Class: OpenCV::Cv::Ml::NormalBayesClassifier

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

Class Method Summary collapse

Instance Method Summary collapse

Class Method Details

.create ⇒ Cv::Ptr::Cv_Ml_NormalBayesClassifier

Note:

wrapper for static method const cv::Ptrcv::ml::NormalBayesClassifier cv::ml::NormalBayesClassifier::create()

Returns:



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# File 'lib/ropencv/ropencv_types.rb', line 47720

def self.create()
    Rbind::cv_ml_normal_bayes_classifier_create()
end

.load(filepath, node_name = Std::String.new()) ⇒ Cv::Ptr::Cv_Ml_NormalBayesClassifier

Note:

wrapper for static method const cv::Ptrcv::ml::NormalBayesClassifier cv::ml::NormalBayesClassifier::load(const std::string filepath, const std::string nodeName = String())

Parameters:

Returns:



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# File 'lib/ropencv/ropencv_types.rb', line 47728

def self.load(filepath, node_name = Std::String.new())
    Rbind::cv_ml_normal_bayes_classifier_load(filepath, node_name)
end

.new(*args) ⇒ Object

Raises:

  • (ArgumentError) 


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# File 'lib/ropencv/ropencv_types.rb', line 47624

def self.new(*args)
    if args.first.is_a?(FFI::Pointer) || args.first.is_a?(NormalBayesClassifierStruct)
        raise ArgumentError, "too many arguments for creating #{self.name} from Pointer" unless args.size == 1
        return super(args.first)
    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 47620

def self.null
    new(NormalBayesClassifierStruct.new)
end

Instance Method Details

#calc_error(data, test, resp) ⇒ Float Also known as: calcError

Note:

method wrapper for float cv::ml::NormalBayesClassifier::calcError(const cv::Ptrcv::ml::TrainData data, bool test, cv::Mat& resp)

Parameters:

Returns:

  • (Float) 


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# File 'lib/ropencv/ropencv_types.rb', line 47826

def calc_error(data, test, resp)
    __validate_pointer__
    Rbind::cv_ml_normal_bayes_classifier_calc_error( self, data, test, resp)
end

#cast_to_algorithm(parse_ownership) ⇒ Cv::Algorithm Also known as: castToAlgorithm

Note:

method wrapper for cv::Algorithm* cv::ml::NormalBayesClassifier::castToAlgorithm(bool parse_ownership)

Parameters:

  • parse_ownership (Bool)

Returns:



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# File 'lib/ropencv/ropencv_types.rb', line 47845

def cast_to_algorithm(parse_ownership)
    __validate_pointer__
    result = Rbind::cv_ml_normal_bayes_classifier_cast_to_algorithm( self, parse_ownership)
    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

#cast_to_stat_model(parse_ownership) ⇒ Cv::Ml::StatModel Also known as: castToStatModel

Note:

method wrapper for cv::ml::StatModel* cv::ml::NormalBayesClassifier::castToStatModel(bool parse_ownership)

Parameters:

  • parse_ownership (Bool)

Returns:



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# File 'lib/ropencv/ropencv_types.rb', line 47735

def cast_to_stat_model(parse_ownership)
    __validate_pointer__
    result = Rbind::cv_ml_normal_bayes_classifier_cast_to_stat_model( self, parse_ownership)
    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 cv::ml::NormalBayesClassifier::clear()

Returns:

  • (Void) 


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# File 'lib/ropencv/ropencv_types.rb', line 47858

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

#empty ⇒ Bool

Note:

method wrapper for bool cv::ml::NormalBayesClassifier::empty()

Returns:

  • (Bool) 


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# File 'lib/ropencv/ropencv_types.rb', line 47756

def empty()
    __validate_pointer__
    Rbind::cv_ml_normal_bayes_classifier_empty( self)
end

#get_default_name ⇒ Std::String Also known as: getDefaultName

Note:

method wrapper for const std::string cv::ml::NormalBayesClassifier::getDefaultName()

Returns:



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# File 'lib/ropencv/ropencv_types.rb', line 47890

def get_default_name()
    __validate_pointer__
    result = Rbind::cv_ml_normal_bayes_classifier_get_default_name( 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

#get_var_count ⇒ Fixnum Also known as: getVarCount

Note:

method wrapper for int cv::ml::NormalBayesClassifier::getVarCount()

Returns:

  • (Fixnum) 


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# File 'lib/ropencv/ropencv_types.rb', line 47748

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

#is_classifier ⇒ Bool Also known as: isClassifier

Note:

method wrapper for bool cv::ml::NormalBayesClassifier::isClassifier()

Returns:

  • (Bool) 


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# File 'lib/ropencv/ropencv_types.rb', line 47771

def is_classifier()
    __validate_pointer__
    Rbind::cv_ml_normal_bayes_classifier_is_classifier( self)
end

#is_trained ⇒ Bool Also known as: isTrained

Note:

method wrapper for bool cv::ml::NormalBayesClassifier::isTrained()

