ImageFeatureDescriptor Class

Reference

Definition

Namespace:: Windows.AI.MachineLearning

Important

Some information relates to prerelease product that may be substantially modified before it’s released. Microsoft makes no warranties, express or implied, with respect to the information provided here.

Edit

Describes the properties of the image the model is expecting.

public ref class ImageFeatureDescriptor sealed : ILearningModelFeatureDescriptor

/// [Windows.Foundation.Metadata.ContractVersion(Windows.AI.MachineLearning.MachineLearningContract, 65536)]
/// [Windows.Foundation.Metadata.MarshalingBehavior(Windows.Foundation.Metadata.MarshalingType.Agile)]
class ImageFeatureDescriptor final : ILearningModelFeatureDescriptor

[Windows.Foundation.Metadata.ContractVersion(typeof(Windows.AI.MachineLearning.MachineLearningContract), 65536)]
[Windows.Foundation.Metadata.MarshalingBehavior(Windows.Foundation.Metadata.MarshalingType.Agile)]
public sealed class ImageFeatureDescriptor : ILearningModelFeatureDescriptor

Public NotInheritable Class ImageFeatureDescriptor
Implements ILearningModelFeatureDescriptor

Inheritance: Object Platform::Object IInspectable ImageFeatureDescriptor

Attributes: ContractVersionAttribute MarshalingBehaviorAttribute

Implements: ILearningModelFeatureDescriptor

Windows requirements

Device family	Windows 10, version 1809 (introduced in 10.0.17763.0)
API contract	Windows.AI.MachineLearning.MachineLearningContract (introduced in v1.0)

Examples

The following example loads a model from a local file, creates a session from it, and gets the input and output features.

private async Task LoadModelAsync(string _modelFileName)
{
    LearningModel _model;
    LearningModelSession _session;
    ImageFeatureDescriptor _inputImageDescription;
    TensorFeatureDescriptor _outputImageDescription;

    try
    {
        // Load and create the model
        var modelFile = 
            await StorageFile.GetFileFromApplicationUriAsync(new Uri($"ms-appx:///Assets/{_modelFileName}"));
        _model = await LearningModel.LoadFromStorageFileAsync(modelFile);

        // Create the evaluation session with the model
        _session = new LearningModelSession(_model);

        //Get input and output features of the model
        List<ILearningModelFeatureDescriptor> inputFeatures = _model.InputFeatures.ToList();
        List<ILearningModelFeatureDescriptor> outputFeatures = _model.OutputFeatures.ToList();

        // Retrieve the first input feature which is an image
        _inputImageDescription = inputFeatures.FirstOrDefault(
            feature => feature.Kind == LearningModelFeatureKind.Image) as ImageFeatureDescriptor;

        // Retrieve the first output feature which is a tensor
        _outputImageDescription = outputFeatures.FirstOrDefault(
            feature => feature.Kind == LearningModelFeatureKind.Tensor) as TensorFeatureDescriptor;
    }
    catch (Exception ex)
    {
        StatusBlock.Text = $"error: {ex.Message}";
        _model = null;
    }
}

Remarks

Windows Server

To use this API on Windows Server, you must use Windows Server 2019 with Desktop Experience.

Thread safety

This API is thread-safe.

Properties

BitmapAlphaMode	Specifies the expected alpha mode of the image.
BitmapPixelFormat	Specifies the expected pixel format (channel ordering, bit depth, and data type).
Description	A description of what this feature is used for in the model.
Height	The expected image height.
IsRequired	If true, you must bind a value to this feature before calling LearningModelSession.Evaluate.
Kind	The kind of feature—use this to know which derived class to use.
Name	The name you use to bind values to this feature.
PixelRange	Provides the expected LearningModelPixelRange information for use with the model.
Width	The expected image width.

Applies to

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