ArmMachineLearningModelFactory.ImageInstanceSegmentation Method
Definition
Important
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Image Instance Segmentation. Instance segmentation is used to identify objects in an image at the pixel level, drawing a polygon around each object in the image.
public static Azure.ResourceManager.MachineLearning.Models.ImageInstanceSegmentation ImageInstanceSegmentation(Azure.ResourceManager.MachineLearning.Models.MachineLearningLogVerbosity? logVerbosity = default, string targetColumnName = default, Azure.ResourceManager.MachineLearning.Models.MachineLearningTableJobInput trainingData = default, Azure.ResourceManager.MachineLearning.Models.ImageModelSettingsObjectDetection modelSettings = default, System.Collections.Generic.IEnumerable<Azure.ResourceManager.MachineLearning.Models.ImageModelDistributionSettingsObjectDetection> searchSpace = default, Azure.ResourceManager.MachineLearning.Models.ImageLimitSettings limitSettings = default, Azure.ResourceManager.MachineLearning.Models.ImageSweepSettings sweepSettings = default, Azure.ResourceManager.MachineLearning.Models.MachineLearningTableJobInput validationData = default, double? validationDataSize = default, Azure.ResourceManager.MachineLearning.Models.InstanceSegmentationPrimaryMetric? primaryMetric = default);static member ImageInstanceSegmentation : Nullable<Azure.ResourceManager.MachineLearning.Models.MachineLearningLogVerbosity> * string * Azure.ResourceManager.MachineLearning.Models.MachineLearningTableJobInput * Azure.ResourceManager.MachineLearning.Models.ImageModelSettingsObjectDetection * seq<Azure.ResourceManager.MachineLearning.Models.ImageModelDistributionSettingsObjectDetection> * Azure.ResourceManager.MachineLearning.Models.ImageLimitSettings * Azure.ResourceManager.MachineLearning.Models.ImageSweepSettings * Azure.ResourceManager.MachineLearning.Models.MachineLearningTableJobInput * Nullable<double> * Nullable<Azure.ResourceManager.MachineLearning.Models.InstanceSegmentationPrimaryMetric> -> Azure.ResourceManager.MachineLearning.Models.ImageInstanceSegmentationPublic Shared Function ImageInstanceSegmentation (Optional logVerbosity As Nullable(Of MachineLearningLogVerbosity) = Nothing, Optional targetColumnName As String = Nothing, Optional trainingData As MachineLearningTableJobInput = Nothing, Optional modelSettings As ImageModelSettingsObjectDetection = Nothing, Optional searchSpace As IEnumerable(Of ImageModelDistributionSettingsObjectDetection) = Nothing, Optional limitSettings As ImageLimitSettings = Nothing, Optional sweepSettings As ImageSweepSettings = Nothing, Optional validationData As MachineLearningTableJobInput = Nothing, Optional validationDataSize As Nullable(Of Double) = Nothing, Optional primaryMetric As Nullable(Of InstanceSegmentationPrimaryMetric) = Nothing) As ImageInstanceSegmentationParameters
- logVerbosity
- Nullable<MachineLearningLogVerbosity>
Enum for setting log verbosity.
- targetColumnName
- String
Target column name: This is prediction values column. Also known as label column name in context of classification tasks.
- trainingData
- MachineLearningTableJobInput
[Required] Training data input.
- modelSettings
- ImageModelSettingsObjectDetection
Settings used for training the model.
- searchSpace
- IEnumerable<ImageModelDistributionSettingsObjectDetection>
Search space for sampling different combinations of models and their hyperparameters.
- limitSettings
- ImageLimitSettings
[Required] Limit settings for the AutoML job.
- sweepSettings
- ImageSweepSettings
Model sweeping and hyperparameter sweeping related settings.
- validationData
- MachineLearningTableJobInput
Validation data inputs.
The fraction of training dataset that needs to be set aside for validation purpose. Values between (0.0 , 1.0) Applied when validation dataset is not provided.
- primaryMetric
- Nullable<InstanceSegmentationPrimaryMetric>
Primary metrics for InstanceSegmentation tasks.
Returns
A new ImageInstanceSegmentation instance for mocking.
