Class: OpenCV::CvSVM

Inherits:
Object
  • Object
show all
Extended by:
FFI::DataConverter
Defined in:
lib/ropencv/ropencv_types.rb

Constants collapse

C_SVC = 
100
NU_SVC = 
101
ONE_CLASS = 
102
EPS_SVR = 
103
NU_SVR = 
104
LINEAR = 
0
POLY = 
1
RBF = 
2
SIGMOID = 
3
C = 
0
GAMMA = 
1
P = 
2
NU = 
3
COEF = 
4
DEGREE = 
5

Class Method Summary collapse

Instance Method Summary collapse

Class Method Details

.cast_from_cv_stat_model(ptr) ⇒ CvSVM Also known as: castFromCvStatModel

Note:

wrapper for static method CvSVM* CvSVM::castFromCvStatModel(CvStatModel* ptr)

Parameters:

Returns:



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# File 'lib/ropencv/ropencv_types.rb', line 42953

def self.cast_from_cv_stat_model(ptr)
    Rbind::cvsvm_cast_from_cv_stat_model(ptr)
end

.cvsvm ⇒ Object .cvsvm(train_data, responses, var_idx = Cv::Mat.new(), sample_idx = Cv::Mat.new(), params = CvSVMParams.new()) ⇒ Object

Overloads:

  • .cvsvm(train_data, responses, var_idx = Cv::Mat.new(), sample_idx = Cv::Mat.new(), params = CvSVMParams.new()) ⇒ Object

    Parameters:

Raises:

  • (ArgumentError) 


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# File 'lib/ropencv/ropencv_types.rb', line 42742

def self.new(*args)
    if args.first.is_a?(FFI::Pointer) || args.first.is_a?(CvSVMStruct)
        raise ArgumentError, "too many arguments for creating #{self.name} from Pointer" unless args.size == 1
        return super(args.first)
    end
    # overloaded method wrapper for CvSVM::CvSVM()
    @@cvsvm_cvsvm_defaults0 ||= []
    if(args.size >= 0 && args.size <= 0)
        targs = args.clone
        targs.size.upto(-1) do |i|
            targs[i] = @@cvsvm_cvsvm_defaults0[i]
        end
        begin
                return Rbind::cvsvm_cvsvm(*targs)
        rescue TypeError => e
            @error = e
        end
    end

    # overloaded method wrapper for CvSVM::CvSVM(const cv::Mat trainData, const cv::Mat responses, const cv::Mat varIdx = cv::Mat(), const cv::Mat sampleIdx = cv::Mat(), const CvSVMParams params = CvSVMParams())
    @@cvsvm_cvsvm2_defaults1 ||= [nil, nil, Cv::Mat.new(), Cv::Mat.new(), CvSVMParams.new()]
    if(args.size >= 2 && args.size <= 5)
        targs = args.clone
        targs.size.upto(4) do |i|
            targs[i] = @@cvsvm_cvsvm2_defaults1[i]
        end
        begin
                return Rbind::cvsvm_cvsvm2(*targs)
        rescue TypeError => e
            @error = e
        end
    end

    raise ArgumentError, "no constructor for #{self}(#{args.inspect})"
end

.null ⇒ Object

returns a null pointer to the object



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# File 'lib/ropencv/ropencv_types.rb', line 42730

def self.null
    new(CvSVMStruct.new)
end

Instance Method Details

#cast_to_cv_stat_model ⇒ CvStatModel Also known as: castToCvStatModel

Note:

method wrapper for CvStatModel* CvSVM::castToCvStatModel()

Returns:



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# File 'lib/ropencv/ropencv_types.rb', line 42939

def cast_to_cv_stat_model()
    __validate_pointer__
    result = Rbind::cvsvm_cast_to_cv_stat_model( self)
    if result.respond_to?(:__owner__?) && !result.__owner__?
    # store owner insight the pointer to not get garbage collected
        result.instance_variable_get(:@__obj_ptr__).instance_variable_set(:@__owner__,self) 
    end
    result
end

#clear ⇒ Void

Note:

method wrapper for void CvSVM::clear()

Returns:

  • (Void) 


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# File 'lib/ropencv/ropencv_types.rb', line 42925

def clear()
    __validate_pointer__
    Rbind::cvsvm_clear( self)
end

#get_support_vector_count ⇒ Fixnum

Note:

method wrapper for int CvSVM::get_support_vector_count()

Returns:

  • (Fixnum) 


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# File 'lib/ropencv/ropencv_types.rb', line 42918

def get_support_vector_count()
    __validate_pointer__
    Rbind::cvsvm_get_support_vector_count( self)
end

#get_var_count ⇒ Fixnum

Note:

method wrapper for int CvSVM::get_var_count()

Returns:

  • (Fixnum) 


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# File 'lib/ropencv/ropencv_types.rb', line 42932

def get_var_count()
    __validate_pointer__
    Rbind::cvsvm_get_var_count( self)
end

#load(filename, name = 0) ⇒ Void

Note:

method wrapper for void CvSVM::load(c_string filename, c_string name = 0)

Parameters:

  • filename (C_string)
  • name (C_string) (defaults to: 0)

Returns:

  • (Void) 


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# File 'lib/ropencv/ropencv_types.rb', line 42971

def load(filename, name = 0)
    __validate_pointer__
    Rbind::cvsvm_load( self, filename, name)
end

