gpuobjdetect module for object detection

modules/gpu/include/opencv2/gpu.hpp

@@ -56,6 +56,7 @@
 #include "opencv2/gpufeatures2d.hpp"
 #include "opencv2/gpuvideo.hpp"
 #include "opencv2/gpucalib3d.hpp"
+#include "opencv2/gpuobjdetect.hpp"
 
 #include "opencv2/imgproc.hpp"
 #include "opencv2/objdetect.hpp"
@@ -92,96 +93,7 @@ namespace cv { namespace gpu {
 
 
 
-//////////////// HOG (Histogram-of-Oriented-Gradients) Descriptor and Object Detector //////////////
-struct CV_EXPORTS HOGConfidence
-{
-   double scale;
-   std::vector<Point> locations;
-   std::vector<double> confidences;
-   std::vector<double> part_scores[4];
-};
 
-struct CV_EXPORTS HOGDescriptor
-{
-    enum { DEFAULT_WIN_SIGMA = -1 };
-    enum { DEFAULT_NLEVELS = 64 };
-    enum { DESCR_FORMAT_ROW_BY_ROW, DESCR_FORMAT_COL_BY_COL };
-
-    HOGDescriptor(Size win_size=Size(64, 128), Size block_size=Size(16, 16),
-                  Size block_stride=Size(8, 8), Size cell_size=Size(8, 8),
-                  int nbins=9, double win_sigma=DEFAULT_WIN_SIGMA,
-                  double threshold_L2hys=0.2, bool gamma_correction=true,
-                  int nlevels=DEFAULT_NLEVELS);
-
-    size_t getDescriptorSize() const;
-    size_t getBlockHistogramSize() const;
-
-    void setSVMDetector(const std::vector<float>& detector);
-
-    static std::vector<float> getDefaultPeopleDetector();
-    static std::vector<float> getPeopleDetector48x96();
-    static std::vector<float> getPeopleDetector64x128();
-
-    void detect(const GpuMat& img, std::vector<Point>& found_locations,
-                double hit_threshold=0, Size win_stride=Size(),
-                Size padding=Size());
-
-    void detectMultiScale(const GpuMat& img, std::vector<Rect>& found_locations,
-                          double hit_threshold=0, Size win_stride=Size(),
-                          Size padding=Size(), double scale0=1.05,
-                          int group_threshold=2);
-
-    void computeConfidence(const GpuMat& img, std::vector<Point>& hits, double hit_threshold,
-                                                Size win_stride, Size padding, std::vector<Point>& locations, std::vector<double>& confidences);
-
-    void computeConfidenceMultiScale(const GpuMat& img, std::vector<Rect>& found_locations,
-                                                                    double hit_threshold, Size win_stride, Size padding,
-                                                                    std::vector<HOGConfidence> &conf_out, int group_threshold);
-
-    void getDescriptors(const GpuMat& img, Size win_stride,
-                        GpuMat& descriptors,
-                        int descr_format=DESCR_FORMAT_COL_BY_COL);
-
-    Size win_size;
-    Size block_size;
-    Size block_stride;
-    Size cell_size;
-    int nbins;
-    double win_sigma;
-    double threshold_L2hys;
-    bool gamma_correction;
-    int nlevels;
-
-protected:
-    void computeBlockHistograms(const GpuMat& img);
-    void computeGradient(const GpuMat& img, GpuMat& grad, GpuMat& qangle);
-
-    double getWinSigma() const;
-    bool checkDetectorSize() const;
-
-    static int numPartsWithin(int size, int part_size, int stride);
-    static Size numPartsWithin(Size size, Size part_size, Size stride);
-
-    // Coefficients of the separating plane
-    float free_coef;
-    GpuMat detector;
-
-    // Results of the last classification step
-    GpuMat labels, labels_buf;
-    Mat labels_host;
-
-    // Results of the last histogram evaluation step
-    GpuMat block_hists, block_hists_buf;
-
-    // Gradients conputation results
-    GpuMat grad, qangle, grad_buf, qangle_buf;
-
-    // returns subbuffer with required size, reallocates buffer if nessesary.
-    static GpuMat getBuffer(const Size& sz, int type, GpuMat& buf);
-    static GpuMat getBuffer(int rows, int cols, int type, GpuMat& buf);
-
-    std::vector<GpuMat> image_scales;
-};
 
 
 ////////////////////////////////// BruteForceMatcher //////////////////////////////////
@@ -213,34 +125,7 @@ public:
 };
 
 ////////////////////////////////// CascadeClassifier_GPU //////////////////////////////////////////
-// The cascade classifier class for object detection: supports old haar and new lbp xlm formats and nvbin for haar cascades olny.
-class CV_EXPORTS CascadeClassifier_GPU
-{
-public:
-    CascadeClassifier_GPU();
-    CascadeClassifier_GPU(const String& filename);
-    ~CascadeClassifier_GPU();
 
-    bool empty() const;
-    bool load(const String& filename);
-    void release();
-
-    /* returns number of detected objects */
-    int detectMultiScale(const GpuMat& image, GpuMat& objectsBuf, double scaleFactor = 1.2, int minNeighbors = 4, Size minSize = Size());
-    int detectMultiScale(const GpuMat& image, GpuMat& objectsBuf, Size maxObjectSize, Size minSize = Size(), double scaleFactor = 1.1, int minNeighbors = 4);
-
-    bool findLargestObject;
-    bool visualizeInPlace;
-
-    Size getClassifierSize() const;
-
-private:
-    struct CascadeClassifierImpl;
-    CascadeClassifierImpl* impl;
-    struct HaarCascade;
-    struct LbpCascade;
-    friend class CascadeClassifier_GPU_LBP;
-};
 
 ////////////////////////////////// FAST //////////////////////////////////////////