Merge pull request #1014 from jet47:gpustereo-refactoring

modules/gpustereo/include/opencv2/gpustereo.hpp

@@ -48,199 +48,145 @@
 #endif
 
 #include "opencv2/core/gpu.hpp"
+#include "opencv2/calib3d.hpp"
 
 namespace cv { namespace gpu {
 
-class CV_EXPORTS StereoBM_GPU
+/////////////////////////////////////////
+// StereoBM
+
+class CV_EXPORTS StereoBM : public cv::StereoBM
 {
 public:
-    enum { BASIC_PRESET = 0, PREFILTER_XSOBEL = 1 };
-
-    enum { DEFAULT_NDISP = 64, DEFAULT_WINSZ = 19 };
-
-    //! the default constructor
-    StereoBM_GPU();
-    //! the full constructor taking the camera-specific preset, number of disparities and the SAD window size. ndisparities must be multiple of 8.
-    StereoBM_GPU(int preset, int ndisparities = DEFAULT_NDISP, int winSize = DEFAULT_WINSZ);
-
-    //! the stereo correspondence operator. Finds the disparity for the specified rectified stereo pair
-    //! Output disparity has CV_8U type.
-    void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream = Stream::Null());
+    using cv::StereoBM::compute;
 
-    //! Some heuristics that tries to estmate
-    // if current GPU will be faster than CPU in this algorithm.
-    // It queries current active device.
-    static bool checkIfGpuCallReasonable();
-
-    int preset;
-    int ndisp;
-    int winSize;
+    virtual void compute(InputArray left, InputArray right, OutputArray disparity, Stream& stream) = 0;
+};
 
-    // If avergeTexThreshold  == 0 => post procesing is disabled
-    // If avergeTexThreshold != 0 then disparity is set 0 in each point (x,y) where for left image
-    // SumOfHorizontalGradiensInWindow(x, y, winSize) < (winSize * winSize) * avergeTexThreshold
-    // i.e. input left image is low textured.
-    float avergeTexThreshold;
+CV_EXPORTS Ptr<gpu::StereoBM> createStereoBM(int numDisparities = 64, int blockSize = 19);
 
-private:
-    GpuMat minSSD, leBuf, riBuf;
-};
+/////////////////////////////////////////
+// StereoBeliefPropagation
 
-// "Efficient Belief Propagation for Early Vision"
-// P.Felzenszwalb
-class CV_EXPORTS StereoBeliefPropagation
+//! "Efficient Belief Propagation for Early Vision" P.Felzenszwalb
+class CV_EXPORTS StereoBeliefPropagation : public cv::StereoMatcher
 {
 public:
-    enum { DEFAULT_NDISP  = 64 };
-    enum { DEFAULT_ITERS  = 5  };
-    enum { DEFAULT_LEVELS = 5  };
-
-    static void estimateRecommendedParams(int width, int height, int& ndisp, int& iters, int& levels);
-
-    //! the default constructor
-    explicit StereoBeliefPropagation(int ndisp  = DEFAULT_NDISP,
-                                     int iters  = DEFAULT_ITERS,
-                                     int levels = DEFAULT_LEVELS,
-                                     int msg_type = CV_32F);
-
-    //! the full constructor taking the number of disparities, number of BP iterations on each level,
-    //! number of levels, truncation of data cost, data weight,
-    //! truncation of discontinuity cost and discontinuity single jump
-    //! DataTerm = data_weight * min(fabs(I2-I1), max_data_term)
-    //! DiscTerm = min(disc_single_jump * fabs(f1-f2), max_disc_term)
-    //! please see paper for more details
-    StereoBeliefPropagation(int ndisp, int iters, int levels,
-        float max_data_term, float data_weight,
-        float max_disc_term, float disc_single_jump,
-        int msg_type = CV_32F);
-
-    //! the stereo correspondence operator. Finds the disparity for the specified rectified stereo pair,
-    //! if disparity is empty output type will be CV_16S else output type will be disparity.type().
-    void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream = Stream::Null());
+    using cv::StereoMatcher::compute;
 
+    virtual void compute(InputArray left, InputArray right, OutputArray disparity, Stream& stream) = 0;
 
     //! version for user specified data term
-    void operator()(const GpuMat& data, GpuMat& disparity, Stream& stream = Stream::Null());
+    virtual void compute(InputArray data, OutputArray disparity, Stream& stream = Stream::Null()) = 0;
 
-    int ndisp;
+    //! number of BP iterations on each level
+    virtual int getNumIters() const = 0;
+    virtual void setNumIters(int iters) = 0;
 
-    int iters;
-    int levels;
+    //! number of levels
+    virtual int getNumLevels() const = 0;
+    virtual void setNumLevels(int levels) = 0;
 
-    float max_data_term;
-    float data_weight;
-    float max_disc_term;
-    float disc_single_jump;
+    //! truncation of data cost
+    virtual double getMaxDataTerm() const = 0;
+    virtual void setMaxDataTerm(double max_data_term) = 0;
 
-    int msg_type;
-private:
-    GpuMat u, d, l, r, u2, d2, l2, r2;
-    std::vector<GpuMat> datas;
-    GpuMat out;
-};
+    //! data weight
+    virtual double getDataWeight() const = 0;
+    virtual void setDataWeight(double data_weight) = 0;
 
-// "A Constant-Space Belief Propagation Algorithm for Stereo Matching"
-// Qingxiong Yang, Liang Wang, Narendra Ahuja
-// http://vision.ai.uiuc.edu/~qyang6/
-class CV_EXPORTS StereoConstantSpaceBP
-{
-public:
-    enum { DEFAULT_NDISP    = 128 };
-    enum { DEFAULT_ITERS    = 8   };
-    enum { DEFAULT_LEVELS   = 4   };
-    enum { DEFAULT_NR_PLANE = 4   };
+    //! truncation of discontinuity cost
+    virtual double getMaxDiscTerm() const = 0;
+    virtual void setMaxDiscTerm(double max_disc_term) = 0;
 
-    static void estimateRecommendedParams(int width, int height, int& ndisp, int& iters, int& levels, int& nr_plane);
+    //! discontinuity single jump
+    virtual double getDiscSingleJump() const = 0;
+    virtual void setDiscSingleJump(double disc_single_jump) = 0;
 
-    //! the default constructor
-    explicit StereoConstantSpaceBP(int ndisp    = DEFAULT_NDISP,
-                                   int iters    = DEFAULT_ITERS,
-                                   int levels   = DEFAULT_LEVELS,
-                                   int nr_plane = DEFAULT_NR_PLANE,
-                                   int msg_type = CV_32F);
+    //! type for messages (CV_16SC1 or CV_32FC1)
+    virtual int getMsgType() const = 0;
+    virtual void setMsgType(int msg_type) = 0;
 
