Common Interfaces of Generic Descriptor Matchers

OneWayDescriptorBase

class OneWayDescriptorBase

Class encapsulates functionality for training/loading a set of one way descriptors and finding the nearest closest descriptor to an input feature.

class CV_EXPORTS OneWayDescriptorBase
{
public:

    // creates an instance of OneWayDescriptor from a set of training files
    // - patch_size: size of the input (large) patch
    // - pose_count: the number of poses to generate for each descriptor
    // - train_path: path to training files
    // - pca_config: the name of the file that contains PCA for small patches (2 times smaller
    // than patch_size each dimension
    // - pca_hr_config: the name of the file that contains PCA for large patches (of patch_size size)
    // - pca_desc_config: the name of the file that contains descriptors of PCA components
    OneWayDescriptorBase(CvSize patch_size, int pose_count, const char* train_path = 0, const char* pca_config = 0,
                        const char* pca_hr_config = 0, const char* pca_desc_config = 0, int pyr_levels = 1,
                        int pca_dim_high = 100, int pca_dim_low = 100);

    OneWayDescriptorBase(CvSize patch_size, int pose_count, const string &pca_filename, const string &train_path = string(), const string &images_list = string(),
                        float _scale_min = 0.7f, float _scale_max=1.5f, float _scale_step=1.2f, int pyr_levels = 1,
                        int pca_dim_high = 100, int pca_dim_low = 100);


    virtual ~OneWayDescriptorBase();
    void clear ();


    // Allocate: allocates memory for a given number of descriptors
    void Allocate(int train_feature_count);

    // AllocatePCADescriptors: allocates memory for pca descriptors
    void AllocatePCADescriptors();

    // returns patch size
    CvSize GetPatchSize() const {return m_patch_size;};
    // returns the number of poses for each descriptor
    int GetPoseCount() const {return m_pose_count;};

    // returns the number of pyramid levels
    int GetPyrLevels() const {return m_pyr_levels;};

    // returns the number of descriptors
    int GetDescriptorCount() const {return m_train_feature_count;};

    // CreateDescriptorsFromImage: creates descriptors for each of the input features
    // - src: input image
    // - features: input features
    // - pyr_levels: the number of pyramid levels
    void CreateDescriptorsFromImage(IplImage* src, const vector<KeyPoint>& features);

    // CreatePCADescriptors: generates descriptors for PCA components, needed for fast generation of feature descriptors
    void CreatePCADescriptors();

    // returns a feature descriptor by feature index
    const OneWayDescriptor* GetDescriptor(int desc_idx) const {return &m_descriptors[desc_idx];};

    // FindDescriptor: finds the closest descriptor
    // - patch: input image patch
    // - desc_idx: output index of the closest descriptor to the input patch
    // - pose_idx: output index of the closest pose of the closest descriptor to the input patch
    // - distance: distance from the input patch to the closest feature pose
    // - _scales: scales of the input patch for each descriptor
    // - scale_ranges: input scales variation (float[2])
    void FindDescriptor(IplImage* patch, int& desc_idx, int& pose_idx, float& distance, float* _scale = 0, float* scale_ranges = 0) const;

    // - patch: input image patch
    // - n: number of the closest indexes
    // - desc_idxs: output indexes of the closest descriptor to the input patch (n)
    // - pose_idx: output indexes of the closest pose of the closest descriptor to the input patch (n)
    // - distances: distance from the input patch to the closest feature pose (n)
    // - _scales: scales of the input patch
    // - scale_ranges: input scales variation (float[2])
    void FindDescriptor(IplImage* patch, int n, vector<int>& desc_idxs, vector<int>& pose_idxs,
                        vector<float>& distances, vector<float>& _scales, float* scale_ranges = 0) const;

    // FindDescriptor: finds the closest descriptor
    // - src: input image
    // - pt: center of the feature
    // - desc_idx: output index of the closest descriptor to the input patch
    // - pose_idx: output index of the closest pose of the closest descriptor to the input patch
    // - distance: distance from the input patch to the closest feature pose
    void FindDescriptor(IplImage* src, cv::Point2f pt, int& desc_idx, int& pose_idx, float& distance) const;

    // InitializePoses: generates random poses
    void InitializePoses();

    // InitializeTransformsFromPoses: generates 2x3 affine matrices from poses (initializes m_transforms)
    void InitializeTransformsFromPoses();

    // InitializePoseTransforms: subsequently calls InitializePoses and InitializeTransformsFromPoses
    void InitializePoseTransforms();

