Name
read_samples_class_gmmT_read_samples_class_gmmReadSamplesClassGmmReadSamplesClassGmm — Read the training data of a Gaussian Mixture Model from a file.
read_samples_class_gmmread_samples_class_gmmReadSamplesClassGmmReadSamplesClassGmmReadSamplesClassGmm reads training samples from the file
given by FileNameFileNameFileNameFileNamefileName and adds them to the training samples
that have already been stored in the Gaussian Mixture Model (GMM)
given by GMMHandleGMMHandleGMMHandleGMMHandleGMMHandle. The GMM must be created with
create_class_gmmcreate_class_gmmCreateClassGmmCreateClassGmmCreateClassGmm before calling
read_samples_class_gmmread_samples_class_gmmReadSamplesClassGmmReadSamplesClassGmmReadSamplesClassGmm. As described with
train_class_gmmtrain_class_gmmTrainClassGmmTrainClassGmmTrainClassGmm and write_samples_class_gmmwrite_samples_class_gmmWriteSamplesClassGmmWriteSamplesClassGmmWriteSamplesClassGmm,
read_samples_class_gmmread_samples_class_gmmReadSamplesClassGmmReadSamplesClassGmmReadSamplesClassGmm, add_sample_class_gmmadd_sample_class_gmmAddSampleClassGmmAddSampleClassGmmAddSampleClassGmm, and
write_samples_class_gmmwrite_samples_class_gmmWriteSamplesClassGmmWriteSamplesClassGmmWriteSamplesClassGmm can be used to build up a database
of training samples, and hence to improve the performance of the GMM
by retraining the GMM with extended data sets.
It should be noted that the training samples must have the correct
dimensionality. The feature vectors stored in FileNameFileNameFileNameFileNamefileName
must have the lengths NumDimNumDimNumDimNumDimnumDim that was specified with
create_class_gmmcreate_class_gmmCreateClassGmmCreateClassGmmCreateClassGmm, and enough classes must have been created
in create_class_gmmcreate_class_gmmCreateClassGmmCreateClassGmmCreateClassGmm. If this is not the case, an error
message is returned.
It is possible to read files of samples that were written with
write_samples_class_svmwrite_samples_class_svmWriteSamplesClassSvmWriteSamplesClassSvmWriteSamplesClassSvm or write_samples_class_mlpwrite_samples_class_mlpWriteSamplesClassMlpWriteSamplesClassMlpWriteSamplesClassMlp.
- Multithreading type: reentrant (runs in parallel with non-exclusive operators).
- Multithreading scope: global (may be called from any thread).
- Processed without parallelization.
This operator modifies the state of the following input parameter:
The value of this parameter may not be shared across multiple threads without external synchronization.
If the parameters are valid, the operator
read_samples_class_gmmread_samples_class_gmmReadSamplesClassGmmReadSamplesClassGmmReadSamplesClassGmm returns the value 2 (H_MSG_TRUE). If necessary
an exception is raised.
create_class_gmmcreate_class_gmmCreateClassGmmCreateClassGmmCreateClassGmm
train_class_gmmtrain_class_gmmTrainClassGmmTrainClassGmmTrainClassGmm
add_sample_class_gmmadd_sample_class_gmmAddSampleClassGmmAddSampleClassGmmAddSampleClassGmm
write_samples_class_gmmwrite_samples_class_gmmWriteSamplesClassGmmWriteSamplesClassGmmWriteSamplesClassGmm,
write_samples_class_mlpwrite_samples_class_mlpWriteSamplesClassMlpWriteSamplesClassMlpWriteSamplesClassMlp,
clear_samples_class_gmmclear_samples_class_gmmClearSamplesClassGmmClearSamplesClassGmmClearSamplesClassGmm
Foundation