Class: OpenCV::CvNormalBayesClassifier

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

Instance Attribute Summary collapse

Class Method Summary collapse

Instance Method Summary collapse

Constructor Details

#initialize(ptr) ⇒ CvNormalBayesClassifier

This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future.

Returns a new instance of CvNormalBayesClassifier.



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# File 'lib/ruby/ropencv/ropencv_types.rb', line 19792

def initialize(ptr)
    @__obj_ptr__ = if ptr.is_a? CvNormalBayesClassifierStruct
                       ptr
                   else
                       CvNormalBayesClassifierStruct.new(FFI::AutoPointer.new(ptr,CvNormalBayesClassifierStruct.method(:release)))
                   end
end

Instance Attribute Details

#__obj_ptr__ ⇒ Object (readonly)

This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future. 



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# File 'lib/ruby/ropencv/ropencv_types.rb', line 19789

def __obj_ptr__
  @__obj_ptr__
end

Class Method Details

.from_native(ptr, context) ⇒ Object

This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future.

can be overwritten by the user



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# File 'lib/ruby/ropencv/ropencv_types.rb', line 19784

def self.from_native(ptr,context)
    rbind_from_native(ptr,context)
end

.new(*args) ⇒ Object

Raises:

  • (ArgumentError) 


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# File 'lib/ruby/ropencv/ropencv_types.rb', line 19728

def self.new(*args)
    if args.first.is_a?(FFI::Pointer) || args.first.is_a?(CvNormalBayesClassifierStruct)
        raise ArgumentError, "too many arguments for creating #{self.name} from Pointer" unless args.size == 1
        return super(args.first)
    end
    # wrapper for CvNormalBayesClassifier::CvNormalBayesClassifier()
    @@cv_normal_bayes_classifier_cv_normal_bayes_classifier_defaults0 ||= []
    if(args.size >= 0 && args.size <= 0)
        args.size.upto(-1) do |i|
            args[i] = @@cv_normal_bayes_classifier_cv_normal_bayes_classifier_defaults0[i]
        end
        begin
            return Rbind::cv_normal_bayes_classifier_cv_normal_bayes_classifier(*args)
        rescue TypeError => e
            @error = e
        end
    end

    # wrapper for CvNormalBayesClassifier::CvNormalBayesClassifier(const cv::Mat trainData, const cv::Mat responses, const cv::Mat varIdx=cv::Mat(), const cv::Mat sampleIdx=cv::Mat())
    @@cv_normal_bayes_classifier_cv_normal_bayes_classifier2_defaults1 ||= [nil, nil, Cv::Mat.new(), Cv::Mat.new()]
    if(args.size >= 2 && args.size <= 4)
        args.size.upto(3) do |i|
            args[i] = @@cv_normal_bayes_classifier_cv_normal_bayes_classifier2_defaults1[i]
        end
        begin
            return Rbind::cv_normal_bayes_classifier_cv_normal_bayes_classifier2(*args)
        rescue TypeError => e
            @error = e
        end
    end

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

.rbind_from_native(ptr, context) ⇒ Object

This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future. 



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# File 'lib/ruby/ropencv/ropencv_types.rb', line 19772

def self.rbind_from_native(ptr,context)
    CvNormalBayesClassifier.new(ptr)
end

.rbind_to_native(obj, context) ⇒ Object

This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future. 



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# File 'lib/ruby/ropencv/ropencv_types.rb', line 19763

def self.rbind_to_native(obj,context)
    if obj.is_a? CvNormalBayesClassifier
        obj.__obj_ptr__
    else
        raise TypeError, "expected kind of #{name}, was #{obj.class}"
    end
end

.to_native(obj, context) ⇒ Object

This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future.

can be overwritten by the user



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# File 'lib/ruby/ropencv/ropencv_types.rb', line 19778

def self.to_native(obj,context)
    rbind_to_native(obj,context)
end

Instance Method Details

#__owner__? ⇒ Boolean

This method is part of a private API. You should avoid using this method if possible, as it may be removed or be changed in the future.

returns true if the underlying pointer is owner of the real object

Returns:

  • (Boolean) 


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# File 'lib/ruby/ropencv/ropencv_types.rb', line 19803

def __owner__?
    @__obj_ptr__[:bowner]
end

#clear ⇒ Object

methods wrapper for void CvNormalBayesClassifier::clear()



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# File 'lib/ruby/ropencv/ropencv_types.rb', line 19817

def clear()
    Rbind::cv_normal_bayes_classifier_clear( self)
end

#load(filename, name = 0) ⇒ Object

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



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# File 'lib/ruby/ropencv/ropencv_types.rb', line 19837

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

#predict(samples, results = 0) ⇒ Object

wrapper for float CvNormalBayesClassifier::predict(const cv::Mat samples, cv::Mat *results=0)



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# File 'lib/ruby/ropencv/ropencv_types.rb', line 19827

def predict(samples, results = 0)
    Rbind::cv_normal_bayes_classifier_predict( self, samples, results)
end

#save(filename, name = 0) ⇒ Object

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



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# File 'lib/ruby/ropencv/ropencv_types.rb', line 19832

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

#train(train_data, responses, var_idx = Cv::Mat.new(), sample_idx = Cv::Mat.new(), update = false) ⇒ Object

wrapper for bool CvNormalBayesClassifier::train(const cv::Mat trainData, const cv::Mat responses, const cv::Mat varIdx=cv::Mat(), const cv::Mat sampleIdx=cv::Mat(), bool update=false)



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# File 'lib/ruby/ropencv/ropencv_types.rb', line 19822

def train(train_data, responses, var_idx = Cv::Mat.new(), sample_idx = Cv::Mat.new(), update = false)
    Rbind::cv_normal_bayes_classifier_train( self, train_data, responses, var_idx, sample_idx, update)
end