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42
43#ifndef __OPENCV_CUDALEGACY_HPP__
44#define __OPENCV_CUDALEGACY_HPP__
45
46#include "opencv2/core/cuda.hpp"
47#include "opencv2/cudalegacy/NCV.hpp"
48#include "opencv2/cudalegacy/NPP_staging.hpp"
49#include "opencv2/cudalegacy/NCVPyramid.hpp"
50#include "opencv2/cudalegacy/NCVHaarObjectDetection.hpp"
51#include "opencv2/cudalegacy/NCVBroxOpticalFlow.hpp"
52#include "opencv2/video/background_segm.hpp"
53
54/**
55  @addtogroup cuda
56  @{
57    @defgroup cudalegacy Legacy support
58  @}
59*/
60
61namespace cv { namespace cuda {
62
63//! @addtogroup cudalegacy
64//! @{
65
66//
67// ImagePyramid
68//
69
70class CV_EXPORTS ImagePyramid : public Algorithm
71{
72public:
73    virtual void getLayer(OutputArray outImg, Size outRoi, Stream& stream = Stream::Null()) const = 0;
74};
75
76CV_EXPORTS Ptr<ImagePyramid> createImagePyramid(InputArray img, int nLayers = -1, Stream& stream = Stream::Null());
77
78//
79// GMG
80//
81
82/** @brief Background/Foreground Segmentation Algorithm.
83
84The class discriminates between foreground and background pixels by building and maintaining a model
85of the background. Any pixel which does not fit this model is then deemed to be foreground. The
86class implements algorithm described in @cite Gold2012 .
87 */
88class CV_EXPORTS BackgroundSubtractorGMG : public cv::BackgroundSubtractor
89{
90public:
91    using cv::BackgroundSubtractor::apply;
92    virtual void apply(InputArray image, OutputArray fgmask, double learningRate, Stream& stream) = 0;
93
94    virtual int getMaxFeatures() const = 0;
95    virtual void setMaxFeatures(int maxFeatures) = 0;
96
97    virtual double getDefaultLearningRate() const = 0;
98    virtual void setDefaultLearningRate(double lr) = 0;
99
100    virtual int getNumFrames() const = 0;
101    virtual void setNumFrames(int nframes) = 0;
102
103    virtual int getQuantizationLevels() const = 0;
104    virtual void setQuantizationLevels(int nlevels) = 0;
105
106    virtual double getBackgroundPrior() const = 0;
107    virtual void setBackgroundPrior(double bgprior) = 0;
108
109    virtual int getSmoothingRadius() const = 0;
110    virtual void setSmoothingRadius(int radius) = 0;
111
112    virtual double getDecisionThreshold() const = 0;
113    virtual void setDecisionThreshold(double thresh) = 0;
114
115    virtual bool getUpdateBackgroundModel() const = 0;
116    virtual void setUpdateBackgroundModel(bool update) = 0;
117
118    virtual double getMinVal() const = 0;
119    virtual void setMinVal(double val) = 0;
120
121    virtual double getMaxVal() const = 0;
122    virtual void setMaxVal(double val) = 0;
123};
124
125/** @brief Creates GMG Background Subtractor
126
127@param initializationFrames Number of frames of video to use to initialize histograms.
128@param decisionThreshold Value above which pixel is determined to be FG.
129 */
130CV_EXPORTS Ptr<cuda::BackgroundSubtractorGMG>
131    createBackgroundSubtractorGMG(int initializationFrames = 120, double decisionThreshold = 0.8);
132
133//
134// FGD
135//
136
137/** @brief The class discriminates between foreground and background pixels by building and maintaining a model
138of the background.
139
140Any pixel which does not fit this model is then deemed to be foreground. The class implements
141algorithm described in @cite FGD2003 .
142@sa BackgroundSubtractor
143 */
144class CV_EXPORTS BackgroundSubtractorFGD : public cv::BackgroundSubtractor
145{
146public:
147    /** @brief Returns the output foreground regions calculated by findContours.
