Executes a Detect Anomalies 2 model on a single input image.
|inModelId||DetectAnomalies2ModelId||Identifier of a Detect Anomalies 2 model|
|outHeatmap||Heatmap||Returns a heatmap indicating found anomalies|
|outIsValid||Bool||Returns true if no anomalies were found|
|outScore||Real||Returns score of the image|
|outIsConfident||Bool||Returns false if the 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.
- It is recommended that the deep learning model is deployed with DL_DetectAnomalies2_Deploy first and connected through the inModelId input.
- If one decides not to use DL_DetectAnomalies2_Deploy, then the model will be loaded in the first iteration. It will take up to several seconds.
This filter should not be executed along with running Deep Learning Service as it may result in degraded performance or even out-of-memory errors.
This filter can throw an exception to report error. Read how to deal with errors in Error Handling.
List of possible exceptions:
|DomainError||Not supported inImage pixel format in AvsFilter_DL_DetectAnomalies2. Supported formats: 1xUInt8, 3xUInt8.|
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, Aurora Vision Studio Professional version.
Models for Deep Learning may be created using Aurora Vision Deep Learning Editor.
For more information, see Machine Vision Guide.