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AvsFilter_DL_DetectAnomalies2
Header: | AVL.h |
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Namespace: | avl |
Module: | DL_DA |
Executes a Detect Anomalies 2 model on a single input image.
Syntax
void avl::AvsFilter_DL_DetectAnomalies2 ( const avl::Image& inImage, const avl::DetectAnomalies2ModelId& inModelId, avl::Heatmap& outHeatmap, bool& outIsValid, float& outScore, bool& outIsConfident, atl::Conditional<avl::Region>& outRoi )
Parameters
Name | Type | Default | Description | |
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inImage | const Image& | Input image | |
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inModelId | const DetectAnomalies2ModelId& | Identifier of a Detect Anomalies 2 model | |
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outHeatmap | Heatmap& | Returns a heatmap indicating found anomalies | |
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outIsValid | bool& | Returns true if no anomalies were found | |
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outScore | float& | Returns score of the image | |
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outIsConfident | bool& | Returns false if the score is between T1 and T2 | |
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outRoi | Conditional<Region>& | ROI used in training |
Requirements
For input inImage only pixel formats are supported: 1⨯uint8, 3⨯uint8.
Read more about pixel formats in Image documentation.
Hints
- It is recommended that the deep learning model is deployed with AvsFilter_DL_DetectAnomalies2_Deploy first and connected through the inModelId input.
- If one decides not to use AvsFilter_DL_DetectAnomalies2_Deploy, then the model will be loaded in the first iteration. It will take up to several seconds.
Remarks
![](../../img/weaver/weaver_logo_slogan.png)
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.
Errors
List of possible exceptions:
Error type | Description |
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DomainError | Not supported inImage pixel format in AvsFilter_DL_DetectAnomalies2. Supported formats: 1xUInt8, 3xUInt8. |
See Also
Models for Deep Learning may be created using Aurora Vision Deep Learning Editor or using Training Api.
For more information, see Machine Vision Guide.