148
149    @param foreground_regions Output array (CPU memory).
150     */
151    virtual void getForegroundRegions(OutputArrayOfArrays foreground_regions) = 0;
152};
153
154struct CV_EXPORTS FGDParams
155{
156    int Lc;  //!< Quantized levels per 'color' component. Power of two, typically 32, 64 or 128.
157    int N1c; //!< Number of color vectors used to model normal background color variation at a given pixel.
158    int N2c; //!< Number of color vectors retained at given pixel.  Must be > N1c, typically ~ 5/3 of N1c.
159    //!< Used to allow the first N1c vectors to adapt over time to changing background.
160
161    int Lcc;  //!< Quantized levels per 'color co-occurrence' component.  Power of two, typically 16, 32 or 64.
162    int N1cc; //!< Number of color co-occurrence vectors used to model normal background color variation at a given pixel.
163    int N2cc; //!< Number of color co-occurrence vectors retained at given pixel.  Must be > N1cc, typically ~ 5/3 of N1cc.
164    //!< Used to allow the first N1cc vectors to adapt over time to changing background.
165
166    bool is_obj_without_holes; //!< If TRUE we ignore holes within foreground blobs. Defaults to TRUE.
167    int perform_morphing;     //!< Number of erode-dilate-erode foreground-blob cleanup iterations.
168    //!< These erase one-pixel junk blobs and merge almost-touching blobs. Default value is 1.
169
170    float alpha1; //!< How quickly we forget old background pixel values seen. Typically set to 0.1.
171    float alpha2; //!< "Controls speed of feature learning". Depends on T. Typical value circa 0.005.
172    float alpha3; //!< Alternate to alpha2, used (e.g.) for quicker initial convergence. Typical value 0.1.
173
174    float delta;   //!< Affects color and color co-occurrence quantization, typically set to 2.
175    float T;       //!< A percentage value which determines when new features can be recognized as new background. (Typically 0.9).
176    float minArea; //!< Discard foreground blobs whose bounding box is smaller than this threshold.
177
178    //! default Params
179    FGDParams();
180};
181
182/** @brief Creates FGD Background Subtractor
183
184@param params Algorithm's parameters. See @cite FGD2003 for explanation.
185 */
186CV_EXPORTS Ptr<cuda::BackgroundSubtractorFGD>
187    createBackgroundSubtractorFGD(const FGDParams& params = FGDParams());
188
189//
190// Optical flow
191//
192
193//! Calculates optical flow for 2 images using block matching algorithm */
194CV_EXPORTS void calcOpticalFlowBM(const GpuMat& prev, const GpuMat& curr,
195                                  Size block_size, Size shift_size, Size max_range, bool use_previous,
196                                  GpuMat& velx, GpuMat& vely, GpuMat& buf,
197                                  Stream& stream = Stream::Null());
198
199class CV_EXPORTS FastOpticalFlowBM
200{
201public:
202    void operator ()(const GpuMat& I0, const GpuMat& I1, GpuMat& flowx, GpuMat& flowy, int search_window = 21, int block_window = 7, Stream& s = Stream::Null());
203
204private:
205    GpuMat buffer;
206    GpuMat extended_I0;
207    GpuMat extended_I1;
208};
209
210/** @brief Interpolates frames (images) using provided optical flow (displacement field).
211
212@param frame0 First frame (32-bit floating point images, single channel).
213@param frame1 Second frame. Must have the same type and size as frame0 .
214@param fu Forward horizontal displacement.
215@param fv Forward vertical displacement.
216@param bu Backward horizontal displacement.
217@param bv Backward vertical displacement.
218@param pos New frame position.
219@param newFrame Output image.
