You are here: Start » AVLDL.DeepLearning_ClassifyObject Method
AVLDL.DeepLearning_ClassifyObject Method
| Namespace: | AvlNet.DeepLearning |
|---|---|
| Assembly: | AvlDl.Net.dll |
Syntax
public static void DeepLearning_ClassifyObject ( AvlNet.Image inImage, string inDeepModel, bool inCreateRelevanceHeatmap, IList<AvlNet.ClassConfidence> outConfidences, out string outClassName, out int outClassIndex, out float outScore, AvlNet.Image outRelevanceHeatmap )
Parameters
| Name | Type | Range | Default | Description | |
|---|---|---|---|---|---|
 | inImage | AvlNet.Image | Input image | ||
| inDeepModel | string | Trained model | ||
| inCreateRelevanceHeatmap | bool | False | Enable-Disable create relevance heatmap | |
 | outConfidences | System.Collections.Generic.IList<AvlNet.ClassConfidence> | Returns confidences for all classes | ||
| outClassName | string | Returns name of the class with highest confidence | ||
| outClassIndex | int | Returns the index of the class with highest confidence | ||
| outScore | float | Returns the value of the highest confidence | ||
| outRelevanceHeatmap | AvlNet.Image | Returns heatmap indicating how strong specific parts of image influenced classification result |
Remarks
- Model provided on inDeepModel input will be loaded automatically on first usage of this filter.
- 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 Anomaly Detection or Instances Segmentation) it is advised that this filter should be executed before other Deep Learning filters. Such "warm up" execution does not have to use real image or roi as long as provided image and roi have similar size.
Errors
List of possible exceptions:
| Error type | Description |
|---|---|
| DomainError | Not supported inImage pixel format in DeepLearning_ClassifyObject. |
