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AVL.DeepLearning_DetectAnomalies1
Detects anomalies using trained deep-learning model.
| Namespace: | AvlNet |
|---|---|
| Assembly: | AVL.NET.dll |
Syntax
C++
C#
public static void DeepLearning_DetectAnomalies1 ( AvlNet.DeepLearningConnectionState ioState, AvlNet.Image inImage, string inDeepModel, AvlNet.Image outHeatmap, out bool outIsValid, out float outScore, out bool outIsConfident )
Parameters
| Name | Type | Range | Default | Description | |
|---|---|---|---|---|---|
| ioState | AvlNet.DeepLearningConnectionState | ||||
 | inImage | AvlNet.Image | Input image. | ||
| inDeepModel | string | Trained model. | ||
 | outHeatmap | AvlNet.Image | Image contains heatmaps for each input image channel. | ||
| outIsValid | bool | Returns true if anomaly was not found. | ||
| outScore | float | Score of classification. | ||
| outIsConfident | bool | Returns "false" if score is between T1 and T2. |
Remarks
- Model provided on inDeepModel input will be loaded to service automatically on first usage of Deep Learning filters.
- Service automatically releases and loads model into its memory. It may result in releasing model previously loaded using DeepLearning_LoadModel filter.
- These filters only communicates with service and cannot be use for parallel computation.