    // InitializeDescriptor: initializes a descriptor
    // - desc_idx: descriptor index
    // - train_image: image patch (ROI is supported)
    // - feature_label: feature textual label
    void InitializeDescriptor(int desc_idx, IplImage* train_image, const char* feature_label);

    void InitializeDescriptor(int desc_idx, IplImage* train_image, const KeyPoint& keypoint, const char* feature_label);

    // InitializeDescriptors: load features from an image and create descriptors for each of them
    void InitializeDescriptors(IplImage* train_image, const vector<KeyPoint>& features,
                              const char* feature_label = "", int desc_start_idx = 0);

    // Write: writes this object to a file storage
    // - fs: output filestorage
    void Write (FileStorage &fs) const;

    // Read: reads OneWayDescriptorBase object from a file node
    // - fn: input file node
    void Read (const FileNode &fn);

    // LoadPCADescriptors: loads PCA descriptors from a file
    // - filename: input filename
    int LoadPCADescriptors(const char* filename);

    // LoadPCADescriptors: loads PCA descriptors from a file node
    // - fn: input file node
    int LoadPCADescriptors(const FileNode &fn);

    // SavePCADescriptors: saves PCA descriptors to a file
    // - filename: output filename
    void SavePCADescriptors(const char* filename);

    // SavePCADescriptors: saves PCA descriptors to a file storage
    // - fs: output file storage
    void SavePCADescriptors(CvFileStorage* fs) const;

    // GeneratePCA: calculate and save PCA components and descriptors
    // - img_path: path to training PCA images directory
    // - images_list: filename with filenames of training PCA images
    void GeneratePCA(const char* img_path, const char* images_list, int pose_count=500);

    // SetPCAHigh: sets the high resolution pca matrices (copied to internal structures)
    void SetPCAHigh(CvMat* avg, CvMat* eigenvectors);

    // SetPCALow: sets the low resolution pca matrices (copied to internal structures)
    void SetPCALow(CvMat* avg, CvMat* eigenvectors);

    int GetLowPCA(CvMat** avg, CvMat** eigenvectors)
    {
        *avg = m_pca_avg;
        *eigenvectors = m_pca_eigenvectors;
        return m_pca_dim_low;
    };

    int GetPCADimLow() const {return m_pca_dim_low;};
    int GetPCADimHigh() const {return m_pca_dim_high;};

    void ConvertDescriptorsArrayToTree(); // Converting pca_descriptors array to KD tree

    // GetPCAFilename: get default PCA filename
    static string GetPCAFilename () { return "pca.yml"; }

    virtual bool empty() const { return m_train_feature_count <= 0 ? true : false; }

protected:
    ...
};

OneWayDescriptorMatcher

class OneWayDescriptorMatcher : public GenericDescriptorMatcher

Wrapping class for computing, matching, and classifying descriptors using the OneWayDescriptorBase class.

class OneWayDescriptorMatcher : public GenericDescriptorMatcher
{
public:
    class Params
    {
    public:
        static const int POSE_COUNT = 500;
        static const int PATCH_WIDTH = 24;
        static const int PATCH_HEIGHT = 24;
        static float GET_MIN_SCALE() { return 0.7f; }
        static float GET_MAX_SCALE() { return 1.5f; }
        static float GET_STEP_SCALE() { return 1.2f; }

        Params( int poseCount = POSE_COUNT,
                Size patchSize = Size(PATCH_WIDTH, PATCH_HEIGHT),
                string pcaFilename = string(),
                string trainPath = string(), string trainImagesList = string(),
                float minScale = GET_MIN_SCALE(), float maxScale = GET_MAX_SCALE(),
                float stepScale = GET_STEP_SCALE() );

        int poseCount;
        Size patchSize;
        string pcaFilename;
        string trainPath;
        string trainImagesList;

        float minScale, maxScale, stepScale;
    };

    OneWayDescriptorMatcher( const Params& params=Params() );
    virtual ~OneWayDescriptorMatcher();

    void initialize( const Params& params, const Ptr<OneWayDescriptorBase>& base=Ptr<OneWayDescriptorBase>() );

    // Clears keypoints stored in collection and OneWayDescriptorBase
    virtual void clear();

    virtual void train();

    virtual bool isMaskSupported();

    virtual void read( const FileNode &fn );
    virtual void write( FileStorage& fs ) const;

    virtual Ptr<GenericDescriptorMatcher> clone( bool emptyTrainData=false ) const;
protected:
    ...
};

