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PyOpenCV
Package pyopencv :: Module ml_ext :: Class CvRTrees
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Class CvRTrees

 object --+        
          |        
??.instance --+    
              |    
    CvStatModel --+
                  |
                 CvRTrees
Known Subclasses:
Instance Methods [hide private]
 
__init__(...)
__init__( (object)arg1) -> None :
 
calc_error(...)
calc_error( (CvRTrees)arg1, (CvMLData)_data, (object)type [, (vector_float32)resp=None]) -> float :
 
clear(...)
clear( (CvRTrees)arg1) -> None :
 
get_active_var_mask(...)
get_active_var_mask( (CvRTrees)arg1) -> CvMat :
 
get_proximity(...)
get_proximity( (CvRTrees)inst, (Mat)sample1, (Mat)sample2 [, (Mat)missing1=Mat() [, (Mat)missing2=Mat()]]) -> object :
 
get_train_error(...)
get_train_error( (CvRTrees)arg1) -> float :
 
get_tree(...)
get_tree( (CvRTrees)arg1, (object)i) -> CvForestTree :
 
get_tree_count(...)
get_tree_count( (CvRTrees)arg1) -> int :
 
get_var_importance(...)
get_var_importance( (CvRTrees)arg1) -> CvMat :
 
load(...)
load( (CvRTrees)arg1, (str)filename [, (str)name=None]) -> None :
 
predict(...)
predict( (CvRTrees)inst, (Mat)sample [, (Mat)missing=Mat()]) -> object :
 
predict_prob(...)
predict_prob( (CvRTrees)inst, (Mat)sample [, (Mat)missing=Mat()]) -> object :
 
read(...)
read( (CvRTrees)inst, (FileStorage)fs, (FileNode)node) -> None :
 
save(...)
save( (CvRTrees)arg1, (str)filename [, (str)name=None]) -> None :
 
train(...)
train( (CvRTrees)inst, (Mat)_train_data, (object)_tflag, (Mat)_responses [, (Mat)_var_idx=Mat() [, (Mat)_sample_idx=Mat() [, (Mat)_var_type=Mat() [, (Mat)_missing_mask=Mat() [, (CvRTParams)params=<pyopencv.ml_ext.CvRTParams object at 0x020417A0>]]]]]) -> object :
 
write(...)
write( (CvRTrees)inst, (FileStorage)fs, (str)name) -> None :

Inherited from CvStatModel: __reduce__

Inherited from unreachable.instance: __new__

Inherited from object: __delattr__, __format__, __getattribute__, __hash__, __reduce_ex__, __repr__, __setattr__, __sizeof__, __str__, __subclasshook__

Class Variables [hide private]
  __instance_size__ = 64
Properties [hide private]
  this

Inherited from object: __class__

Method Details [hide private]

__init__(...)
(Constructor)

  

__init__( (object)arg1) -> None :

    C++ signature :
        void __init__(_object*)
Overrides: object.__init__

calc_error(...)

  

calc_error( (CvRTrees)arg1, (CvMLData)_data, (object)type [, (vector_float32)resp=None]) -> float :

    C++ signature :
        float calc_error(CvRTrees {lvalue},CvMLData*,int [,std::vector<float, std::allocator<float> >*=None])

calc_error( (CvRTrees)arg1, (CvMLData)_data, (object)type [, (vector_float32)resp=None]) -> float :

    C++ signature :
        float calc_error(CvRTrees_wrapper {lvalue},CvMLData*,int [,std::vector<float, std::allocator<float> >*=None])

clear(...)

  

clear( (CvRTrees)arg1) -> None :

    C++ signature :
        void clear(CvRTrees {lvalue})

clear( (CvRTrees)arg1) -> None :

    C++ signature :
        void clear(CvRTrees_wrapper {lvalue})
Overrides: CvStatModel.clear

get_active_var_mask(...)

  

get_active_var_mask( (CvRTrees)arg1) -> CvMat :

    C++ signature :
        CvMat* get_active_var_mask(CvRTrees {lvalue})

get_proximity(...)