-    //! the full constructor taking the number of disparities, number of BP iterations on each level,
-    //! number of levels, number of active disparity on the first level, truncation of data cost, data weight,
-    //! truncation of discontinuity cost, discontinuity single jump and minimum disparity threshold
-    StereoConstantSpaceBP(int ndisp, int iters, int levels, int nr_plane,
-        float max_data_term, float data_weight, float max_disc_term, float disc_single_jump,
-        int min_disp_th = 0,
-        int msg_type = CV_32F);
-
-    //! the stereo correspondence operator. Finds the disparity for the specified rectified stereo pair,
-    //! if disparity is empty output type will be CV_16S else output type will be disparity.type().
-    void operator()(const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream = Stream::Null());
+    static void estimateRecommendedParams(int width, int height, int& ndisp, int& iters, int& levels);
+};
 
-    int ndisp;
+CV_EXPORTS Ptr<gpu::StereoBeliefPropagation>
+    createStereoBeliefPropagation(int ndisp = 64, int iters = 5, int levels = 5, int msg_type = CV_32F);
 
-    int iters;
-    int levels;
+/////////////////////////////////////////
+// StereoConstantSpaceBP
 
-    int nr_plane;
+//! "A Constant-Space Belief Propagation Algorithm for Stereo Matching"
+//! Qingxiong Yang, Liang Wang, Narendra Ahuja
+//! http://vision.ai.uiuc.edu/~qyang6/
+class CV_EXPORTS StereoConstantSpaceBP : public gpu::StereoBeliefPropagation
+{
+public:
+    //! number of active disparity on the first level
+    virtual int getNrPlane() const = 0;
+    virtual void setNrPlane(int nr_plane) = 0;
 
-    float max_data_term;
-    float data_weight;
-    float max_disc_term;
-    float disc_single_jump;
+    virtual bool getUseLocalInitDataCost() const = 0;
+    virtual void setUseLocalInitDataCost(bool use_local_init_data_cost) = 0;
 
-    int min_disp_th;
+    static void estimateRecommendedParams(int width, int height, int& ndisp, int& iters, int& levels, int& nr_plane);
+};
 
-    int msg_type;
+CV_EXPORTS Ptr<gpu::StereoConstantSpaceBP>
+    createStereoConstantSpaceBP(int ndisp = 128, int iters = 8, int levels = 4, int nr_plane = 4, int msg_type = CV_32F);
 
-    bool use_local_init_data_cost;
-private:
-    GpuMat messages_buffers;
+/////////////////////////////////////////
+// DisparityBilateralFilter
 
-    GpuMat temp;
-    GpuMat out;
-};
-
-// Disparity map refinement using joint bilateral filtering given a single color image.
-// Qingxiong Yang, Liang Wang, Narendra Ahuja
-// http://vision.ai.uiuc.edu/~qyang6/
-class CV_EXPORTS DisparityBilateralFilter
+//! Disparity map refinement using joint bilateral filtering given a single color image.
+//! Qingxiong Yang, Liang Wang, Narendra Ahuja
+//! http://vision.ai.uiuc.edu/~qyang6/
+class CV_EXPORTS DisparityBilateralFilter : public cv::Algorithm
 {
 public:
-    enum { DEFAULT_NDISP  = 64 };
-    enum { DEFAULT_RADIUS = 3 };
-    enum { DEFAULT_ITERS  = 1 };
+    //! the disparity map refinement operator. Refine disparity map using joint bilateral filtering given a single color image.
+    //! disparity must have CV_8U or CV_16S type, image must have CV_8UC1 or CV_8UC3 type.
+    virtual void apply(InputArray disparity, InputArray image, OutputArray dst, Stream& stream = Stream::Null()) = 0;
 
-    //! the default constructor
-    explicit DisparityBilateralFilter(int ndisp = DEFAULT_NDISP, int radius = DEFAULT_RADIUS, int iters = DEFAULT_ITERS);
+    virtual int getNumDisparities() const = 0;
+    virtual void setNumDisparities(int numDisparities) = 0;
 
-    //! the full constructor taking the number of disparities, filter radius,
-    //! number of iterations, truncation of data continuity, truncation of disparity continuity
-    //! and filter range sigma
-    DisparityBilateralFilter(int ndisp, int radius, int iters, float edge_threshold, float max_disc_threshold, float sigma_range);
+    virtual int getRadius() const = 0;
+    virtual void setRadius(int radius) = 0;
 
-    //! the disparity map refinement operator. Refine disparity map using joint bilateral filtering given a single color image.
-    //! disparity must have CV_8U or CV_16S type, image must have CV_8UC1 or CV_8UC3 type.
-    void operator()(const GpuMat& disparity, const GpuMat& image, GpuMat& dst, Stream& stream = Stream::Null());
+    virtual int getNumIters() const = 0;
+    virtual void setNumIters(int iters) = 0;
 
-private:
-    int ndisp;
-    int radius;
-    int iters;
+    //! truncation of data continuity
+    virtual double getEdgeThreshold() const = 0;
+    virtual void setEdgeThreshold(double edge_threshold) = 0;
 
-    float edge_threshold;
-    float max_disc_threshold;
-    float sigma_range;
+    //! truncation of disparity continuity
+    virtual double getMaxDiscThreshold() const = 0;
+    virtual void setMaxDiscThreshold(double max_disc_threshold) = 0;
 
-    GpuMat table_color;
-    GpuMat table_space;
+    //! filter range sigma
+    virtual double getSigmaRange() const = 0;
+    virtual void setSigmaRange(double sigma_range) = 0;
 };
 
+CV_EXPORTS Ptr<gpu::DisparityBilateralFilter>
+    createDisparityBilateralFilter(int ndisp = 64, int radius = 3, int iters = 1);
+
+/////////////////////////////////////////
+// Utility
+
 //! Reprojects disparity image to 3D space.
 //! Supports CV_8U and CV_16S types of input disparity.
 //! The output is a 3- or 4-channel floating-point matrix.
 //! Each element of this matrix will contain the 3D coordinates of the point (x,y,z,1), computed from the disparity map.
 //! Q is the 4x4 perspective transformation matrix that can be obtained with cvStereoRectify.
-CV_EXPORTS void reprojectImageTo3D(const GpuMat& disp, GpuMat& xyzw, const Mat& Q, int dst_cn = 4, Stream& stream = Stream::Null());
+CV_EXPORTS void reprojectImageTo3D(InputArray disp, OutputArray xyzw, InputArray Q, int dst_cn = 4, Stream& stream = Stream::Null());
 
 //! Does coloring of disparity image: [0..ndisp) -> [0..240, 1, 1] in HSV.
 //! Supported types of input disparity: CV_8U, CV_16S.
 //! Output disparity has CV_8UC4 type in BGRA format (alpha = 255).
-CV_EXPORTS void drawColorDisp(const GpuMat& src_disp, GpuMat& dst_disp, int ndisp, Stream& stream = Stream::Null());
+CV_EXPORTS void drawColorDisp(InputArray src_disp, OutputArray dst_disp, int ndisp, Stream& stream = Stream::Null());
 
