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object --+ | ??.instance --+ | CvStatModel --+ | CvDTree --+ | CvForestTree
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Inherited from Inherited from Inherited from Inherited from |
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__instance_size__ = 40
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Inherited from Inherited from |
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__init__( (object)arg1) -> None : C++ signature : void __init__(_object*)
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calc_error( (CvForestTree)arg1, (CvMLData)_data, (object)type [, (vector_float32)resp=None]) -> float : C++ signature : float calc_error(CvForestTree {lvalue},CvMLData*,int [,std::vector<float, std::allocator<float> >*=None]) calc_error( (CvForestTree)arg1, (CvMLData)_data, (object)type [, (vector_float32)resp=None]) -> float : C++ signature : float calc_error(CvForestTree_wrapper {lvalue},CvMLData*,int [,std::vector<float, std::allocator<float> >*=None])
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clear( (CvForestTree)arg1) -> None : C++ signature : void clear(CvForestTree {lvalue}) clear( (CvForestTree)arg1) -> None : C++ signature : void clear(CvForestTree_wrapper {lvalue})
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get_var_count( (CvForestTree)arg1) -> int : C++ signature : int get_var_count(CvForestTree {lvalue}) get_var_count( (CvForestTree)arg1) -> int : C++ signature : int get_var_count(CvForestTree_wrapper {lvalue}) |
get_var_importance( (CvForestTree)arg1) -> CvMat : C++ signature : CvMat const* get_var_importance(CvForestTree {lvalue}) get_var_importance( (CvForestTree)arg1) -> CvMat : C++ signature : CvMat const* get_var_importance(CvForestTree_wrapper {lvalue})
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load( (CvForestTree)arg1, (str)filename [, (str)name=None]) -> None : C++ signature : void load(CvForestTree {lvalue},char const* [,char const*=None]) load( (CvForestTree)arg1, (str)filename [, (str)name=None]) -> None : C++ signature : void load(CvForestTree_wrapper {lvalue},char const* [,char const*=None])
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predict( (CvDTree)inst, (Mat)_sample [, (Mat)_missing_data_mask=Mat() [, (bool)preprocessed_input=False]]) -> object : Argument '_sample': C++ type: ::CvMat const * Python type: Mat Argument '_missing_data_mask': C++ type: ::CvMat const * Python type: Mat C++ signature : boost::python::api::object predict(CvDTree,cv::Mat {lvalue} [,cv::Mat=Mat() [,bool=False]]) predict( (CvForestTree)arg1, (Mat)_sample [, (Mat)_missing_data_mask=Mat() [, (bool)preprocessed_input=False]]) -> object : C++ signature : CvDTreeNode* predict(CvForestTree {lvalue},cv::Mat [,cv::Mat=Mat() [,bool=False]]) predict( (CvForestTree)arg1, (Mat)_sample [, (Mat)_missing_data_mask=Mat() [, (bool)preprocessed_input=False]]) -> object : C++ signature : CvDTreeNode* predict(CvForestTree_wrapper {lvalue},cv::Mat [,cv::Mat=Mat() [,bool=False]])
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read_21f4d9d118da24ef774e945ac72443bf( (CvForestTree)inst, (FileStorage)fs, (FileNode)node) -> None : Wrapped function: read Argument 'fs': C++ type: ::CvFileStorage * Python type: FileStorage Argument 'node': C++ type: ::CvFileNode * Python type: FileNode C++ signature : void read_21f4d9d118da24ef774e945ac72443bf(CvForestTree {lvalue},cv::FileStorage {lvalue},cv::FileNode {lvalue}) |
read_8d6757d6bbd70f87efa21a9a88d7b91b( (CvForestTree)inst, (FileStorage)fs, (FileNode)node, (CvRTrees)forest, (CvDTreeTrainData)_data) -> None : Wrapped function: read Argument 'fs': C++ type: ::CvFileStorage * Python type: FileStorage Argument 'node': C++ type: ::CvFileNode * Python type: FileNode C++ signature : void read_8d6757d6bbd70f87efa21a9a88d7b91b(CvForestTree {lvalue},cv::FileStorage {lvalue},cv::FileNode {lvalue},CvRTrees*,CvDTreeTrainData*) |
