
FisFilter_DL_DetectAnomalies2
Header: | FILDL.h |
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Namespace: | fil |
Module: | DeepLearning |
Executes a Detect Anomalies 2 model on a single input image.
Syntax
void fil::FisFilter_DL_DetectAnomalies2 ( const fil::Image& inImage, const fil::DetectAnomalies2ModelId& inModelId, fil::Heatmap& outHeatmap, bool& outIsValid, float& outScore, bool& outIsConfident )
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 |
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 FisFilter_DL_DetectAnomalies2_Deploy first and connected through the inModelId input.
- If one decides not to use FisFilter_DL_DetectAnomalies2_Deploy, then the model will be loaded in the first iteration. It will take up to several seconds.
Remarks

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 FisFilter_DL_DetectAnomalies2. Supported formats: 1xUInt8, 3xUInt8. |
See Also
Models for Deep Learning may be created using FabImage Deep Learning Editor or using Training Api.