220@param buf Temporary buffer, will have width x 6\*height size, CV_32FC1 type and contain 6
221GpuMat: occlusion masks for first frame, occlusion masks for second, interpolated forward
222horizontal flow, interpolated forward vertical flow, interpolated backward horizontal flow,
223interpolated backward vertical flow.
224@param stream Stream for the asynchronous version.
225 */
226CV_EXPORTS void interpolateFrames(const GpuMat& frame0, const GpuMat& frame1,
227                                  const GpuMat& fu, const GpuMat& fv,
228                                  const GpuMat& bu, const GpuMat& bv,
229                                  float pos, GpuMat& newFrame, GpuMat& buf,
230                                  Stream& stream = Stream::Null());
231
232CV_EXPORTS void createOpticalFlowNeedleMap(const GpuMat& u, const GpuMat& v, GpuMat& vertex, GpuMat& colors);
233
234//
235// Labeling
236//
237
238//!performs labeling via graph cuts of a 2D regular 4-connected graph.
239CV_EXPORTS void graphcut(GpuMat& terminals, GpuMat& leftTransp, GpuMat& rightTransp, GpuMat& top, GpuMat& bottom, GpuMat& labels,
240                         GpuMat& buf, Stream& stream = Stream::Null());
241
242//!performs labeling via graph cuts of a 2D regular 8-connected graph.
243CV_EXPORTS void graphcut(GpuMat& terminals, GpuMat& leftTransp, GpuMat& rightTransp, GpuMat& top, GpuMat& topLeft, GpuMat& topRight,
244                         GpuMat& bottom, GpuMat& bottomLeft, GpuMat& bottomRight,
245                         GpuMat& labels,
246                         GpuMat& buf, Stream& stream = Stream::Null());
247
248//! compute mask for Generalized Flood fill componetns labeling.
249CV_EXPORTS void connectivityMask(const GpuMat& image, GpuMat& mask, const cv::Scalar& lo, const cv::Scalar& hi, Stream& stream = Stream::Null());
250
251//! performs connected componnents labeling.
252CV_EXPORTS void labelComponents(const GpuMat& mask, GpuMat& components, int flags = 0, Stream& stream = Stream::Null());
253
254//
255// Calib3d
256//
257
258CV_EXPORTS void transformPoints(const GpuMat& src, const Mat& rvec, const Mat& tvec,
259                                GpuMat& dst, Stream& stream = Stream::Null());
260
261CV_EXPORTS void projectPoints(const GpuMat& src, const Mat& rvec, const Mat& tvec,
262                              const Mat& camera_mat, const Mat& dist_coef, GpuMat& dst,
263                              Stream& stream = Stream::Null());
264
265/** @brief Finds the object pose from 3D-2D point correspondences.
266
267@param object Single-row matrix of object points.
268@param image Single-row matrix of image points.
269@param camera_mat 3x3 matrix of intrinsic camera parameters.
270@param dist_coef Distortion coefficients. See undistortPoints for details.
271@param rvec Output 3D rotation vector.
272@param tvec Output 3D translation vector.
273@param use_extrinsic_guess Flag to indicate that the function must use rvec and tvec as an
274initial transformation guess. It is not supported for now.
275@param num_iters Maximum number of RANSAC iterations.
276@param max_dist Euclidean distance threshold to detect whether point is inlier or not.
277@param min_inlier_count Flag to indicate that the function must stop if greater or equal number
278of inliers is achieved. It is not supported for now.
279@param inliers Output vector of inlier indices.
280 */
281CV_EXPORTS void solvePnPRansac(const Mat& object, const Mat& image, const Mat& camera_mat,
282                               const Mat& dist_coef, Mat& rvec, Mat& tvec, bool use_extrinsic_guess=false,
283                               int num_iters=100, float max_dist=8.0, int min_inlier_count=100,
284                               std::vector<int>* inliers=NULL);
285
286//! @}
287
288}}
289
290#endif /* __OPENCV_CUDALEGACY_HPP__ */
291