 }} // namespace cv { namespace gpu {
 

modules/gpustereo/perf/perf_stereo.cpp

@@ -63,18 +63,17 @@ PERF_TEST_P(ImagePair, StereoBM,
     const cv::Mat imgRight = readImage(GET_PARAM(1), cv::IMREAD_GRAYSCALE);
     ASSERT_FALSE(imgRight.empty());
 
-    const int preset = 0;
     const int ndisp = 256;
 
     if (PERF_RUN_GPU())
     {
-        cv::gpu::StereoBM_GPU d_bm(preset, ndisp);
+        cv::Ptr<cv::StereoBM> d_bm = cv::gpu::createStereoBM(ndisp);
 
         const cv::gpu::GpuMat d_imgLeft(imgLeft);
         const cv::gpu::GpuMat d_imgRight(imgRight);
         cv::gpu::GpuMat dst;
 
-        TEST_CYCLE() d_bm(d_imgLeft, d_imgRight, dst);
+        TEST_CYCLE() d_bm->compute(d_imgLeft, d_imgRight, dst);
 
         GPU_SANITY_CHECK(dst);
     }
@@ -108,13 +107,13 @@ PERF_TEST_P(ImagePair, StereoBeliefPropagation,
 
     if (PERF_RUN_GPU())
     {
-        cv::gpu::StereoBeliefPropagation d_bp(ndisp);
+        cv::Ptr<cv::gpu::StereoBeliefPropagation> d_bp = cv::gpu::createStereoBeliefPropagation(ndisp);
 
         const cv::gpu::GpuMat d_imgLeft(imgLeft);
         const cv::gpu::GpuMat d_imgRight(imgRight);
         cv::gpu::GpuMat dst;
 
-        TEST_CYCLE() d_bp(d_imgLeft, d_imgRight, dst);
+        TEST_CYCLE() d_bp->compute(d_imgLeft, d_imgRight, dst);
 
         GPU_SANITY_CHECK(dst);
     }
@@ -142,13 +141,13 @@ PERF_TEST_P(ImagePair, StereoConstantSpaceBP,
 
     if (PERF_RUN_GPU())
     {
-        cv::gpu::StereoConstantSpaceBP d_csbp(ndisp);
+        cv::Ptr<cv::gpu::StereoConstantSpaceBP> d_csbp = cv::gpu::createStereoConstantSpaceBP(ndisp);
 
         const cv::gpu::GpuMat d_imgLeft(imgLeft);
         const cv::gpu::GpuMat d_imgRight(imgRight);
         cv::gpu::GpuMat dst;
 
-        TEST_CYCLE() d_csbp(d_imgLeft, d_imgRight, dst);
+        TEST_CYCLE() d_csbp->compute(d_imgLeft, d_imgRight, dst);
 
         GPU_SANITY_CHECK(dst);
     }
@@ -174,13 +173,13 @@ PERF_TEST_P(ImagePair, DisparityBilateralFilter,
 
     if (PERF_RUN_GPU())
     {
-        cv::gpu::DisparityBilateralFilter d_filter(ndisp);
+        cv::Ptr<cv::gpu::DisparityBilateralFilter> d_filter = cv::gpu::createDisparityBilateralFilter(ndisp);
 
         const cv::gpu::GpuMat d_img(img);
         const cv::gpu::GpuMat d_disp(disp);
         cv::gpu::GpuMat dst;
 
-        TEST_CYCLE() d_filter(d_disp, d_img, dst);
+        TEST_CYCLE() d_filter->apply(d_disp, d_img, dst);
 
         GPU_SANITY_CHECK(dst);
     }

modules/gpustereo/src/disparity_bilateral_filter.cpp

@@ -47,10 +47,7 @@ using namespace cv::gpu;
 
 #if !defined (HAVE_CUDA) || defined (CUDA_DISABLER)
 
-cv::gpu::DisparityBilateralFilter::DisparityBilateralFilter(int, int, int) { throw_no_cuda(); }
-cv::gpu::DisparityBilateralFilter::DisparityBilateralFilter(int, int, int, float, float, float) { throw_no_cuda(); }
-
-void cv::gpu::DisparityBilateralFilter::operator()(const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_no_cuda(); }
+Ptr<gpu::DisparityBilateralFilter> cv::gpu::createDisparityBilateralFilter(int, int, int) { throw_no_cuda(); return Ptr<gpu::DisparityBilateralFilter>(); }
 
 #else /* !defined (HAVE_CUDA) */
 
@@ -65,15 +62,46 @@ namespace cv { namespace gpu { namespace cudev
     }
 }}}
 
-using namespace ::cv::gpu::cudev::disp_bilateral_filter;
-
 namespace
 {
-    const float DEFAULT_EDGE_THRESHOLD = 0.1f;
-    const float DEFAULT_MAX_DISC_THRESHOLD = 0.2f;
-    const float DEFAULT_SIGMA_RANGE = 10.0f;
+    class DispBilateralFilterImpl : public gpu::DisparityBilateralFilter
+    {
+    public:
+        DispBilateralFilterImpl(int ndisp, int radius, int iters);
+
+        void apply(InputArray disparity, InputArray image, OutputArray dst, Stream& stream);
+
+        int getNumDisparities() const { return ndisp_; }
+        void setNumDisparities(int numDisparities) { ndisp_ = numDisparities; }
+
+        int getRadius() const { return radius_; }
+        void setRadius(int radius);
+
+        int getNumIters() const { return iters_; }
+        void setNumIters(int iters) { iters_ = iters; }
 
-    inline void calc_color_weighted_table(GpuMat& table_color, float sigma_range, int len)
+        double getEdgeThreshold() const { return edge_threshold_; }
+        void setEdgeThreshold(double edge_threshold) { edge_threshold_ = (float) edge_threshold; }
+
+        double getMaxDiscThreshold() const { return max_disc_threshold_; }
+        void setMaxDiscThreshold(double max_disc_threshold) { max_disc_threshold_ = (float) max_disc_threshold; }
+
+        double getSigmaRange() const { return sigma_range_; }
+        void setSigmaRange(double sigma_range);
+
+    private:
+        int ndisp_;
+        int radius_;
+        int iters_;
+        float edge_threshold_;
+        float max_disc_threshold_;
+        float sigma_range_;
+
+        GpuMat table_color_;
+        GpuMat table_space_;
+    };
+
+    void calc_color_weighted_table(GpuMat& table_color, float sigma_range, int len)
     {
         Mat cpu_table_color(1, len, CV_32F);
 
@@ -85,7 +113,7 @@ namespace
         table_color.upload(cpu_table_color);
     }
 
-    inline void calc_space_weighted_filter(GpuMat& table_space, int win_size, float dist_space)
+    void calc_space_weighted_filter(GpuMat& table_space, int win_size, float dist_space)
     {
         int half = (win_size >> 1);
 
@@ -101,54 +129,78 @@ namespace
         table_space.upload(cpu_table_space);
     }
 
