Detects anomalies using trained deep-learning 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|
For input inImage only pixel formats are supported: 1⨯uint8, 3⨯uint8.
Read more about pixel formats in Image documentation.
Loading Deep Learning Model may take longer timer. Consider using DeepLearning_LoadModel_AnomalyDetection2 for pre-loading model before execution starts.
- Model provided on inDeepModel input will be loaded to service automatically on first usage of Deep Learning filters.
- These filters only communicates with service and cannot be use for parallel computation.
This filter is available on Basic Complexity Level.
Disabled in Lite Edition
Models for Deep Learning may be created using Adaptive Vision Deep Learning Editor.