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Detects anomalies using trained deep-learning model.
Name | Type | Description | |
---|---|---|---|
inImage | Image | Input image | |
inDeepModel | DeepModel_AnomalyDetection1 | Trained model | |
outHeatmap | Image | Image contains heatmaps for each input image channel | |
outIsValid | Bool | Returns true if anomaly was not found | |
outScore | Real | Score of classification | |
outIsConfident | Bool | Returns "false" if score is between T1 and T2 | |
outReconstructedImage | Image | Returns network answer |
Requirements
For input inImage only pixel formats are supported: 1⨯uint8, 3⨯uint8.
Read more about pixel formats in Image documentation.
Hints
Loading Deep Learning Model may take longer timer. Consider using DeepLearning_LoadModel for pre-loading model before execution starts.
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.
Complexity Level
This filter is available on Basic Complexity Level.
Disabled in Lite Edition
This filter is disabled in Lite Edition. It is available only in full, Adaptive Vision Studio Professional version.
See Also
Models for Deep Learning may be created using Adaptive Vision Deep Learning Editor.