Executes a Detect Anomalies 2 model on a single input image.
void avl::DL_DetectAnomalies2 ( const avl::Image& inImage, const avl::DetectAnomalies2ModelId& inModelId, avl::Heatmap& outHeatmap, bool& outIsValid, float& outScore, bool& outIsConfident )
|inImage||const Image&||Input image|
|inModelId||const 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||float&||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.
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. However, if stopping Deep Learning Service is not an option (e.g. program uses other Deep Learning filters related to Instances Segmentation) it is advised that this filter should be executed at least once before performing operations utilizing Deep Learning Service (e.g. executing filters related to Instances Segmentation). Such "warm up" execution does not have to use real image or roi as long as provided image and roi have similar size.
List of possible exceptions:
|DomainError||Not supported inImage pixel format in DL_DetectAnomalies2.|
Models for Deep Learning may be created using Adaptive Vision Deep Learning Editor or using Training Api.