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ImageInstanceSegmentation.cs
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ImageInstanceSegmentation.cs
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// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
// <auto-generated/>
#nullable disable
using System;
using System.Collections.Generic;
using Azure.Core;
namespace Azure.ResourceManager.MachineLearning.Models
{
/// <summary>
/// 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.
/// </summary>
public partial class ImageInstanceSegmentation : AutoMLVertical
{
/// <summary> Initializes a new instance of <see cref="ImageInstanceSegmentation"/>. </summary>
/// <param name="trainingData"> [Required] Training data input. </param>
/// <param name="limitSettings"> [Required] Limit settings for the AutoML job. </param>
/// <exception cref="ArgumentNullException"> <paramref name="trainingData"/> or <paramref name="limitSettings"/> is null. </exception>
public ImageInstanceSegmentation(MachineLearningTableJobInput trainingData, ImageLimitSettings limitSettings) : base(trainingData)
{
Argument.AssertNotNull(trainingData, nameof(trainingData));
Argument.AssertNotNull(limitSettings, nameof(limitSettings));
SearchSpace = new ChangeTrackingList<ImageModelDistributionSettingsObjectDetection>();
LimitSettings = limitSettings;
TaskType = TaskType.ImageInstanceSegmentation;
}
/// <summary> Initializes a new instance of <see cref="ImageInstanceSegmentation"/>. </summary>
/// <param name="logVerbosity"> Log verbosity for the job. </param>
/// <param name="targetColumnName">
/// Target column name: This is prediction values column.
/// Also known as label column name in context of classification tasks.
/// </param>
/// <param name="taskType"> [Required] Task type for AutoMLJob. </param>
/// <param name="trainingData"> [Required] Training data input. </param>
/// <param name="primaryMetric"> Primary metric to optimize for this task. </param>
/// <param name="modelSettings"> Settings used for training the model. </param>
/// <param name="searchSpace"> Search space for sampling different combinations of models and their hyperparameters. </param>
/// <param name="limitSettings"> [Required] Limit settings for the AutoML job. </param>
/// <param name="sweepSettings"> Model sweeping and hyperparameter sweeping related settings. </param>
/// <param name="validationData"> Validation data inputs. </param>
/// <param name="validationDataSize">
/// 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.
/// </param>
internal ImageInstanceSegmentation(MachineLearningLogVerbosity? logVerbosity, string targetColumnName, TaskType taskType, MachineLearningTableJobInput trainingData, InstanceSegmentationPrimaryMetric? primaryMetric, ImageModelSettingsObjectDetection modelSettings, IList<ImageModelDistributionSettingsObjectDetection> searchSpace, ImageLimitSettings limitSettings, ImageSweepSettings sweepSettings, MachineLearningTableJobInput validationData, double? validationDataSize) : base(logVerbosity, targetColumnName, taskType, trainingData)
{
PrimaryMetric = primaryMetric;
ModelSettings = modelSettings;
SearchSpace = searchSpace;
LimitSettings = limitSettings;
SweepSettings = sweepSettings;
ValidationData = validationData;
ValidationDataSize = validationDataSize;
TaskType = taskType;
}
/// <summary> Primary metric to optimize for this task. </summary>
public InstanceSegmentationPrimaryMetric? PrimaryMetric { get; set; }
/// <summary> Settings used for training the model. </summary>
public ImageModelSettingsObjectDetection ModelSettings { get; set; }
/// <summary> Search space for sampling different combinations of models and their hyperparameters. </summary>
public IList<ImageModelDistributionSettingsObjectDetection> SearchSpace { get; set; }
/// <summary> [Required] Limit settings for the AutoML job. </summary>
public ImageLimitSettings LimitSettings { get; set; }
/// <summary> Model sweeping and hyperparameter sweeping related settings. </summary>
public ImageSweepSettings SweepSettings { get; set; }
/// <summary> Validation data inputs. </summary>
public MachineLearningTableJobInput ValidationData { get; set; }
/// <summary>
/// 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.
/// </summary>
public double? ValidationDataSize { get; set; }
}
}