TorchSharpCatalog.ObjectDetection Metode

Definisi

Ruang nama:

Microsoft.ML.TorchSharp

Rakitan:

Microsoft.ML.TorchSharp.dll

Paket:

Microsoft.ML.TorchSharp v0.23.0-preview.1.25125.4

Overload

ObjectDetection(MulticlassClassificationCatalog+MulticlassClassificationTrainers, ObjectDetectionTrainer+Options)	Menyempurnakan model deteksi objek.
ObjectDetection(MulticlassClassificationCatalog+MulticlassClassificationTrainers, String, String, String, String, String, String, Int32)	Menyempurnakan model deteksi objek.

ObjectDetection(MulticlassClassificationCatalog+MulticlassClassificationTrainers, ObjectDetectionTrainer+Options)

Sumber:

TorchSharpCatalog.cs

Menyempurnakan model deteksi objek.

public static Microsoft.ML.TorchSharp.AutoFormerV2.ObjectDetectionTrainer ObjectDetection(this Microsoft.ML.MulticlassClassificationCatalog.MulticlassClassificationTrainers catalog, Microsoft.ML.TorchSharp.AutoFormerV2.ObjectDetectionTrainer.Options options);

static member ObjectDetection : Microsoft.ML.MulticlassClassificationCatalog.MulticlassClassificationTrainers * Microsoft.ML.TorchSharp.AutoFormerV2.ObjectDetectionTrainer.Options -> Microsoft.ML.TorchSharp.AutoFormerV2.ObjectDetectionTrainer

<Extension()>
Public Function ObjectDetection (catalog As MulticlassClassificationCatalog.MulticlassClassificationTrainers, options As ObjectDetectionTrainer.Options) As ObjectDetectionTrainer

Parameter

catalog

MulticlassClassificationCatalog.MulticlassClassificationTrainers

Katalog transformasi.

options

ObjectDetectionTrainer.Options

Set lengkap opsi tingkat lanjut.

Mengembalikan

ObjectDetectionTrainer

ObjectDetection(MulticlassClassificationCatalog+MulticlassClassificationTrainers, String, String, String, String, String, String, Int32)

Sumber:

TorchSharpCatalog.cs

Menyempurnakan model deteksi objek.

public static Microsoft.ML.TorchSharp.AutoFormerV2.ObjectDetectionTrainer ObjectDetection(this Microsoft.ML.MulticlassClassificationCatalog.MulticlassClassificationTrainers catalog, string labelColumnName = "Label", string predictedLabelColumnName = "PredictedLabel", string scoreColumnName = "Score", string boundingBoxColumnName = "BoundingBoxes", string predictedBoundingBoxColumnName = "PredictedBoundingBoxes", string imageColumnName = "Image", int maxEpoch = 10);

static member ObjectDetection : Microsoft.ML.MulticlassClassificationCatalog.MulticlassClassificationTrainers * string * string * string * string * string * string * int -> Microsoft.ML.TorchSharp.AutoFormerV2.ObjectDetectionTrainer

<Extension()>
Public Function ObjectDetection (catalog As MulticlassClassificationCatalog.MulticlassClassificationTrainers, Optional labelColumnName As String = "Label", Optional predictedLabelColumnName As String = "PredictedLabel", Optional scoreColumnName As String = "Score", Optional boundingBoxColumnName As String = "BoundingBoxes", Optional predictedBoundingBoxColumnName As String = "PredictedBoundingBoxes", Optional imageColumnName As String = "Image", Optional maxEpoch As Integer = 10) As ObjectDetectionTrainer

Parameter

catalog

MulticlassClassificationCatalog.MulticlassClassificationTrainers

Katalog transformasi.

labelColumnName

String

Nama kolom label. Harus menjadi vektor keytype

predictedLabelColumnName

String

Nama kolom label yang diprediksi output. Adalah vektor keytype

scoreColumnName

String

Nama kolom skor output. Adalah vektor float.

boundingBoxColumnName

String

Nama kolom kotak pembatas. Adalah vektor float. Nilai harus dalam urutan x0 y0 x1 y1.

predictedBoundingBoxColumnName

String

Nama kolom kotak pembatas output. Adalah vektor float. Nilai harus dalam urutan x0 y0 x1 y1.

imageColumnName

String

Nama kolom yang menyimpan data gambar. Adalah MLImage

maxEpoch

Int32

Berapa banyak epoch untuk dijalankan.

Mengembalikan

ObjectDetectionTrainer