  

get_proximity( (CvRTrees)inst, (Mat)sample1, (Mat)sample2 [, (Mat)missing1=Mat() [, (Mat)missing2=Mat()]]) -> object :
    
    Argument 'sample1':
        C++ type: ::CvMat const *
        Python type: Mat
    Argument 'sample2':
        C++ type: ::CvMat const *
        Python type: Mat
    Argument 'missing1':
        C++ type: ::CvMat const *
        Python type: Mat
    Argument 'missing2':
        C++ type: ::CvMat const *
        Python type: Mat

    C++ signature :
        boost::python::api::object get_proximity(CvRTrees,cv::Mat {lvalue},cv::Mat {lvalue} [,cv::Mat=Mat() [,cv::Mat=Mat()]])

get_train_error(...)

  

get_train_error( (CvRTrees)arg1) -> float :

    C++ signature :
        float get_train_error(CvRTrees {lvalue})

get_train_error( (CvRTrees)arg1) -> float :

    C++ signature :
        float get_train_error(CvRTrees_wrapper {lvalue})

get_tree(...)

  

get_tree( (CvRTrees)arg1, (object)i) -> CvForestTree :

    C++ signature :
        CvForestTree* get_tree(CvRTrees {lvalue},int)

get_tree_count(...)

  

get_tree_count( (CvRTrees)arg1) -> int :

    C++ signature :
        int get_tree_count(CvRTrees {lvalue})

get_var_importance(...)

  

get_var_importance( (CvRTrees)arg1) -> CvMat :

    C++ signature :
        CvMat const* get_var_importance(CvRTrees {lvalue})

get_var_importance( (CvRTrees)arg1) -> CvMat :

    C++ signature :
        CvMat const* get_var_importance(CvRTrees_wrapper {lvalue})

load(...)

  

load( (CvRTrees)arg1, (str)filename [, (str)name=None]) -> None :

    C++ signature :
        void load(CvRTrees {lvalue},char const* [,char const*=None])

load( (CvRTrees)arg1, (str)filename [, (str)name=None]) -> None :

    C++ signature :
        void load(CvRTrees_wrapper {lvalue},char const* [,char const*=None])
Overrides: CvStatModel.load

predict(...)

  

predict( (CvRTrees)inst, (Mat)sample [, (Mat)missing=Mat()]) -> object :
    
    Argument 'sample':
        C++ type: ::CvMat const *
        Python type: Mat
    Argument 'missing':
        C++ type: ::CvMat const *
        Python type: Mat

    C++ signature :
        boost::python::api::object predict(CvRTrees,cv::Mat {lvalue} [,cv::Mat=Mat()])

predict( (CvRTrees)arg1, (Mat)sample [, (Mat)missing=Mat()]) -> float :

    C++ signature :
        float predict(CvRTrees {lvalue},cv::Mat [,cv::Mat=Mat()])

predict( (CvRTrees)arg1, (Mat)sample [, (Mat)missing=Mat()]) -> float :

    C++ signature :
        float predict(CvRTrees_wrapper {lvalue},cv::Mat [,cv::Mat=Mat()])

predict_prob(...)

  

predict_prob( (CvRTrees)inst, (Mat)sample [, (Mat)missing=Mat()]) -> object :
    
    Argument 'sample':
        C++ type: ::CvMat const *
        Python type: Mat
    Argument 'missing':
        C++ type: ::CvMat const *
        Python type: Mat

    C++ signature :
        boost::python::api::object predict_prob(CvRTrees,cv::Mat {lvalue} [,cv::Mat=Mat()])

predict_prob( (CvRTrees)arg1, (Mat)sample [, (Mat)missing=Mat()]) -> float :

    C++ signature :
        float predict_prob(CvRTrees {lvalue},cv::Mat [,cv::Mat=Mat()])

predict_prob( (CvRTrees)arg1, (Mat)sample [, (Mat)missing=Mat()]) -> float :

    C++ signature :
        float predict_prob(CvRTrees_wrapper {lvalue},cv::Mat [,cv::Mat=Mat()])

read(...)

  

read( (CvRTrees)inst, (FileStorage)fs, (FileNode)node) -> None :
    
    Argument 'fs':
        C++ type: ::CvFileStorage *
        Python type: FileStorage
    Argument 'node':
        C++ type: ::CvFileNode *
        Python type: FileNode

    C++ signature :
        void read(CvRTrees {lvalue},cv::FileStorage {lvalue},cv::FileNode {lvalue})
Overrides: CvStatModel.read

save(...)

