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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 
61 namespace cv { namespace cuda {
62 
63 //! @addtogroup cudalegacy
64 //! @{
65 
66 //
67 // ImagePyramid
68 //
69 
70 class CV_EXPORTS ImagePyramid : public Algorithm
71 {
72 public:
73     virtual void getLayer(OutputArray outImg, Size outRoi, Stream& stream = Stream::Null()) const = 0;
74 };
75 
76 CV_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 
84 The class discriminates between foreground and background pixels by building and maintaining a model
85 of the background. Any pixel which does not fit this model is then deemed to be foreground. The
86 class implements algorithm described in @cite Gold2012 .
87  */
88 class CV_EXPORTS BackgroundSubtractorGMG : public cv::BackgroundSubtractor
89 {
90 public:
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  */
130 CV_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
138 of the background.
139 
140 Any pixel which does not fit this model is then deemed to be foreground. The class implements
141 algorithm described in @cite FGD2003 .
142 @sa BackgroundSubtractor
143  */
144 class CV_EXPORTS BackgroundSubtractorFGD : public cv::BackgroundSubtractor
145 {
146 public:
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 
154 struct 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  */
186 CV_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 */
194 CV_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 
199 class CV_EXPORTS FastOpticalFlowBM
200 {
201 public:
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 
204 private:
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
221 GpuMat: occlusion masks for first frame, occlusion masks for second, interpolated forward
222 horizontal flow, interpolated forward vertical flow, interpolated backward horizontal flow,
223 interpolated backward vertical flow.
224 @param stream Stream for the asynchronous version.
225  */
226 CV_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 
232 CV_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.
239 CV_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.
243 CV_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.
249 CV_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.
252 CV_EXPORTS void labelComponents(const GpuMat& mask, GpuMat& components, int flags = 0, Stream& stream = Stream::Null());
253 
254 //
255 // Calib3d
256 //
257 
258 CV_EXPORTS void transformPoints(const GpuMat& src, const Mat& rvec, const Mat& tvec,
259                                 GpuMat& dst, Stream& stream = Stream::Null());
260 
261 CV_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
274 initial 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
278 of inliers is achieved. It is not supported for now.
279 @param inliers Output vector of inlier indices.
280  */
281 CV_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