Class: OpenCV::Cv::Ml::EM

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

Constants collapse

COV_MAT_SPHERICAL = 
0
COV_MAT_DIAGONAL = 
1
COV_MAT_GENERIC = 
2
COV_MAT_DEFAULT = 
1
DEFAULT_NCLUSTERS = 
5
DEFAULT_MAX_ITERS = 
100
START_E_STEP = 
1
START_M_STEP = 
2
START_AUTO_STEP = 
0

Class Method Summary collapse

Instance Method Summary collapse

Class Method Details

.create ⇒ Cv::Ptr::Cv_Ml_EM

Note:

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

Returns:



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# File 'lib/ropencv/ropencv_types.rb', line 49160

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

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

Note:

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

Parameters:

Returns:



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# File 'lib/ropencv/ropencv_types.rb', line 49168

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

.new(*args) ⇒ Object

Raises:

  • (ArgumentError) 


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# File 'lib/ropencv/ropencv_types.rb', line 48912

def self.new(*args)
    if args.first.is_a?(FFI::Pointer) || args.first.is_a?(EMStruct)
        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 48908

def self.null
    new(EMStruct.new)
end

Instance Method Details

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

Note:

method wrapper for float cv::ml::EM::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 49266

def calc_error(data, test, resp)
    __validate_pointer__
    Rbind::cv_ml_em_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::EM::castToAlgorithm(bool parse_ownership)

Parameters:

  • parse_ownership (Bool)

Returns:



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# File 'lib/ropencv/ropencv_types.rb', line 49275

def cast_to_algorithm(parse_ownership)
    __validate_pointer__
    result = Rbind::cv_ml_em_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::EM::castToStatModel(bool parse_ownership)

Parameters:

  • parse_ownership (Bool)

Returns:



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# File 'lib/ropencv/ropencv_types.rb', line 49175

def cast_to_stat_model(parse_ownership)
    __validate_pointer__
    result = Rbind::cv_ml_em_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::EM::clear()

Returns:

  • (Void) 


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# File 'lib/ropencv/ropencv_types.rb', line 49288

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

#empty ⇒ Bool

Note:

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

Returns:

  • (Bool) 


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# File 'lib/ropencv/ropencv_types.rb', line 49196

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

#get_clusters_number ⇒ Fixnum Also known as: getClustersNumber

Note:

method wrapper for int cv::ml::EM::getClustersNumber()

methods

Returns:

  • (Fixnum) 


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# File 'lib/ropencv/ropencv_types.rb', line 49005

def get_clusters_number()
    __validate_pointer__
    Rbind::cv_ml_em_get_clusters_number( self)
end

#get_covariance_matrix_type ⇒ Fixnum Also known as: getCovarianceMatrixType

Note:

method wrapper for int cv::ml::EM::getCovarianceMatrixType()

Returns:

  • (Fixnum) 


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# File 'lib/ropencv/ropencv_types.rb', line 49022

def get_covariance_matrix_type()
    __validate_pointer__
    Rbind::cv_ml_em_get_covariance_matrix_type( self)
end

#get_covs(covs) ⇒ Void Also known as: getCovs

Note:

method wrapper for void cv::ml::EM::getCovs(std::vectorcv::Mat& covs)

Parameters:

Returns:

  • (Void) 


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# File 'lib/ropencv/ropencv_types.rb', line 49088

def get_covs(covs)
    __validate_pointer__
    Rbind::cv_ml_em_get_covs( self, covs)
end

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

Note:

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

Returns:



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# File 'lib/ropencv/ropencv_types.rb', line 49320

def get_default_name()
    __validate_pointer__
    result = Rbind::cv_ml_em_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_means ⇒ Cv::Mat Also known as: getMeans

Note:

method wrapper for const cv::Mat cv::ml::EM::getMeans()

Returns:



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# File 'lib/ropencv/ropencv_types.rb', line 49074

def get_means()
    __validate_pointer__
    result = Rbind::cv_ml_em_get_means( 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_term_criteria ⇒ Cv::TermCriteria Also known as: getTermCriteria

Note:

method wrapper for const cv::TermCriteria cv::ml::EM::getTermCriteria()

