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clear_train_data_variation_modelClearTrainDataVariationModelClearTrainDataVariationModelclear_train_data_variation_modelT_clear_train_data_variation_model🔗

Short description🔗

clear_train_data_variation_modelClearTrainDataVariationModelClearTrainDataVariationModelclear_train_data_variation_modelT_clear_train_data_variation_model — Free the memory of the training data of a variation model.

Signature🔗

clear_train_data_variation_model( variation_model ModelID )void ClearTrainDataVariationModel( const HTuple& ModelID )static void HOperatorSet.ClearTrainDataVariationModel( HTuple modelID )def clear_train_data_variation_model( model_id: HHandle ) -> None

Herror T_clear_train_data_variation_model( const Htuple ModelID )

void HVariationModel::ClearTrainDataVariationModel( ) const

void HVariationModel.ClearTrainDataVariationModel( )

Description🔗

clear_train_data_variation_modelClearTrainDataVariationModel frees the memory of a variation model that was created by create_variation_modelCreateVariationModel. clear_train_data_variation_modelClearTrainDataVariationModel can be used to reduce the amount of memory required for the variation model (in main memory as well as when writing the model to file with write_variation_modelWriteVariationModel). clear_train_data_variation_modelClearTrainDataVariationModel can only be called if the model has been prepared for comparison with an image with prepare_variation_modelPrepareVariationModel. After the call to clear_train_data_variation_modelClearTrainDataVariationModel the variation model can only be used for image comparison with compare_variation_modelCompareVariationModel or compare_ext_variation_modelCompareExtVariationModel. The model cannot be trained any further. Furthermore, the images used for the image comparison can no longer be read with get_variation_modelGetVariationModel. If they are required, get_variation_modelGetVariationModel must be called before clear_train_data_variation_modelClearTrainDataVariationModel is called.

Execution information🔗

Execution information
  • 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:

During execution of this operator, access to the value of this parameter must be synchronized if it is used across multiple threads.

Parameters🔗

ModelIDmodelIDmodel_id (input_control, state is modified) variation_model → (handle)HTuple (HHandle)HVariationModel, HTuple (IntPtr)HHandleHtuple (handle)

ID of the variation model.

Result🔗

clear_train_data_variation_modelClearTrainDataVariationModel returns 2 (H_MSG_TRUE) if all parameters are correct.

Combinations with other operators🔗

Combinations

Possible predecessors

prepare_variation_modelPrepareVariationModel

Possible successors

compare_variation_modelCompareVariationModel, compare_ext_variation_modelCompareExtVariationModel, write_variation_modelWriteVariationModel

Module🔗

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