clear_dl_modelT_clear_dl_modelClearDlModelClearDlModelclear_dl_model (Operator)

Name

clear_dl_modelT_clear_dl_modelClearDlModelClearDlModelclear_dl_model — Clear a deep learning model.

Signature

clear_dl_model( : : DLModelHandle : )

Description

clear_dl_modelclear_dl_modelClearDlModelClearDlModelclear_dl_model clears the handle of the deep learning model given by DLModelHandleDLModelHandleDLModelHandleDLModelHandledlmodel_handle and frees all memory required for the model. After calling clear_dl_modelclear_dl_modelClearDlModelClearDlModelclear_dl_model, the model can no longer be used and the handle DLModelHandleDLModelHandleDLModelHandleDLModelHandledlmodel_handle becomes invalid.

For further explanations to deep learning models in HALCON, see the chapter Deep Learning / Model.

Execution Information

Multithreading type: reentrant (runs in parallel with non-exclusive operators).
Multithreading scope: local (may only be called from the same thread in which the window, model, or tool instance was created).
Processed without parallelization.

This operator modifies the state of the following input parameter:

DLModelHandleDLModelHandleDLModelHandleDLModelHandledlmodel_handle

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

Parameters

DLModelHandleDLModelHandleDLModelHandleDLModelHandledlmodel_handle (input_control, state is modified) dl_model(-array) → (handle)

Handle of the deep learning model.

Result

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

Possible Predecessors

read_dl_modelread_dl_modelReadDlModelReadDlModelread_dl_model, apply_dl_modelapply_dl_modelApplyDlModelApplyDlModelapply_dl_model, train_dl_model_batchtrain_dl_model_batchTrainDlModelBatchTrainDlModelBatchtrain_dl_model_batch, train_dl_model_anomaly_datasettrain_dl_model_anomaly_datasetTrainDlModelAnomalyDatasetTrainDlModelAnomalyDatasettrain_dl_model_anomaly_dataset

Module

Foundation. This operator uses dynamic licensing (see the ``Installation Guide''). Which of the following modules is required depends on the specific usage of the operator:
3D Metrology, OCR/OCV, Matching, Deep Learning Inference

Operators