Returns:



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# File 'lib/ropencv/ropencv_types.rb', line 49039

def get_term_criteria()
    __validate_pointer__
    result = Rbind::cv_ml_em_get_term_criteria( 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::EM::getVarCount()

Returns:

  • (Fixnum) 


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# File 'lib/ropencv/ropencv_types.rb', line 49188

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

#get_weights ⇒ Cv::Mat Also known as: getWeights

Note:

method wrapper for const cv::Mat cv::ml::EM::getWeights()

Returns:



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# File 'lib/ropencv/ropencv_types.rb', line 49061

def get_weights()
    __validate_pointer__
    result = Rbind::cv_ml_em_get_weights( 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

#is_classifier ⇒ Bool Also known as: isClassifier

Note:

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

Returns:

  • (Bool) 


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# File 'lib/ropencv/ropencv_types.rb', line 49211

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

#is_trained ⇒ Bool Also known as: isTrained

Note:

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

Returns:

  • (Bool) 


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# File 'lib/ropencv/ropencv_types.rb', line 49203

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

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

Note:

method wrapper for float cv::ml::EM::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 49099

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

#predict2(sample, probs) ⇒ Cv::Vec2d

Note:

method wrapper for const cv::Vec2d cv::ml::EM::predict2(const cv::Mat sample, cv::Mat& probs)

Parameters:

Returns:



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# File 'lib/ropencv/ropencv_types.rb', line 49108

def predict2(sample, probs)
    __validate_pointer__
    result = Rbind::cv_ml_em_predict2( self, sample, probs)
    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

#read(fn) ⇒ Void

Note:

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

Parameters:

Returns:

  • (Void) 


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# File 'lib/ropencv/ropencv_types.rb', line 49305

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

#save(filename) ⇒ Void

Note:

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

Parameters:

Returns:

  • (Void) 


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# File 'lib/ropencv/ropencv_types.rb', line 49313

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

#set_clusters_number(val) ⇒ Void Also known as: setClustersNumber

Note:

method wrapper for void cv::ml::EM::setClustersNumber(int val)

Parameters:

  • val (Fixnum)

Returns:

  • (Void) 


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# File 'lib/ropencv/ropencv_types.rb', line 49014

def set_clusters_number(val)
    __validate_pointer__
    Rbind::cv_ml_em_set_clusters_number( self, val)
end

#set_covariance_matrix_type(val) ⇒ Void Also known as: setCovarianceMatrixType

Note:

method wrapper for void cv::ml::EM::setCovarianceMatrixType(int val)

Parameters:

  • val (Fixnum)

Returns:

  • (Void) 


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# File 'lib/ropencv/ropencv_types.rb', line 49031

def set_covariance_matrix_type(val)
    __validate_pointer__
    Rbind::cv_ml_em_set_covariance_matrix_type( self, val)
end

#set_term_criteria(val) ⇒ Void Also known as: setTermCriteria

Note:

method wrapper for void cv::ml::EM::setTermCriteria(const cv::TermCriteria val)

Parameters:

Returns:

  • (Void) 


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# File 'lib/ropencv/ropencv_types.rb', line 49053

def set_term_criteria(val)
    __validate_pointer__
    Rbind::cv_ml_em_set_term_criteria( self, val)
end

#to_s ⇒ Object

converts EM into a string by crawling through all its attributes



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# File 'lib/ropencv/ropencv_types.rb', line 48985

def to_s
    "#<cv::ml::EM >"
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 49228

def train(*args)
    __validate_pointer__
    # overloaded method wrapper for bool cv::ml::EM::train(const cv::Ptr<cv::ml::TrainData> trainData, int flags = 0)
    @@cv_ml_em_train_defaults0 ||= [nil, 0]
    if(args.size >= 1 && args.size <= 2)
        targs = args.clone
        targs.size.upto(1) do |i|
            targs[i] = @@cv_ml_em_train_defaults0[i]
        end
        begin
                return Rbind::cv_ml_em_train(self,*targs)
        rescue TypeError => e
            @error = e
        end
    end