+    const float DEFAULT_EDGE_THRESHOLD = 0.1f;
+    const float DEFAULT_MAX_DISC_THRESHOLD = 0.2f;
+    const float DEFAULT_SIGMA_RANGE = 10.0f;
+
+    DispBilateralFilterImpl::DispBilateralFilterImpl(int ndisp, int radius, int iters) :
+        ndisp_(ndisp), radius_(radius), iters_(iters),
+        edge_threshold_(DEFAULT_EDGE_THRESHOLD), max_disc_threshold_(DEFAULT_MAX_DISC_THRESHOLD),
+        sigma_range_(DEFAULT_SIGMA_RANGE)
+    {
+        calc_color_weighted_table(table_color_, sigma_range_, 255);
+        calc_space_weighted_filter(table_space_, radius_ * 2 + 1, radius_ + 1.0f);
+    }
+
+    void DispBilateralFilterImpl::setRadius(int radius)
+    {
+        radius_ = radius;
+        calc_space_weighted_filter(table_space_, radius_ * 2 + 1, radius_ + 1.0f);
+    }
+
+    void DispBilateralFilterImpl::setSigmaRange(double sigma_range)
+    {
+        sigma_range_ = (float) sigma_range;
+        calc_color_weighted_table(table_color_, sigma_range_, 255);
+    }
+
     template <typename T>
-    void disp_bilateral_filter_operator(int ndisp, int radius, int iters, float edge_threshold,float max_disc_threshold,
-                                   GpuMat& table_color, GpuMat& table_space,
-                                   const GpuMat& disp, const GpuMat& img, GpuMat& dst, Stream& stream)
+    void disp_bilateral_filter_operator(int ndisp, int radius, int iters, float edge_threshold, float max_disc_threshold,
+                                        GpuMat& table_color, GpuMat& table_space,
+                                        const GpuMat& disp, const GpuMat& img,
+                                        OutputArray _dst, Stream& stream)
     {
-        short edge_disc = std::max<short>(short(1), short(ndisp * edge_threshold + 0.5));
-        short max_disc = short(ndisp * max_disc_threshold + 0.5);
+        using namespace cv::gpu::cudev::disp_bilateral_filter;
+
+        const short edge_disc = std::max<short>(short(1), short(ndisp * edge_threshold + 0.5));
+        const short max_disc = short(ndisp * max_disc_threshold + 0.5);
 
         disp_load_constants(table_color.ptr<float>(), table_space, ndisp, radius, edge_disc, max_disc);
 
-        if (&dst != &disp)
-        {
+        _dst.create(disp.size(), disp.type());
+        GpuMat dst = _dst.getGpuMat();
+
+        if (dst.data != disp.data)
             disp.copyTo(dst, stream);
-        }
 
         disp_bilateral_filter<T>(dst, img, img.channels(), iters, StreamAccessor::getStream(stream));
     }
 
-    typedef void (*bilateral_filter_operator_t)(int ndisp, int radius, int iters, float edge_threshold, float max_disc_threshold,
-                                                GpuMat& table_color, GpuMat& table_space,
-                                                const GpuMat& disp, const GpuMat& img, GpuMat& dst, Stream& stream);
+    void DispBilateralFilterImpl::apply(InputArray _disp, InputArray _image, OutputArray dst, Stream& stream)
+    {
+        typedef void (*bilateral_filter_operator_t)(int ndisp, int radius, int iters, float edge_threshold, float max_disc_threshold,
+                                                    GpuMat& table_color, GpuMat& table_space,
+                                                    const GpuMat& disp, const GpuMat& img, OutputArray dst, Stream& stream);
+        const bilateral_filter_operator_t operators[] =
+            {disp_bilateral_filter_operator<unsigned char>, 0, 0, disp_bilateral_filter_operator<short>, 0, 0, 0, 0};
 
-    const bilateral_filter_operator_t operators[] =
-        {disp_bilateral_filter_operator<unsigned char>, 0, 0, disp_bilateral_filter_operator<short>, 0, 0, 0, 0};
-}
+        CV_Assert( 0 < ndisp_ && 0 < radius_ && 0 < iters_ );
 
-cv::gpu::DisparityBilateralFilter::DisparityBilateralFilter(int ndisp_, int radius_, int iters_)
-    : ndisp(ndisp_), radius(radius_), iters(iters_), edge_threshold(DEFAULT_EDGE_THRESHOLD), max_disc_threshold(DEFAULT_MAX_DISC_THRESHOLD),
-      sigma_range(DEFAULT_SIGMA_RANGE)
-{
-    calc_color_weighted_table(table_color, sigma_range, 255);
-    calc_space_weighted_filter(table_space, radius * 2 + 1, radius + 1.0f);
-}
+        GpuMat disp = _disp.getGpuMat();
+        GpuMat img = _image.getGpuMat();
 
-cv::gpu::DisparityBilateralFilter::DisparityBilateralFilter(int ndisp_, int radius_, int iters_, float edge_threshold_,
-                                                     float max_disc_threshold_, float sigma_range_)
-    : ndisp(ndisp_), radius(radius_), iters(iters_), edge_threshold(edge_threshold_), max_disc_threshold(max_disc_threshold_),
-      sigma_range(sigma_range_)
-{
-    calc_color_weighted_table(table_color, sigma_range, 255);
-    calc_space_weighted_filter(table_space, radius * 2 + 1, radius + 1.0f);
+        CV_Assert( disp.type() == CV_8U || disp.type() == CV_16S );
+        CV_Assert( img.type() == CV_8UC1 || img.type() == CV_8UC3 );
+        CV_Assert( disp.size() == img.size() );
+
+        operators[disp.type()](ndisp_, radius_, iters_, edge_threshold_, max_disc_threshold_,
+                               table_color_, table_space_, disp, img, dst, stream);
+    }
 }
 
-void cv::gpu::DisparityBilateralFilter::operator()(const GpuMat& disp, const GpuMat& img, GpuMat& dst, Stream& stream)
+Ptr<gpu::DisparityBilateralFilter> cv::gpu::createDisparityBilateralFilter(int ndisp, int radius, int iters)
 {
-    CV_DbgAssert(0 < ndisp && 0 < radius && 0 < iters);
-    CV_Assert(disp.rows == img.rows && disp.cols == img.cols && (disp.type() == CV_8U || disp.type() == CV_16S) && (img.type() == CV_8UC1 || img.type() == CV_8UC3));
-    operators[disp.type()](ndisp, radius, iters, edge_threshold, max_disc_threshold, table_color, table_space, disp, img, dst, stream);
+    return new DispBilateralFilterImpl(ndisp, radius, iters);
 }
 
 #endif /* !defined (HAVE_CUDA) */

modules/gpustereo/src/precomp.hpp

@@ -48,5 +48,6 @@
 #include "opencv2/gpustereo.hpp"
 
 #include "opencv2/core/private.gpu.hpp"
+#include "opencv2/core/utility.hpp"
 
 #endif /* __OPENCV_PRECOMP_H__ */

modules/gpustereo/src/stereobm.cpp

@@ -47,11 +47,7 @@ using namespace cv::gpu;
 
 #if !defined (HAVE_CUDA) || defined (CUDA_DISABLER)
 
