Loads a deep learning model and prepares its execution on a specific target device.
void avl::DL_DetectAnomalies2_Deploy ( const avl::DetectAnomalies2ModelDirectory& inModelDirectory, const atl::Optional<avl::DeviceType::Type>& inTargetDevice, avl::DetectAnomalies2ModelId& outModelId )
|inModelDirectory||const DetectAnomalies2ModelDirectory&||A Detect Anomalies 2 model stored in a specific disk directory.|
|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.|
|outModelId||DetectAnomalies2ModelId&||Identifier of the deployed model|
- 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.
- 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.
- DL_DetectAnomalies2 – Executes a Detect Anomalies 2 model on a single input image.