KeyPoint>& keypoints) const;
//! finds the keypoints and computes their descriptors. Optionally it can compute descriptors for the user-provided keypoints
void operator()(InputArray img, InputArray mask,
CV_OUT vector<KeyPoint>& keypoints,
OutputArray descriptors,
bool useProvidedKeypoints=false) const;
AlgorithmInfo* info() const;
void releaseMemory();
// SURF parameters
float hessianThreshold;
int nOctaves;
int nOctaveLayers;
bool extended;
bool upright;
//! max keypoints = min(keypointsRatio * img.size().area(), 65535)
float keypointsRatio;
oclMat sum, mask1, maskSum, intBuffer;
oclMat det, trace;
oclMat maxPosBuffer;
protected:
void detectImpl( const Mat& image, vector<KeyPoint>& keypoints, const Mat& mask) const;
void computeImpl( const Mat& image, vector<KeyPoint>& keypoints, Mat& descriptors) const;
};
}
}
#endif //__OPENCV_NONFREE_OCL_HPP__