#predict(sample, return_d_f_val = false) ⇒ Float

Note:

method wrapper for float CvSVM::predict(const cv::Mat sample, bool returnDFVal = false)

Parameters:

  • sample (Cv::Mat)
  • return_d_f_val (Bool) (defaults to: false)

Returns:

  • (Float) 


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# File 'lib/ropencv/ropencv_types.rb', line 42902

def predict(sample, return_d_f_val = false)
    __validate_pointer__
    Rbind::cvsvm_predict( self, sample, return_d_f_val)
end

#predict_all(samples, results) ⇒ Void

Note:

method wrapper for void CvSVM::predict(const cv::Mat samples, cv::Mat& results)

Parameters:

Returns:

  • (Void) 


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# File 'lib/ropencv/ropencv_types.rb', line 42911

def predict_all(samples, results)
    __validate_pointer__
    Rbind::cvsvm_predict_all( self, samples, results)
end

#save(filename, name = 0) ⇒ Void

Note:

method wrapper for void CvSVM::save(c_string filename, c_string name = 0)

Parameters:

  • filename (C_string)
  • name (C_string) (defaults to: 0)

Returns:

  • (Void) 


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# File 'lib/ropencv/ropencv_types.rb', line 42962

def save(filename, name = 0)
    __validate_pointer__
    Rbind::cvsvm_save( self, filename, name)
end

#to_s ⇒ Object

converts CvSVM into a string by crawling through all its attributes



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# File 'lib/ropencv/ropencv_types.rb', line 42842

def to_s
    "#<CvSVM >"
end

#train(train_data, responses, var_idx = Cv::Mat.new(), sample_idx = Cv::Mat.new(), params = CvSVMParams.new()) ⇒ Bool

Note:

method wrapper for bool CvSVM::train(const cv::Mat trainData, const cv::Mat responses, const cv::Mat varIdx = cv::Mat(), const cv::Mat sampleIdx = cv::Mat(), const CvSVMParams params = CvSVMParams())

methods

Parameters:

Returns:

  • (Bool) 


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# File 'lib/ropencv/ropencv_types.rb', line 42873

def train(train_data, responses, var_idx = Cv::Mat.new(), sample_idx = Cv::Mat.new(), params = CvSVMParams.new())
    __validate_pointer__
    Rbind::cvsvm_train( self, train_data, responses, var_idx, sample_idx, params)
end

#train_auto(train_data, responses, var_idx, sample_idx, params, k_fold = 10, cgrid = CvSVM.new(CvSVM::C), gamma_grid = CvSVM.new(CvSVM::GAMMA), p_grid = CvSVM.new(CvSVM::P), nu_grid = CvSVM.new(CvSVM::NU), coeff_grid = CvSVM.new(CvSVM::COEF), degree_grid = CvSVM.new(CvSVM::DEGREE), balanced = false) ⇒ Bool

Note:

method wrapper for bool CvSVM::train_auto(const cv::Mat trainData, const cv::Mat responses, const cv::Mat varIdx, const cv::Mat sampleIdx, const CvSVMParams params, int k_fold = 10, const CvParamGrid Cgrid = CvSVM::get_default_grid(CvSVM::C), const CvParamGrid gammaGrid = CvSVM::get_default_grid(CvSVM::GAMMA), const CvParamGrid pGrid = CvSVM::get_default_grid(CvSVM::P), const CvParamGrid nuGrid = CvSVM::get_default_grid(CvSVM::NU), const CvParamGrid coeffGrid = CvSVM::get_default_grid(CvSVM::COEF), const CvParamGrid degreeGrid = CvSVM::get_default_grid(CvSVM::DEGREE), bool balanced = false)

Parameters:

  • train_data (Cv::Mat)
  • responses (Cv::Mat)
  • var_idx (Cv::Mat)
  • sample_idx (Cv::Mat)
  • params (CvSVMParams)
  • k_fold (Fixnum) (defaults to: 10)
  • cgrid (CvParamGrid) (defaults to: CvSVM.new(CvSVM::C))
  • gamma_grid (CvParamGrid) (defaults to: CvSVM.new(CvSVM::GAMMA))
  • p_grid (CvParamGrid) (defaults to: CvSVM.new(CvSVM::P))
  • nu_grid (CvParamGrid) (defaults to: CvSVM.new(CvSVM::NU))
  • coeff_grid (CvParamGrid) (defaults to: CvSVM.new(CvSVM::COEF))
  • degree_grid (CvParamGrid) (defaults to: CvSVM.new(CvSVM::DEGREE))
  • balanced (Bool) (defaults to: false)

Returns:

  • (Bool) 


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# File 'lib/ropencv/ropencv_types.rb', line 42893

def train_auto(train_data, responses, var_idx, sample_idx, params, k_fold = 10, cgrid = CvSVM.new(CvSVM::C), gamma_grid = CvSVM.new(CvSVM::GAMMA), p_grid = CvSVM.new(CvSVM::P), nu_grid = CvSVM.new(CvSVM::NU), coeff_grid = CvSVM.new(CvSVM::COEF), degree_grid = CvSVM.new(CvSVM::DEGREE), balanced = false)
    __validate_pointer__
    Rbind::cvsvm_train_auto( self, train_data, responses, var_idx, sample_idx, params, k_fold, cgrid, gamma_grid, p_grid, nu_grid, coeff_grid, degree_grid, balanced)
end