LearningModelEvaluationResult 类

定义

命名空间:

Windows.AI.MachineLearning

获取评估结果。

public ref class LearningModelEvaluationResult sealed

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

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

Public NotInheritable Class LearningModelEvaluationResult

继承

Object Platform::Object IInspectable LearningModelEvaluationResult

属性

ContractVersionAttribute MarshalingBehaviorAttribute

Windows 要求

设备系列	Windows 10, version 1809 (在 10.0.17763.0 中引入)
API contract	Windows.AI.MachineLearning.MachineLearningContract (在 v1.0 中引入)

示例

以下示例检索模型的第一个输入和输出特征，创建输出帧，绑定输入和输出特征，并评估模型。

private async Task EvaluateModelAsync(
    VideoFrame _inputFrame, 
    LearningModelSession _session, 
    IReadOnlyList<ILearningModelFeatureDescriptor> _inputFeatures, 
    IReadOnlyList<ILearningModelFeatureDescriptor> _outputFeatures,
    LearningModel _model)
{
    ImageFeatureDescriptor _inputImageDescription;
    TensorFeatureDescriptor _outputImageDescription;
    LearningModelBinding _binding = null;
    VideoFrame _outputFrame = null;
    LearningModelEvaluationResult _results;

    try
    {
        // 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;

        // Create output frame based on expected image width and height
        _outputFrame = new VideoFrame(
            BitmapPixelFormat.Bgra8, 
            (int)_inputImageDescription.Width, 
            (int)_inputImageDescription.Height);

        // Create binding and then bind input/output features
        _binding = new LearningModelBinding(_session);

        _binding.Bind(_inputImageDescription.Name, _inputFrame);
        _binding.Bind(_outputImageDescription.Name, _outputFrame);

        // Evaluate and get the results
        _results = await _session.EvaluateAsync(_binding, "test");
    }
    catch (Exception ex)
    {
        StatusBlock.Text = $"error: {ex.Message}";
        _model = null;
    }
}

注解

Windows Server

若要在 Windows Server 上使用此 API，必须使用带桌面体验的 Windows Server 2019。

线程安全

此 API 是线程安全的。

属性

CorrelationId	传递给 LearningModelSession.Evaluate 的可选字符串。
ErrorStatus	如果评估失败，则 返回导致失败的原因的错误代码。
Outputs	获取模型的输出特征。
Succeeded	如果评估成功完成，则为 True;否则为 false。

另请参阅

• Windows ML
• Windows ML 示例 (GitHub)