Operator Reference

HALCON Operator Reference / Classification / Gaussian Mixture Models
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get_sample_class_gmmT_get_sample_class_gmmGetSampleClassGmmGetSampleClassGmmget_sample_class_gmm (Operator)

get_sample_class_gmmT_get_sample_class_gmmGetSampleClassGmmGetSampleClassGmmget_sample_class_gmm — Return a training sample from the training data of a Gaussian Mixture Models (GMM).

Signature

get_sample_class_gmm( : : GMMHandle, NumSample : Features, ClassID)

Herror T_get_sample_class_gmm(const Htuple GMMHandle, const Htuple NumSample, Htuple* Features, Htuple* ClassID)

void GetSampleClassGmm(const HTuple& GMMHandle, const HTuple& NumSample, HTuple* Features, HTuple* ClassID)

HTuple HClassGmm::GetSampleClassGmm(Hlong NumSample, Hlong* ClassID) const

static void HOperatorSet.GetSampleClassGmm(HTuple GMMHandle, HTuple numSample, out HTuple features, out HTuple classID)

HTuple HClassGmm.GetSampleClassGmm(int numSample, out int classID)

def get_sample_class_gmm(gmmhandle: HHandle, num_sample: int) -> Tuple[Sequence[float], int]

Description

get_sample_class_gmmget_sample_class_gmmGetSampleClassGmmGetSampleClassGmmget_sample_class_gmm reads out a training sample from the Gaussian Mixture Model (GMM) given by GMMHandleGMMHandleGMMHandleGMMHandlegmmhandle that was stored with add_sample_class_gmmadd_sample_class_gmmAddSampleClassGmmAddSampleClassGmmadd_sample_class_gmm or add_samples_image_class_gmmadd_samples_image_class_gmmAddSamplesImageClassGmmAddSamplesImageClassGmmadd_samples_image_class_gmm. The index of the sample is specified with NumSampleNumSampleNumSamplenumSamplenum_sample. The index is counted from 0, i.e., NumSampleNumSampleNumSamplenumSamplenum_sample must be a number between 0 and NumSamplesNumSamplesNumSamplesnumSamplesnum_samples - 1, where NumSamplesNumSamplesNumSamplesnumSamplesnum_samples can be determined with get_sample_num_class_gmmget_sample_num_class_gmmGetSampleNumClassGmmGetSampleNumClassGmmget_sample_num_class_gmm. The training sample is returned in FeaturesFeaturesFeaturesfeaturesfeatures and ClassIDClassIDClassIDclassIDclass_id. FeaturesFeaturesFeaturesfeaturesfeatures is a feature vector of length NumDimNumDimNumDimnumDimnum_dim, while ClassIDClassIDClassIDclassIDclass_id is its class (see add_sample_class_gmmadd_sample_class_gmmAddSampleClassGmmAddSampleClassGmmadd_sample_class_gmm and create_class_gmmcreate_class_gmmCreateClassGmmCreateClassGmmcreate_class_gmm).

get_sample_class_gmmget_sample_class_gmmGetSampleClassGmmGetSampleClassGmmget_sample_class_gmm can, for example, be used to reclassify the training data with classify_class_gmmclassify_class_gmmClassifyClassGmmClassifyClassGmmclassify_class_gmm in order to determine which training samples, if any, are classified incorrectly.

Execution Information

  • Multithreading type: reentrant (runs in parallel with non-exclusive operators).
  • Multithreading scope: global (may be called from any thread).
  • Processed without parallelization.

Parameters

GMMHandleGMMHandleGMMHandleGMMHandlegmmhandle (input_control)  class_gmm → HClassGmm, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)

GMM handle.

NumSampleNumSampleNumSamplenumSamplenum_sample (input_control)  integer → HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Index of the stored training sample.

FeaturesFeaturesFeaturesfeaturesfeatures (output_control)  real-array → HTupleSequence[float]HTupleHtuple (real) (double) (double) (double)

Feature vector of the training sample.

ClassIDClassIDClassIDclassIDclass_id (output_control)  number → HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Class of the training sample.

Example (HDevelop)

create_class_gmm (2, 2, [1,10], 'spherical', 'none', 2, 42, GMMHandle)
read_samples_class_gmm (GMMHandle, 'samples.gsf')
train_class_gmm (GMMHandle, 100, 1e-4, 'training', 1e-4, Centers, Iter)
* Reclassify the training samples
get_sample_num_class_gmm (GMMHandle, NumSamples)
for I := 0 to NumSamples-1 by 1
  get_sample_class_gmm (GMMHandle, I, Features, Class)
  classify_class_gmm (GMMHandle, Features, 2, ClassID, ClassProb,\
                      Density, KSigmaProb)
  if (not (Class == ClassProb[0]))
    * classified incorrectly
  endif
endfor

Result

If the parameters are valid, the operator get_sample_class_gmmget_sample_class_gmmGetSampleClassGmmGetSampleClassGmmget_sample_class_gmm returns the value 2 ( H_MSG_TRUE) . If necessary an exception is raised.

Possible Predecessors

add_sample_class_gmmadd_sample_class_gmmAddSampleClassGmmAddSampleClassGmmadd_sample_class_gmm, add_samples_image_class_gmmadd_samples_image_class_gmmAddSamplesImageClassGmmAddSamplesImageClassGmmadd_samples_image_class_gmm, read_samples_class_gmmread_samples_class_gmmReadSamplesClassGmmReadSamplesClassGmmread_samples_class_gmm, get_sample_num_class_gmmget_sample_num_class_gmmGetSampleNumClassGmmGetSampleNumClassGmmget_sample_num_class_gmm

Possible Successors

classify_class_gmmclassify_class_gmmClassifyClassGmmClassifyClassGmmclassify_class_gmm, evaluate_class_gmmevaluate_class_gmmEvaluateClassGmmEvaluateClassGmmevaluate_class_gmm

See also

create_class_gmmcreate_class_gmmCreateClassGmmCreateClassGmmcreate_class_gmm

Module

Foundation

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