TorchSharpCatalog.ObjectDetection Method
Definition
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.
Overloads
| ObjectDetection(MulticlassClassificationCatalog+MulticlassClassificationTrainers, ObjectDetectionTrainer+Options) |
Fine tune an object detection model. |
| ObjectDetection(MulticlassClassificationCatalog+MulticlassClassificationTrainers, String, String, String, String, String, String, Int32) |
Fine tune an object detection model. |
ObjectDetection(MulticlassClassificationCatalog+MulticlassClassificationTrainers, ObjectDetectionTrainer+Options)
Fine tune an object detection model.
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 ObjectDetectionTrainerParameters
The transform's catalog.
- options
- ObjectDetectionTrainer.Options
The full set of advanced options.
Returns
Applies to
ObjectDetection(MulticlassClassificationCatalog+MulticlassClassificationTrainers, String, String, String, String, String, String, Int32)
Fine tune an object detection model.
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 ObjectDetectionTrainerParameters
The transform's catalog.
- labelColumnName
- String
The label column name. Should be a vector of keytype
- predictedLabelColumnName
- String
The output predicted label column name. Is a vector of keytype
- scoreColumnName
- String
The output score column name. Is a vector of float.
- boundingBoxColumnName
- String
The bounding box column name. Is a vector of float. Values should be in the order x0 y0 x1 y1.
- predictedBoundingBoxColumnName
- String
The output bounding box column name. Is a vector of float. Values should be in the order x0 y0 x1 y1.
- imageColumnName
- String
The column name holding the image Data. Is an MLImage
- maxEpoch
- Int32
How many epochs to run.