    # overloaded method wrapper for bool cv::ml::EM::train(const cv::Mat samples, int layout, const cv::Mat responses)
    @@cv_ml_em_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_em_train__2_defaults1[i]
        end
        begin
                return Rbind::cv_ml_em_train__2(self,*targs)
        rescue TypeError => e
            @error = e
        end
    end

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

#traine(samples, _means0, _covs0 = Cv::Mat.new(), _weights0 = Cv::Mat.new(), log_likelihoods = Cv::Mat.new(), labels = Cv::Mat.new(), probs = Cv::Mat.new()) ⇒ Bool Also known as: trainE

Note:

method wrapper for bool cv::ml::EM::trainE(const cv::Mat samples, const cv::Mat means0, const cv::Mat covs0 = Mat(), const cv::Mat weights0 = Mat(), const cv::Mat logLikelihoods = Mat()/O, const cv::Mat labels = Mat()/O, const cv::Mat probs = Mat()/O)

Parameters:

  • samples (Cv::Mat)
  • _means0 (Cv::Mat)
  • _covs0 (Cv::Mat) (defaults to: Cv::Mat.new())
  • _weights0 (Cv::Mat) (defaults to: Cv::Mat.new())
  • log_likelihoods (Cv::Mat) (defaults to: Cv::Mat.new())
  • labels (Cv::Mat) (defaults to: Cv::Mat.new())
  • probs (Cv::Mat) (defaults to: Cv::Mat.new())

Returns:

  • (Bool) 


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# File 'lib/ropencv/ropencv_types.rb', line 49139

def traine(samples, _means0, _covs0 = Cv::Mat.new(), _weights0 = Cv::Mat.new(), log_likelihoods = Cv::Mat.new(), labels = Cv::Mat.new(), probs = Cv::Mat.new())
    __validate_pointer__
    Rbind::cv_ml_em_traine( self, samples, _means0, _covs0, _weights0, log_likelihoods, labels, probs)
end

#trainem(samples, log_likelihoods = Cv::Mat.new(), labels = Cv::Mat.new(), probs = Cv::Mat.new()) ⇒ Bool Also known as: trainEM

Note:

method wrapper for bool cv::ml::EM::trainEM(const cv::Mat samples, const cv::Mat logLikelihoods = Mat()/O, const cv::Mat labels = Mat()/O, const cv::Mat probs = Mat()/O)

Parameters:

  • samples (Cv::Mat)
  • log_likelihoods (Cv::Mat) (defaults to: Cv::Mat.new())
  • labels (Cv::Mat) (defaults to: Cv::Mat.new())
  • probs (Cv::Mat) (defaults to: Cv::Mat.new())

Returns:

  • (Bool) 


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# File 'lib/ropencv/ropencv_types.rb', line 49124

def trainem(samples, log_likelihoods = Cv::Mat.new(), labels = Cv::Mat.new(), probs = Cv::Mat.new())
    __validate_pointer__
    Rbind::cv_ml_em_trainem( self, samples, log_likelihoods, labels, probs)
end

#trainm(samples, _probs0, log_likelihoods = Cv::Mat.new(), labels = Cv::Mat.new(), probs = Cv::Mat.new()) ⇒ Bool Also known as: trainM

Note:

method wrapper for bool cv::ml::EM::trainM(const cv::Mat samples, const cv::Mat probs0, const cv::Mat logLikelihoods = Mat()/O, const cv::Mat labels = Mat()/O, const cv::Mat probs = Mat()/O)

Parameters:

  • samples (Cv::Mat)
  • _probs0 (Cv::Mat)
  • log_likelihoods (Cv::Mat) (defaults to: Cv::Mat.new())
  • labels (Cv::Mat) (defaults to: Cv::Mat.new())
  • probs (Cv::Mat) (defaults to: Cv::Mat.new())

Returns:

  • (Bool) 


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# File 'lib/ropencv/ropencv_types.rb', line 49152

def trainm(samples, _probs0, log_likelihoods = Cv::Mat.new(), labels = Cv::Mat.new(), probs = Cv::Mat.new())
    __validate_pointer__
    Rbind::cv_ml_em_trainm( self, samples, _probs0, log_likelihoods, labels, probs)
end

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

Note:

method wrapper for void cv::ml::EM::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 49297

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