read_f1eddefe30282eed3e835c344b312841( (CvForestTree)inst, (FileStorage)fs, (FileNode)node, (CvDTreeTrainData)data) -> None : Wrapped function: read Argument 'fs': C++ type: ::CvFileStorage * Python type: FileStorage Argument 'node': C++ type: ::CvFileNode * Python type: FileNode C++ signature : void read_f1eddefe30282eed3e835c344b312841(CvForestTree {lvalue},cv::FileStorage {lvalue},cv::FileNode {lvalue},CvDTreeTrainData*) |
save( (CvForestTree)arg1, (str)filename [, (str)name=None]) -> None : C++ signature : void save(CvForestTree {lvalue},char const* [,char const*=None]) save( (CvForestTree)arg1, (str)filename [, (str)name=None]) -> None : C++ signature : void save(CvForestTree_wrapper {lvalue},char const* [,char const*=None])
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train( (CvForestTree)inst, (CvDTreeTrainData)_train_data, (Mat)_subsample_idx, (CvRTrees)forest) -> object : Argument '_subsample_idx': C++ type: ::CvMat const * Python type: Mat C++ signature : boost::python::api::object train(CvForestTree {lvalue},CvDTreeTrainData*,cv::Mat {lvalue},CvRTrees*) train( (CvForestTree)inst, (Mat)_train_data, (object)_tflag, (Mat)_responses [, (Mat)_var_idx=Mat() [, (Mat)_sample_idx=Mat() [, (Mat)_var_type=Mat() [, (Mat)_missing_mask=Mat() [, (CvDTreeParams)params=<pyopencv.ml_ext.CvDTreeParams object at 0x021E25D0>]]]]]) -> 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(CvForestTree {lvalue},cv::Mat {lvalue},int,cv::Mat {lvalue} [,cv::Mat=Mat() [,cv::Mat=Mat() [,cv::Mat=Mat() [,cv::Mat=Mat() [,CvDTreeParams=<pyopencv.ml_ext.CvDTreeParams object at 0x021E25D0>]]]]]) train( (CvForestTree)inst, (CvDTreeTrainData)_train_data, (Mat)_subsample_idx) -> object : Argument '_subsample_idx': C++ type: ::CvMat const * Python type: Mat C++ signature : boost::python::api::object train(CvForestTree {lvalue},CvDTreeTrainData*,cv::Mat {lvalue}) train( (CvForestTree)arg1, (CvMLData)_data [, (CvDTreeParams)_params=<pyopencv.ml_ext.CvDTreeParams object at 0x021E2580>]) -> bool : C++ signature : bool train(CvForestTree {lvalue},CvMLData* [,CvDTreeParams=<pyopencv.ml_ext.CvDTreeParams object at 0x021E2580>]) train( (CvForestTree)arg1, (CvMLData)_data [, (CvDTreeParams)_params=<pyopencv.ml_ext.CvDTreeParams object at 0x021E2580>]) -> bool : C++ signature : bool train(CvForestTree_wrapper {lvalue},CvMLData* [,CvDTreeParams=<pyopencv.ml_ext.CvDTreeParams object at 0x021E2580>]) train( (CvForestTree)arg1, (Mat)_train_data, (object)_tflag, (Mat)_responses [, (Mat)_var_idx=Mat() [, (Mat)_sample_idx=Mat() [, (Mat)_var_type=Mat() [, (Mat)_missing_mask=Mat() [, (CvDTreeParams)params=<pyopencv.ml_ext.CvDTreeParams object at 0x021E2530>]]]]]) -> bool : C++ signature : bool train(CvForestTree {lvalue},cv::Mat,int,cv::Mat [,cv::Mat=Mat() [,cv::Mat=Mat() [,cv::Mat=Mat() [,cv::Mat=Mat() [,CvDTreeParams=<pyopencv.ml_ext.CvDTreeParams object at 0x021E2530>]]]]]) train( (CvForestTree)arg1, (Mat)_train_data, (object)_tflag, (Mat)_responses [, (Mat)_var_idx=Mat() [, (Mat)_sample_idx=Mat() [, (Mat)_var_type=Mat() [, (Mat)_missing_mask=Mat() [, (CvDTreeParams)params=<pyopencv.ml_ext.CvDTreeParams object at 0x021E2530>]]]]]) -> bool : C++ signature : bool train(CvForestTree_wrapper {lvalue},cv::Mat,int,cv::Mat [,cv::Mat=Mat() [,cv::Mat=Mat() [,cv::Mat=Mat() [,cv::Mat=Mat() [,CvDTreeParams=<pyopencv.ml_ext.CvDTreeParams object at 0x021E2530>]]]]])
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write_d1e064f966d50e01902f80ef0f045741( (CvDTree)inst, (FileStorage)fs) -> None : Wrapped function: write Argument 'fs': C++ type: ::CvFileStorage * Python type: FileStorage C++ signature : void write_d1e064f966d50e01902f80ef0f045741(CvDTree,cv::FileStorage {lvalue}) |
write_d5b05f94ebb65d268cbd4756fe0d6221( (CvDTree)inst, (FileStorage)fs, (str)name) -> None : Wrapped function: write Argument 'fs': C++ type: ::CvFileStorage * Python type: FileStorage C++ signature : void write_d5b05f94ebb65d268cbd4756fe0d6221(CvDTree,cv::FileStorage {lvalue},char const*) |
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