serialize_dl_modelT_serialize_dl_modelSerializeDlModelSerializeDlModelserialize_dl_model (Operator)

Name

serialize_dl_modelT_serialize_dl_modelSerializeDlModelSerializeDlModelserialize_dl_model — Serialize a deep learning model.

Signature

serialize_dl_model( : : DLModelHandle : SerializedItemHandle)

Herror T_serialize_dl_model(const Htuple DLModelHandle, Htuple* SerializedItemHandle)

void SerializeDlModel(const HTuple& DLModelHandle, HTuple* SerializedItemHandle)

HSerializedItem HDlModel::SerializeDlModel() const

static void HOperatorSet.SerializeDlModel(HTuple DLModelHandle, out HTuple serializedItemHandle)

HSerializedItem HDlModel.SerializeDlModel()

def serialize_dl_model(dlmodel_handle: HHandle) -> HHandle

Description

serialize_dl_modelserialize_dl_modelSerializeDlModelSerializeDlModelSerializeDlModelserialize_dl_model serializes the deep learning model defined by the handle DLModelHandleDLModelHandleDLModelHandleDLModelHandleDLModelHandledlmodel_handle. The serialized model is returned by the handle SerializedItemHandleSerializedItemHandleSerializedItemHandleSerializedItemHandleserializedItemHandleserialized_item_handle and can be deserialized by deserialize_dl_modeldeserialize_dl_modelDeserializeDlModelDeserializeDlModelDeserializeDlModeldeserialize_dl_model. See fwrite_serialized_itemfwrite_serialized_itemFwriteSerializedItemFwriteSerializedItemFwriteSerializedItemfwrite_serialized_item for an introduction of the basic principle of serialization.

The operator acts the same as write_dl_modelwrite_dl_modelWriteDlModelWriteDlModelWriteDlModelwrite_dl_model except that the output is a serialized item instead of a file. For a detailed description please refer to the documentation of write_dl_modelwrite_dl_modelWriteDlModelWriteDlModelWriteDlModelwrite_dl_model.

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

Execution Information

Parameters

DLModelHandleDLModelHandleDLModelHandleDLModelHandleDLModelHandledlmodel_handle (input_control)  dl_model HDlModel, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)

Handle of the deep learning model.

SerializedItemHandleSerializedItemHandleSerializedItemHandleSerializedItemHandleserializedItemHandleserialized_item_handle (output_control)  serialized_item HSerializedItem, HTupleHHandleHTupleHtuple (handle) (IntPtr) (HHandle) (handle)

Handle of the serialized item.

Result

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

Possible Predecessors

train_dl_model_batchtrain_dl_model_batchTrainDlModelBatchTrainDlModelBatchTrainDlModelBatchtrain_dl_model_batch, train_dl_model_anomaly_datasettrain_dl_model_anomaly_datasetTrainDlModelAnomalyDatasetTrainDlModelAnomalyDatasetTrainDlModelAnomalyDatasettrain_dl_model_anomaly_dataset

Possible Successors

train_dl_model_batchtrain_dl_model_batchTrainDlModelBatchTrainDlModelBatchTrainDlModelBatchtrain_dl_model_batch, train_dl_model_anomaly_datasettrain_dl_model_anomaly_datasetTrainDlModelAnomalyDatasetTrainDlModelAnomalyDatasetTrainDlModelAnomalyDatasettrain_dl_model_anomaly_dataset, fwrite_serialized_itemfwrite_serialized_itemFwriteSerializedItemFwriteSerializedItemFwriteSerializedItemfwrite_serialized_item, send_serialized_itemsend_serialized_itemSendSerializedItemSendSerializedItemSendSerializedItemsend_serialized_item

See also

deserialize_dl_modeldeserialize_dl_modelDeserializeDlModelDeserializeDlModelDeserializeDlModeldeserialize_dl_model, apply_dl_modelapply_dl_modelApplyDlModelApplyDlModelApplyDlModelapply_dl_model, train_dl_model_batchtrain_dl_model_batchTrainDlModelBatchTrainDlModelBatchTrainDlModelBatchtrain_dl_model_batch, train_dl_model_anomaly_datasettrain_dl_model_anomaly_datasetTrainDlModelAnomalyDatasetTrainDlModelAnomalyDatasetTrainDlModelAnomalyDatasettrain_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, Deep Learning Inference