-cv::gpu::StereoBM_GPU::StereoBM_GPU() { throw_no_cuda(); }
-cv::gpu::StereoBM_GPU::StereoBM_GPU(int, int, int) { throw_no_cuda(); }
-
-bool cv::gpu::StereoBM_GPU::checkIfGpuCallReasonable() { throw_no_cuda(); return false; }
-void cv::gpu::StereoBM_GPU::operator() ( const GpuMat&, const GpuMat&, GpuMat&, Stream&) { throw_no_cuda(); }
+Ptr<gpu::StereoBM> cv::gpu::createStereoBM(int, int) { throw_no_cuda(); return Ptr<gpu::StereoBM>(); }
 
 #else /* !defined (HAVE_CUDA) */
 
@@ -67,74 +63,123 @@ namespace cv { namespace gpu { namespace cudev
 
 namespace
 {
-    const float defaultAvgTexThreshold = 3;
-}
+    class StereoBMImpl : public gpu::StereoBM
+    {
+    public:
+        StereoBMImpl(int numDisparities, int blockSize);
 
-cv::gpu::StereoBM_GPU::StereoBM_GPU()
-    : preset(BASIC_PRESET), ndisp(DEFAULT_NDISP), winSize(DEFAULT_WINSZ), avergeTexThreshold(defaultAvgTexThreshold)
-{
-}
+        void compute(InputArray left, InputArray right, OutputArray disparity);
+        void compute(InputArray left, InputArray right, OutputArray disparity, Stream& stream);
 
-cv::gpu::StereoBM_GPU::StereoBM_GPU(int preset_, int ndisparities_, int winSize_)
-    : preset(preset_), ndisp(ndisparities_), winSize(winSize_), avergeTexThreshold(defaultAvgTexThreshold)
-{
-    const int max_supported_ndisp = 1 << (sizeof(unsigned char) * 8);
-    CV_Assert(0 < ndisp && ndisp <= max_supported_ndisp);
-    CV_Assert(ndisp % 8 == 0);
-    CV_Assert(winSize % 2 == 1);
-}
+        int getMinDisparity() const { return 0; }
+        void setMinDisparity(int /*minDisparity*/) {}
 
-bool cv::gpu::StereoBM_GPU::checkIfGpuCallReasonable()
-{
-    if (0 == getCudaEnabledDeviceCount())
-        return false;
+        int getNumDisparities() const { return ndisp_; }
+        void setNumDisparities(int numDisparities) { ndisp_ = numDisparities; }
 
-    DeviceInfo device_info;
+        int getBlockSize() const { return winSize_; }
+        void setBlockSize(int blockSize) { winSize_ = blockSize; }
 
-    if (device_info.major() > 1 || device_info.multiProcessorCount() > 16)
-        return true;
+        int getSpeckleWindowSize() const { return 0; }
+        void setSpeckleWindowSize(int /*speckleWindowSize*/) {}
 
-    return false;
-}
+        int getSpeckleRange() const { return 0; }
+        void setSpeckleRange(int /*speckleRange*/) {}
 
-namespace
-{
-    void stereo_bm_gpu_operator( GpuMat& minSSD,  GpuMat& leBuf, GpuMat&  riBuf,  int preset, int ndisp, int winSize, float avergeTexThreshold, const GpuMat& left, const GpuMat& right, GpuMat& disparity, cudaStream_t stream)
+        int getDisp12MaxDiff() const { return 0; }
+        void setDisp12MaxDiff(int /*disp12MaxDiff*/) {}
+
+        int getPreFilterType() const { return preset_; }
+        void setPreFilterType(int preFilterType) { preset_ = preFilterType; }
+
+        int getPreFilterSize() const { return 0; }
+        void setPreFilterSize(int /*preFilterSize*/) {}
+
+        int getPreFilterCap() const { return preFilterCap_; }
+        void setPreFilterCap(int preFilterCap) { preFilterCap_ = preFilterCap; }
+
+        int getTextureThreshold() const { return avergeTexThreshold_; }
+        void setTextureThreshold(int textureThreshold) { avergeTexThreshold_ = textureThreshold; }
+
+        int getUniquenessRatio() const { return 0; }
+        void setUniquenessRatio(int /*uniquenessRatio*/) {}
+
+        int getSmallerBlockSize() const { return 0; }
+        void setSmallerBlockSize(int /*blockSize*/){}
+
+        Rect getROI1() const { return Rect(); }
+        void setROI1(Rect /*roi1*/) {}
+
+        Rect getROI2() const { return Rect(); }
+        void setROI2(Rect /*roi2*/) {}
+
+    private:
+        int preset_;
+        int ndisp_;
+        int winSize_;
+        int preFilterCap_;
+        float avergeTexThreshold_;
+
+        GpuMat minSSD_, leBuf_, riBuf_;
+    };
+
+    StereoBMImpl::StereoBMImpl(int numDisparities, int blockSize)
+        : preset_(0), ndisp_(numDisparities), winSize_(blockSize), preFilterCap_(31), avergeTexThreshold_(3)
+    {
+    }
+
+    void StereoBMImpl::compute(InputArray left, InputArray right, OutputArray disparity)
+    {
+        compute(left, right, disparity, Stream::Null());
+    }
+
+    void StereoBMImpl::compute(InputArray _left, InputArray _right, OutputArray _disparity, Stream& _stream)
     {
         using namespace ::cv::gpu::cudev::stereobm;
 
-        CV_Assert(left.rows == right.rows && left.cols == right.cols);
-        CV_Assert(left.type() == CV_8UC1);
-        CV_Assert(right.type() == CV_8UC1);
+        const int max_supported_ndisp = 1 << (sizeof(unsigned char) * 8);
+        CV_Assert( 0 < ndisp_ && ndisp_ <= max_supported_ndisp );
+        CV_Assert( ndisp_ % 8 == 0 );
+        CV_Assert( winSize_ % 2 == 1 );
+
+        GpuMat left = _left.getGpuMat();
+        GpuMat right = _right.getGpuMat();
+
+        CV_Assert( left.type() == CV_8UC1 );
+        CV_Assert( left.size() == right.size() && left.type() == right.type() );
+
+        _disparity.create(left.size(), CV_8UC1);
+        GpuMat disparity = _disparity.getGpuMat();
+
+        cudaStream_t stream = StreamAccessor::getStream(_stream);
 
-        disparity.create(left.size(), CV_8U);
-        minSSD.create(left.size(), CV_32S);
+        gpu::ensureSizeIsEnough(left.size(), CV_32SC1, minSSD_);
 
-        GpuMat le_for_bm =  left;
-        GpuMat ri_for_bm = right;
+        PtrStepSzb le_for_bm =  left;
+        PtrStepSzb ri_for_bm = right;
 
-        if (preset == StereoBM_GPU::PREFILTER_XSOBEL)
+        if (preset_ == cv::StereoBM::PREFILTER_XSOBEL)
         {
-            leBuf.create( left.size(),  left.type());
-            riBuf.create(right.size(), right.type());
+            gpu::ensureSizeIsEnough(left.size(), left.type(), leBuf_);
+            gpu::ensureSizeIsEnough(right.size(), right.type(), riBuf_);
 
