ImageObjectDetection Class
Definition
Important
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Image Object Detection. Object detection is used to identify objects in an image and locate each object with a bounding box e.g. locate all dogs and cats in an image and draw a bounding box around each.
public class ImageObjectDetection : Azure.ResourceManager.MachineLearning.Models.AutoMLVertical, System.ClientModel.Primitives.IJsonModel<Azure.ResourceManager.MachineLearning.Models.ImageObjectDetection>, System.ClientModel.Primitives.IPersistableModel<Azure.ResourceManager.MachineLearning.Models.ImageObjectDetection>
public class ImageObjectDetection : Azure.ResourceManager.MachineLearning.Models.AutoMLVertical
type ImageObjectDetection = class
inherit AutoMLVertical
interface IJsonModel<ImageObjectDetection>
interface IPersistableModel<ImageObjectDetection>
type ImageObjectDetection = class
inherit AutoMLVertical
Public Class ImageObjectDetection
Inherits AutoMLVertical
Implements IJsonModel(Of ImageObjectDetection), IPersistableModel(Of ImageObjectDetection)
Public Class ImageObjectDetection
Inherits AutoMLVertical
- Inheritance
- Implements
Constructors
ImageObjectDetection(MachineLearningTableJobInput, ImageLimitSettings) |
Initializes a new instance of ImageObjectDetection. |
Properties
LimitSettings |
[Required] Limit settings for the AutoML job. |
LogVerbosity |
Log verbosity for the job. (Inherited from AutoMLVertical) |
ModelSettings |
Settings used for training the model. |
PrimaryMetric |
Primary metric to optimize for this task. |
SearchSpace |
Search space for sampling different combinations of models and their hyperparameters. |
SweepSettings |
Model sweeping and hyperparameter sweeping related settings. |
TargetColumnName |
Target column name: This is prediction values column. Also known as label column name in context of classification tasks. (Inherited from AutoMLVertical) |
TrainingData |
[Required] Training data input. (Inherited from AutoMLVertical) |
ValidationData |
Validation data inputs. |
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. |