
DL_DetectAnomalies2_Deploy
Header: | FILDL.h |
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Namespace: | fil |
Module: | DeepLearning |
Loads a deep learning model and prepares its execution on a specific target device.
Syntax
void fil::DL_DetectAnomalies2_Deploy ( const fil::DetectAnomalies2ModelDirectory& inModelDirectory, const ftl::Optional<fil::DeviceType::Type>& inTargetDevice, fil::DetectAnomalies2ModelId& outModelId )
Parameters
Name | Type | Default | Description | |
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inModelDirectory | const DetectAnomalies2ModelDirectory& | A Detect Anomalies 2 model stored in a specific disk directory. | |
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inTargetDevice | const Optional<DeviceType::Type>& | NIL | A device selected for deploying and executing the model. If not set, device depending on version (CPU/GPU) of installed Deep Learning Add-on is selected. |
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outModelId | DetectAnomalies2ModelId& | Identifier of the deployed model |
Hints
- In most cases, this filter should be placed in the INITIALIZE section.
- Executing this filter may take several seconds.
- This filter should be connected to DL_DetectAnomalies2 through the ModelId ports.
- You can edit the model directly through the inModelDirectory. Another option is to use the Deep Learning Editor application and just copy the path to the created model.
Remarks

- Passing NIL as inTargetDevice (which is default), is identical to passing DeviceType::CUDA on GPU version of Deep Learning Addon and DeviceType::CPU on CPU version on Deep Learning Addon.
- GPU version of Deep Learning Addon supports DeviceType::CUDA and DeviceType::CPU as inTargetDevice value.
- CPU version of Deep Learning Addon supports only DeviceType::CPU as inTargetDevice value.
See Also
- DL_DetectAnomalies2 – Executes a Detect Anomalies 2 model on a single input image.