-            prefilter_xsobel( left, leBuf, 31, stream);
-            prefilter_xsobel(right, riBuf, 31, stream);
+            prefilter_xsobel( left, leBuf_, preFilterCap_, stream);
+            prefilter_xsobel(right, riBuf_, preFilterCap_, stream);
 
-            le_for_bm = leBuf;
-            ri_for_bm = riBuf;
+            le_for_bm = leBuf_;
+            ri_for_bm = riBuf_;
         }
 
-        stereoBM_GPU(le_for_bm, ri_for_bm, disparity, ndisp, winSize, minSSD, stream);
+        stereoBM_GPU(le_for_bm, ri_for_bm, disparity, ndisp_, winSize_, minSSD_, stream);
 
-        if (avergeTexThreshold)
-            postfilter_textureness(le_for_bm, winSize, avergeTexThreshold, disparity, stream);
+        if (avergeTexThreshold_ > 0)
+            postfilter_textureness(le_for_bm, winSize_, avergeTexThreshold_, disparity, stream);
     }
 }
 
-void cv::gpu::StereoBM_GPU::operator() ( const GpuMat& left, const GpuMat& right, GpuMat& disparity, Stream& stream)
+Ptr<gpu::StereoBM> cv::gpu::createStereoBM(int numDisparities, int blockSize)
 {
-    stereo_bm_gpu_operator(minSSD, leBuf, riBuf, preset, ndisp, winSize, avergeTexThreshold, left, right, disparity, StreamAccessor::getStream(stream));
+    return new StereoBMImpl(numDisparities, blockSize);
 }
 
 #endif /* !defined (HAVE_CUDA) */

modules/gpustereo/src/util.cpp

@@ -47,8 +47,8 @@ using namespace cv::gpu;
 
 #if !defined HAVE_CUDA || defined(CUDA_DISABLER)
 
-void cv::gpu::reprojectImageTo3D(const GpuMat&, GpuMat&, const Mat&, int, Stream&) { throw_no_cuda(); }
-void cv::gpu::drawColorDisp(const GpuMat&, GpuMat&, int, Stream&) { throw_no_cuda(); }
+void cv::gpu::reprojectImageTo3D(InputArray, OutputArray, InputArray, int, Stream&) { throw_no_cuda(); }
+void cv::gpu::drawColorDisp(InputArray, OutputArray, int, Stream&) { throw_no_cuda(); }
 
 #else
 
@@ -61,7 +61,7 @@ namespace cv { namespace gpu { namespace cudev
     void reprojectImageTo3D_gpu(const PtrStepSzb disp, PtrStepSzb xyz, const float* q, cudaStream_t stream);
 }}}
 
-void cv::gpu::reprojectImageTo3D(const GpuMat& disp, GpuMat& xyz, const Mat& Q, int dst_cn, Stream& stream)
+void cv::gpu::reprojectImageTo3D(InputArray _disp, OutputArray _xyz, InputArray _Q, int dst_cn, Stream& stream)
 {
     using namespace cv::gpu::cudev;
 
@@ -72,11 +72,15 @@ void cv::gpu::reprojectImageTo3D(const GpuMat& disp, GpuMat& xyz, const Mat& Q,
         {reprojectImageTo3D_gpu<uchar, float4>, 0, 0, reprojectImageTo3D_gpu<short, float4>}
     };
 
-    CV_Assert(disp.type() == CV_8U || disp.type() == CV_16S);
-    CV_Assert(Q.type() == CV_32F && Q.rows == 4 && Q.cols == 4 && Q.isContinuous());
-    CV_Assert(dst_cn == 3 || dst_cn == 4);
+    GpuMat disp = _disp.getGpuMat();
+    Mat Q = _Q.getMat();
 
-    xyz.create(disp.size(), CV_MAKE_TYPE(CV_32F, dst_cn));
+    CV_Assert( disp.type() == CV_8U || disp.type() == CV_16S );
+    CV_Assert( Q.type() == CV_32F && Q.rows == 4 && Q.cols == 4 && Q.isContinuous() );
+    CV_Assert( dst_cn == 3 || dst_cn == 4 );
+
+    _xyz.create(disp.size(), CV_MAKE_TYPE(CV_32F, dst_cn));
+    GpuMat xyz = _xyz.getGpuMat();
 
     funcs[dst_cn == 4][disp.type()](disp, xyz, Q.ptr<float>(), StreamAccessor::getStream(stream));
 }
@@ -93,23 +97,25 @@ namespace cv { namespace gpu { namespace cudev
 namespace
 {
     template <typename T>
-    void drawColorDisp_caller(const GpuMat& src, GpuMat& dst, int ndisp, const cudaStream_t& stream)
+    void drawColorDisp_caller(const GpuMat& src, OutputArray _dst, int ndisp, const cudaStream_t& stream)
     {
         using namespace ::cv::gpu::cudev;
 
-        dst.create(src.size(), CV_8UC4);
+        _dst.create(src.size(), CV_8UC4);
+        GpuMat dst = _dst.getGpuMat();
 
         drawColorDisp_gpu((PtrStepSz<T>)src, dst, ndisp, stream);
     }
-
-    typedef void (*drawColorDisp_caller_t)(const GpuMat& src, GpuMat& dst, int ndisp, const cudaStream_t& stream);
-
-    const drawColorDisp_caller_t drawColorDisp_callers[] = {drawColorDisp_caller<unsigned char>, 0, 0, drawColorDisp_caller<short>, 0, 0, 0, 0};
 }
 
-void cv::gpu::drawColorDisp(const GpuMat& src, GpuMat& dst, int ndisp, Stream& stream)
+void cv::gpu::drawColorDisp(InputArray _src, OutputArray dst, int ndisp, Stream& stream)
 {
-    CV_Assert(src.type() == CV_8U || src.type() == CV_16S);
+    typedef void (*drawColorDisp_caller_t)(const GpuMat& src, OutputArray dst, int ndisp, const cudaStream_t& stream);
+    const drawColorDisp_caller_t drawColorDisp_callers[] = {drawColorDisp_caller<unsigned char>, 0, 0, drawColorDisp_caller<short>, 0, 0, 0, 0};
+
+    GpuMat src = _src.getGpuMat();
+
+    CV_Assert( src.type() == CV_8U || src.type() == CV_16S );
 
     drawColorDisp_callers[src.type()](src, dst, ndisp, StreamAccessor::getStream(stream));
 }

modules/gpustereo/test/test_stereo.cpp

@@ -71,10 +71,10 @@ GPU_TEST_P(StereoBM, Regression)
     ASSERT_FALSE(right_image.empty());
     ASSERT_FALSE(disp_gold.empty());
 
-    cv::gpu::StereoBM_GPU bm(0, 128, 19);
+    cv::Ptr<cv::StereoBM> bm = cv::gpu::createStereoBM(128, 19);
     cv::gpu::GpuMat disp;
 
