LearningModelEvaluationResult Kelas
Definisi
Penting
Beberapa informasi terkait produk prarilis yang dapat diubah secara signifikan sebelum dirilis. Microsoft tidak memberikan jaminan, tersirat maupun tersurat, sehubungan dengan informasi yang diberikan di sini.
Dapatkan hasil evaluasi.
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
- Warisan
- Atribut
Persyaratan Windows
Rangkaian perangkat |
Windows 10, version 1809 (diperkenalkan dalam 10.0.17763.0)
|
API contract |
Windows.AI.MachineLearning.MachineLearningContract (diperkenalkan dalam v1.0)
|
Contoh
Contoh berikut mengambil fitur input dan output pertama dari model, membuat bingkai output, mengikat fitur input dan output, dan mengevaluasi model.
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;
}
}
Keterangan
Windows Server
Untuk menggunakan API ini di Windows Server, Anda harus menggunakan Windows Server 2019 dengan Pengalaman Desktop.
Keamanan utas
API ini aman untuk utas.
Properti
CorrelationId |
String opsional yang diteruskan ke LearningModelSession.Evaluate. |
ErrorStatus |
Jika evaluasi gagal, mengembalikan kode kesalahan untuk apa yang menyebabkan kegagalan. |
Outputs |
Mendapatkan fitur output model. |
Succeeded |
True jika evaluasi berhasil diselesaikan; jika tidak, salah. |