FernClassifier

class FernClassifier

class CV_EXPORTS FernClassifier
{
public:
    FernClassifier();
    FernClassifier(const FileNode& node);
    FernClassifier(const vector<vector<Point2f> >& points,
                  const vector<Mat>& refimgs,
                  const vector<vector<int> >& labels=vector<vector<int> >(),
                  int _nclasses=0, int _patchSize=PATCH_SIZE,
                  int _signatureSize=DEFAULT_SIGNATURE_SIZE,
                  int _nstructs=DEFAULT_STRUCTS,
                  int _structSize=DEFAULT_STRUCT_SIZE,
                  int _nviews=DEFAULT_VIEWS,
                  int _compressionMethod=COMPRESSION_NONE,
                  const PatchGenerator& patchGenerator=PatchGenerator());
    virtual ~FernClassifier();
    virtual void read(const FileNode& n);
    virtual void write(FileStorage& fs, const String& name=String()) const;
    virtual void trainFromSingleView(const Mat& image,
                                    const vector<KeyPoint>& keypoints,
                                    int _patchSize=PATCH_SIZE,
                                    int _signatureSize=DEFAULT_SIGNATURE_SIZE,
                                    int _nstructs=DEFAULT_STRUCTS,
                                    int _structSize=DEFAULT_STRUCT_SIZE,
                                    int _nviews=DEFAULT_VIEWS,
                                    int _compressionMethod=COMPRESSION_NONE,
                                    const PatchGenerator& patchGenerator=PatchGenerator());
    virtual void train(const vector<vector<Point2f> >& points,
                      const vector<Mat>& refimgs,
                      const vector<vector<int> >& labels=vector<vector<int> >(),
                      int _nclasses=0, int _patchSize=PATCH_SIZE,
                      int _signatureSize=DEFAULT_SIGNATURE_SIZE,
                      int _nstructs=DEFAULT_STRUCTS,
                      int _structSize=DEFAULT_STRUCT_SIZE,
                      int _nviews=DEFAULT_VIEWS,
                      int _compressionMethod=COMPRESSION_NONE,
                      const PatchGenerator& patchGenerator=PatchGenerator());
    virtual int operator()(const Mat& img, Point2f kpt, vector<float>& signature) const;
    virtual int operator()(const Mat& patch, vector<float>& signature) const;
    virtual void clear();
    virtual bool empty() const;
    void setVerbose(bool verbose);

    int getClassCount() const;
    int getStructCount() const;
    int getStructSize() const;
    int getSignatureSize() const;
    int getCompressionMethod() const;
    Size getPatchSize() const;

    struct Feature
    {
        uchar x1, y1, x2, y2;
        Feature() : x1(0), y1(0), x2(0), y2(0) {}
        Feature(int _x1, int _y1, int _x2, int _y2)
        : x1((uchar)_x1), y1((uchar)_y1), x2((uchar)_x2), y2((uchar)_y2)
        {}
        template<typename _Tp> bool operator ()(const Mat_<_Tp>& patch) const
        { return patch(y1,x1) > patch(y2, x2); }
    };

    enum
    {
        PATCH_SIZE = 31,
        DEFAULT_STRUCTS = 50,
        DEFAULT_STRUCT_SIZE = 9,
        DEFAULT_VIEWS = 5000,
        DEFAULT_SIGNATURE_SIZE = 176,
        COMPRESSION_NONE = 0,
        COMPRESSION_RANDOM_PROJ = 1,
        COMPRESSION_PCA = 2,
        DEFAULT_COMPRESSION_METHOD = COMPRESSION_NONE
    };

protected:
    ...
};

FernDescriptorMatcher

class FernDescriptorMatcher : public GenericDescriptorMatcher

Wrapping class for computing, matching, and classifying descriptors using the FernClassifier class.

class FernDescriptorMatcher : public GenericDescriptorMatcher
{
public:
    class Params
    {
    public:
        Params( int nclasses=0,
                int patchSize=FernClassifier::PATCH_SIZE,
                int signatureSize=FernClassifier::DEFAULT_SIGNATURE_SIZE,
                int nstructs=FernClassifier::DEFAULT_STRUCTS,
                int structSize=FernClassifier::DEFAULT_STRUCT_SIZE,
                int nviews=FernClassifier::DEFAULT_VIEWS,
                int compressionMethod=FernClassifier::COMPRESSION_NONE,
                const PatchGenerator& patchGenerator=PatchGenerator() );

        Params( const string& filename );

        int nclasses;
        int patchSize;
        int signatureSize;
        int nstructs;
        int structSize;
        int nviews;
        int compressionMethod;
        PatchGenerator patchGenerator;

        string filename;
    };

    FernDescriptorMatcher( const Params& params=Params() );
    virtual ~FernDescriptorMatcher();

    virtual void clear();

    virtual void train();

    virtual bool isMaskSupported();

    virtual void read( const FileNode &fn );
    virtual void write( FileStorage& fs ) const;

    virtual Ptr<GenericDescriptorMatcher> clone( bool emptyTrainData=false ) const;

protected:
        ...
};