-    bm(loadMat(left_image), loadMat(right_image), disp);
+    bm->compute(loadMat(left_image), loadMat(right_image), disp);
 
     EXPECT_MAT_NEAR(disp_gold, disp, 0.0);
 }
@@ -106,10 +106,15 @@ GPU_TEST_P(StereoBeliefPropagation, Regression)
     ASSERT_FALSE(right_image.empty());
     ASSERT_FALSE(disp_gold.empty());
 
-    cv::gpu::StereoBeliefPropagation bp(64, 8, 2, 25, 0.1f, 15, 1, CV_16S);
+    cv::Ptr<cv::gpu::StereoBeliefPropagation> bp = cv::gpu::createStereoBeliefPropagation(64, 8, 2, CV_16S);
+    bp->setMaxDataTerm(25.0);
+    bp->setDataWeight(0.1);
+    bp->setMaxDiscTerm(15.0);
+    bp->setDiscSingleJump(1.0);
+
     cv::gpu::GpuMat disp;
 
-    bp(loadMat(left_image), loadMat(right_image), disp);
+    bp->compute(loadMat(left_image), loadMat(right_image), disp);
 
     cv::Mat h_disp(disp);
     h_disp.convertTo(h_disp, disp_gold.depth());
@@ -150,10 +155,10 @@ GPU_TEST_P(StereoConstantSpaceBP, Regression)
     ASSERT_FALSE(right_image.empty());
     ASSERT_FALSE(disp_gold.empty());
 
-    cv::gpu::StereoConstantSpaceBP csbp(128, 16, 4, 4);
+    cv::Ptr<cv::gpu::StereoConstantSpaceBP> csbp = cv::gpu::createStereoConstantSpaceBP(128, 16, 4, 4);
     cv::gpu::GpuMat disp;
 
-    csbp(loadMat(left_image), loadMat(right_image), disp);
+    csbp->compute(loadMat(left_image), loadMat(right_image), disp);
 
     cv::Mat h_disp(disp);
     h_disp.convertTo(h_disp, disp_gold.depth());

samples/gpu/driver_api_stereo_multi.cpp

@@ -85,7 +85,7 @@ void inline contextOff()
 // GPUs data
 GpuMat d_left[2];
 GpuMat d_right[2];
-StereoBM_GPU* bm[2];
+Ptr<gpu::StereoBM> bm[2];
 GpuMat d_result[2];
 
 static void printHelp()
@@ -162,14 +162,14 @@ int main(int argc, char** argv)
     contextOn(0);
     d_left[0].upload(left.rowRange(0, left.rows / 2));
     d_right[0].upload(right.rowRange(0, right.rows / 2));
-    bm[0] = new StereoBM_GPU();
+    bm[0] = gpu::createStereoBM();
     contextOff();
 
     // Split source images for processing on the GPU #1
     contextOn(1);
     d_left[1].upload(left.rowRange(left.rows / 2, left.rows));
     d_right[1].upload(right.rowRange(right.rows / 2, right.rows));
-    bm[1] = new StereoBM_GPU();
+    bm[1] = gpu::createStereoBM();
     contextOff();
 
     // Execute calculation in two threads using two GPUs
@@ -182,7 +182,7 @@ int main(int argc, char** argv)
     d_left[0].release();
     d_right[0].release();
     d_result[0].release();
-    delete bm[0];
+    bm[0].release();
     contextOff();
 
     // Release the second GPU resources
@@ -191,7 +191,7 @@ int main(int argc, char** argv)
     d_left[1].release();
     d_right[1].release();
     d_result[1].release();
-    delete bm[1];
+    bm[1].release();
     contextOff();
 
     waitKey();
@@ -204,8 +204,7 @@ void Worker::operator()(int device_id) const
 {
     contextOn(device_id);
 
-    bm[device_id]->operator()(d_left[device_id], d_right[device_id],
-                              d_result[device_id]);
+    bm[device_id]->compute(d_left[device_id], d_right[device_id], d_result[device_id]);
 
     std::cout << "GPU #" << device_id << " (" << DeviceInfo().name()
         << "): finished\n";

samples/gpu/stereo_match.cpp

@@ -65,9 +65,9 @@ private:
     Mat left, right;
     gpu::GpuMat d_left, d_right;
 
-    gpu::StereoBM_GPU bm;
-    gpu::StereoBeliefPropagation bp;
-    gpu::StereoConstantSpaceBP csbp;
+    Ptr<gpu::StereoBM> bm;
+    Ptr<gpu::StereoBeliefPropagation> bp;
+    Ptr<gpu::StereoConstantSpaceBP> csbp;
 
     int64 work_begin;
     double work_fps;
@@ -172,9 +172,9 @@ void App::run()
     imshow("right", right);
 
     // Set common parameters
-    bm.ndisp = p.ndisp;
-    bp.ndisp = p.ndisp;
-    csbp.ndisp = p.ndisp;
+    bm = gpu::createStereoBM(p.ndisp);
+    bp = gpu::createStereoBeliefPropagation(p.ndisp);
+    csbp = cv::gpu::createStereoConstantSpaceBP(p.ndisp);
 
     // Prepare disparity map of specified type
     Mat disp(left.size(), CV_8U);
@@ -201,10 +201,10 @@ void App::run()
                 imshow("left", left);
                 imshow("right", right);
             }
-            bm(d_left, d_right, d_disp);
+            bm->compute(d_left, d_right, d_disp);
             break;
-        case Params::BP: bp(d_left, d_right, d_disp); break;
-        case Params::CSBP: csbp(d_left, d_right, d_disp); break;
+        case Params::BP: bp->compute(d_left, d_right, d_disp); break;
+        case Params::CSBP: csbp->compute(d_left, d_right, d_disp); break;
         }
         workEnd();
 
