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Detects anomalies using trained deep-learning model.
Namespace: | AvlNet |
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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.