Returns:

  • (Bool) 


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# File 'lib/ropencv/ropencv_types.rb', line 47763

def is_trained()
    __validate_pointer__
    Rbind::cv_ml_normal_bayes_classifier_is_trained( self)
end

#predict(samples, results = Cv::Mat.new(), flags = 0) ⇒ Float

Note:

method wrapper for float cv::ml::NormalBayesClassifier::predict(const cv::Mat samples, const cv::Mat results = Mat()/O, int flags = 0)

Parameters:

  • samples (Cv::Mat)
  • results (Cv::Mat) (defaults to: Cv::Mat.new())
  • flags (Fixnum) (defaults to: 0)

Returns:

  • (Float) 


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# File 'lib/ropencv/ropencv_types.rb', line 47837

def predict(samples, results = Cv::Mat.new(), flags = 0)
    __validate_pointer__
    Rbind::cv_ml_normal_bayes_classifier_predict( self, samples, results, flags)
end

#predict_prob(inputs, outputs, output_probs, flags = 0) ⇒ Float Also known as: predictProb

Note:

method wrapper for float cv::ml::NormalBayesClassifier::predictProb(const cv::Mat inputs, cv::Mat& outputs, cv::Mat& outputProbs, int flags = 0)

methods

Parameters:

Returns:

  • (Float) 


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# File 'lib/ropencv/ropencv_types.rb', line 47712

def predict_prob(inputs, outputs, output_probs, flags = 0)
    __validate_pointer__
    Rbind::cv_ml_normal_bayes_classifier_predict_prob( self, inputs, outputs, output_probs, flags)
end

#read(fn) ⇒ Void

Note:

method wrapper for void cv::ml::NormalBayesClassifier::read(const cv::FileNode fn)

Parameters:

Returns:

  • (Void) 


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# File 'lib/ropencv/ropencv_types.rb', line 47875

def read(fn)
    __validate_pointer__
    Rbind::cv_ml_normal_bayes_classifier_read( self, fn)
end

#save(filename) ⇒ Void

Note:

method wrapper for void cv::ml::NormalBayesClassifier::save(const std::string filename)

Parameters:

Returns:

  • (Void) 


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# File 'lib/ropencv/ropencv_types.rb', line 47883

def save(filename)
    __validate_pointer__
    Rbind::cv_ml_normal_bayes_classifier_save( self, filename)
end

#to_s ⇒ Object

converts NormalBayesClassifier into a string by crawling through all its attributes



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# File 'lib/ropencv/ropencv_types.rb', line 47697

def to_s
    "#<cv::ml::NormalBayesClassifier >"
end

#train(train_data, flags = 0) ⇒ Bool #train(samples, layout, responses) ⇒ Bool

Note:

wrapper for overloaded method train

Overloads:

  • #train(train_data, flags = 0) ⇒ Bool

    Parameters:

    Returns:

    • (Bool)
  • #train(samples, layout, responses) ⇒ Bool

    Parameters:

    Returns:

    • (Bool)

Raises:

  • (ArgumentError) 


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# File 'lib/ropencv/ropencv_types.rb', line 47788

def train(*args)
    __validate_pointer__
    # overloaded method wrapper for bool cv::ml::NormalBayesClassifier::train(const cv::Ptr<cv::ml::TrainData> trainData, int flags = 0)
    @@cv_ml_normal_bayes_classifier_train_defaults0 ||= [nil, 0]
    if(args.size >= 1 && args.size <= 2)
        targs = args.clone
        targs.size.upto(1) do |i|
            targs[i] = @@cv_ml_normal_bayes_classifier_train_defaults0[i]
        end
        begin
                return Rbind::cv_ml_normal_bayes_classifier_train(self,*targs)
        rescue TypeError => e
            @error = e
        end
    end

    # overloaded method wrapper for bool cv::ml::NormalBayesClassifier::train(const cv::Mat samples, int layout, const cv::Mat responses)
    @@cv_ml_normal_bayes_classifier_train__2_defaults1 ||= [nil, nil, nil]
    if(args.size >= 3 && args.size <= 3)
        targs = args.clone
        targs.size.upto(2) do |i|
            targs[i] = @@cv_ml_normal_bayes_classifier_train__2_defaults1[i]
        end
        begin
                return Rbind::cv_ml_normal_bayes_classifier_train__2(self,*targs)
        rescue TypeError => e
            @error = e
        end
    end

    raise ArgumentError, "No overloaded signature fits to: #{args.map(&:class)}"
end

#write(fs, name = Std::String.new()) ⇒ Void

Note:

method wrapper for void cv::ml::NormalBayesClassifier::write(const cv::Ptrcv::FileStorage fs, const std::string name = String())

Parameters:

Returns:

  • (Void) 


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# File 'lib/ropencv/ropencv_types.rb', line 47867

def write(fs, name = Std::String.new())
    __validate_pointer__
    Rbind::cv_ml_normal_bayes_classifier_write( self, fs, name)
end