@@ -228,16 +228,16 @@ void App::printParams() const
     switch (p.method)
     {
     case Params::BM:
-        cout << "win_size: " << bm.winSize << endl;
-        cout << "prefilter_sobel: " << bm.preset << endl;
+        cout << "win_size: " << bm->getBlockSize() << endl;
+        cout << "prefilter_sobel: " << bm->getPreFilterType() << endl;
         break;
     case Params::BP:
-        cout << "iter_count: " << bp.iters << endl;
-        cout << "level_count: " << bp.levels << endl;
+        cout << "iter_count: " << bp->getNumIters() << endl;
+        cout << "level_count: " << bp->getNumLevels() << endl;
         break;
     case Params::CSBP:
-        cout << "iter_count: " << csbp.iters << endl;
-        cout << "level_count: " << csbp.levels << endl;
+        cout << "iter_count: " << csbp->getNumIters() << endl;
+        cout << "level_count: " << csbp->getNumLevels() << endl;
         break;
     }
     cout << endl;
@@ -289,92 +289,92 @@ void App::handleKey(char key)
     case 's': case 'S':
         if (p.method == Params::BM)
         {
-            switch (bm.preset)
+            switch (bm->getPreFilterType())
             {
-            case gpu::StereoBM_GPU::BASIC_PRESET:
-                bm.preset = gpu::StereoBM_GPU::PREFILTER_XSOBEL;
+            case 0:
+                bm->setPreFilterType(cv::StereoBM::PREFILTER_XSOBEL);
                 break;
-            case gpu::StereoBM_GPU::PREFILTER_XSOBEL:
-                bm.preset = gpu::StereoBM_GPU::BASIC_PRESET;
+            case cv::StereoBM::PREFILTER_XSOBEL:
+                bm->setPreFilterType(0);
                 break;
             }
-            cout << "prefilter_sobel: " << bm.preset << endl;
+            cout << "prefilter_sobel: " << bm->getPreFilterType() << endl;
         }
         break;
     case '1':
         p.ndisp = p.ndisp == 1 ? 8 : p.ndisp + 8;
         cout << "ndisp: " << p.ndisp << endl;
-        bm.ndisp = p.ndisp;
-        bp.ndisp = p.ndisp;
-        csbp.ndisp = p.ndisp;
+        bm->setNumDisparities(p.ndisp);
+        bp->setNumDisparities(p.ndisp);
+        csbp->setNumDisparities(p.ndisp);
         break;
     case 'q': case 'Q':
         p.ndisp = max(p.ndisp - 8, 1);
         cout << "ndisp: " << p.ndisp << endl;
-        bm.ndisp = p.ndisp;
-        bp.ndisp = p.ndisp;
-        csbp.ndisp = p.ndisp;
+        bm->setNumDisparities(p.ndisp);
+        bp->setNumDisparities(p.ndisp);
+        csbp->setNumDisparities(p.ndisp);
         break;
     case '2':
         if (p.method == Params::BM)
         {
-            bm.winSize = min(bm.winSize + 1, 51);
-            cout << "win_size: " << bm.winSize << endl;
+            bm->setBlockSize(min(bm->getBlockSize() + 1, 51));
+            cout << "win_size: " << bm->getBlockSize() << endl;
         }
         break;
     case 'w': case 'W':
         if (p.method == Params::BM)
         {
-            bm.winSize = max(bm.winSize - 1, 2);
-            cout << "win_size: " << bm.winSize << endl;
+            bm->setBlockSize(max(bm->getBlockSize() - 1, 2));
+            cout << "win_size: " << bm->getBlockSize() << endl;
         }
         break;
     case '3':
         if (p.method == Params::BP)
         {
-            bp.iters += 1;
-            cout << "iter_count: " << bp.iters << endl;
+            bp->setNumIters(bp->getNumIters() + 1);
+            cout << "iter_count: " << bp->getNumIters() << endl;
         }
         else if (p.method == Params::CSBP)
         {
-            csbp.iters += 1;
-            cout << "iter_count: " << csbp.iters << endl;
+            csbp->setNumIters(csbp->getNumIters() + 1);
+            cout << "iter_count: " << csbp->getNumIters() << endl;
         }
         break;
     case 'e': case 'E':
         if (p.method == Params::BP)
         {
-            bp.iters = max(bp.iters - 1, 1);
-            cout << "iter_count: " << bp.iters << endl;
+            bp->setNumIters(max(bp->getNumIters() - 1, 1));
+            cout << "iter_count: " << bp->getNumIters() << endl;
         }
         else if (p.method == Params::CSBP)
         {
-            csbp.iters = max(csbp.iters - 1, 1);
-            cout << "iter_count: " << csbp.iters << endl;
+            csbp->setNumIters(max(csbp->getNumIters() - 1, 1));
+            cout << "iter_count: " << csbp->getNumIters() << endl;
         }
         break;
     case '4':
         if (p.method == Params::BP)
         {
-            bp.levels += 1;
-            cout << "level_count: " << bp.levels << endl;
+            bp->setNumLevels(bp->getNumLevels() + 1);
+            cout << "level_count: " << bp->getNumLevels() << endl;
         }
         else if (p.method == Params::CSBP)
         {
-            csbp.levels += 1;
-            cout << "level_count: " << csbp.levels << endl;
+            csbp->setNumLevels(csbp->getNumLevels() + 1);
+            cout << "level_count: " << csbp->getNumLevels() << endl;
         }
         break;
     case 'r': case 'R':
         if (p.method == Params::BP)
         {
-            bp.levels = max(bp.levels - 1, 1);
-            cout << "level_count: " << bp.levels << endl;
+            bp->setNumLevels(max(bp->getNumLevels() - 1, 1));
+            cout << "level_count: " << bp->getNumLevels() << endl;
         }
         else if (p.method == Params::CSBP)
         {
-            csbp.levels = max(csbp.levels - 1, 1);
-            cout << "level_count: " << csbp.levels << endl;
+            csbp->setNumLevels(max(csbp->getNumLevels() - 1, 1));
+            cout << "level_count: " << csbp->getNumLevels() << endl;
         }
         break;
     }

samples/gpu/stereo_multi.cpp

@@ -51,7 +51,7 @@ struct Worker { void operator()(int device_id) const; };
 // GPUs data
 GpuMat d_left[2];
 GpuMat d_right[2];
-StereoBM_GPU* bm[2];
+Ptr<gpu::StereoBM> bm[2];
 GpuMat d_result[2];
 
 static void printHelp()
@@ -112,13 +112,13 @@ int main(int argc, char** argv)
     setDevice(0);
     d_left[0].upload(left.rowRange(0, left.rows / 2));
     d_right[0].upload(right.rowRange(0, right.rows / 2));
-    bm[0] = new StereoBM_GPU();
+    bm[0] = gpu::createStereoBM();
 
     // Split source images for processing on the GPU #1
     setDevice(1);
     d_left[1].upload(left.rowRange(left.rows / 2, left.rows));
     d_right[1].upload(right.rowRange(right.rows / 2, right.rows));
-    bm[1] = new StereoBM_GPU();
+    bm[1] = gpu::createStereoBM();
 
     // Execute calculation in two threads using two GPUs
     int devices[] = {0, 1};
@@ -130,7 +130,7 @@ int main(int argc, char** argv)
     d_left[0].release();
     d_right[0].release();
     d_result[0].release();
-    delete bm[0];
+    bm[0].release();
 
     // Release the second GPU resources
     setDevice(1);
@@ -138,7 +138,7 @@ int main(int argc, char** argv)
     d_left[1].release();
     d_right[1].release();
     d_result[1].release();
-    delete bm[1];
+    bm[1].release();
 
     waitKey();
     return 0;
@@ -149,8 +149,7 @@ void Worker::operator()(int device_id) const
 {
     setDevice(device_id);
 
-    bm[device_id]->operator()(d_left[device_id], d_right[device_id],
-                              d_result[device_id]);
+    bm[device_id]->compute(d_left[device_id], d_right[device_id], d_result[device_id]);
 
     std::cout << "GPU #" << device_id << " (" << DeviceInfo().name()
         << "): finished\n";