  

save( (CvRTrees)arg1, (str)filename [, (str)name=None]) -> None :

    C++ signature :
        void save(CvRTrees {lvalue},char const* [,char const*=None])

save( (CvRTrees)arg1, (str)filename [, (str)name=None]) -> None :

    C++ signature :
        void save(CvRTrees_wrapper {lvalue},char const* [,char const*=None])
Overrides: CvStatModel.save

train(...)

  

train( (CvRTrees)inst, (Mat)_train_data, (object)_tflag, (Mat)_responses [, (Mat)_var_idx=Mat() [, (Mat)_sample_idx=Mat() [, (Mat)_var_type=Mat() [, (Mat)_missing_mask=Mat() [, (CvRTParams)params=<pyopencv.ml_ext.CvRTParams object at 0x020417A0>]]]]]) -> object :
    
    Argument '_train_data':
        C++ type: ::CvMat const *
        Python type: Mat
    Argument '_responses':
        C++ type: ::CvMat const *
        Python type: Mat
    Argument '_var_idx':
        C++ type: ::CvMat const *
        Python type: Mat
    Argument '_sample_idx':
        C++ type: ::CvMat const *
        Python type: Mat
    Argument '_var_type':
        C++ type: ::CvMat const *
        Python type: Mat
    Argument '_missing_mask':
        C++ type: ::CvMat const *
        Python type: Mat

    C++ signature :
        boost::python::api::object train(CvRTrees {lvalue},cv::Mat {lvalue},int,cv::Mat {lvalue} [,cv::Mat=Mat() [,cv::Mat=Mat() [,cv::Mat=Mat() [,cv::Mat=Mat() [,CvRTParams=<pyopencv.ml_ext.CvRTParams object at 0x020417A0>]]]]])

train( (CvRTrees)arg1, (CvMLData)data [, (CvRTParams)params=<pyopencv.ml_ext.CvRTParams object at 0x02041730>]) -> bool :

    C++ signature :
        bool train(CvRTrees {lvalue},CvMLData* [,CvRTParams=<pyopencv.ml_ext.CvRTParams object at 0x02041730>])

train( (CvRTrees)arg1, (CvMLData)data [, (CvRTParams)params=<pyopencv.ml_ext.CvRTParams object at 0x02041730>]) -> bool :

    C++ signature :
        bool train(CvRTrees_wrapper {lvalue},CvMLData* [,CvRTParams=<pyopencv.ml_ext.CvRTParams object at 0x02041730>])

train( (CvRTrees)arg1, (Mat)_train_data, (object)_tflag, (Mat)_responses [, (Mat)_var_idx=Mat() [, (Mat)_sample_idx=Mat() [, (Mat)_var_type=Mat() [, (Mat)_missing_mask=Mat() [, (CvRTParams)params=<pyopencv.ml_ext.CvRTParams object at 0x020416C0>]]]]]) -> bool :

    C++ signature :
        bool train(CvRTrees {lvalue},cv::Mat,int,cv::Mat [,cv::Mat=Mat() [,cv::Mat=Mat() [,cv::Mat=Mat() [,cv::Mat=Mat() [,CvRTParams=<pyopencv.ml_ext.CvRTParams object at 0x020416C0>]]]]])

train( (CvRTrees)arg1, (Mat)_train_data, (object)_tflag, (Mat)_responses [, (Mat)_var_idx=Mat() [, (Mat)_sample_idx=Mat() [, (Mat)_var_type=Mat() [, (Mat)_missing_mask=Mat() [, (CvRTParams)params=<pyopencv.ml_ext.CvRTParams object at 0x020416C0>]]]]]) -> bool :

    C++ signature :
        bool train(CvRTrees_wrapper {lvalue},cv::Mat,int,cv::Mat [,cv::Mat=Mat() [,cv::Mat=Mat() [,cv::Mat=Mat() [,cv::Mat=Mat() [,CvRTParams=<pyopencv.ml_ext.CvRTParams object at 0x020416C0>]]]]])

write(...)

  

write( (CvRTrees)inst, (FileStorage)fs, (str)name) -> None :
    
    Argument 'fs':
        C++ type: ::CvFileStorage *
        Python type: FileStorage

    C++ signature :
        void write(CvRTrees,cv::FileStorage {lvalue},char const*)
Overrides: CvStatModel.write

Property Details [hide private]

this

Get Method:
unreachable(...)

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