This topic describes how to create a labeling job.

Prerequisites

A dataset is registered. For more information about how to register a dataset, see Register a dataset.

Procedure

  1. Log on to the Machine Learning Platform for AI console.
  2. In the left-side navigation pane of the Machine Learning Platform for AI console, choose Data Preprocessing > Smart Labeling.
  3. On the Smart Labeling page, click Create Labeling Job.
  4. In the Template step, set the parameters and click Next.
    Parameter Description
    Template The template to be used in the labeling job. The system supports the following templates:
    • Image
      • Object Detection
      • Semantic Segmentation
      • Image Comprehensive Label
      • OCR
      • Image Classification
    • Text

      Text Classification

    • Video
      • Video Classification
      • Object Annotation
    Labels The labels that are used to classify images. This parameter takes effect only when you select Object Detection, Semantic Segmentation, or Image Comprehensive Label for the Template parameter.
    Image and Text Orientation Label Image Orientation Specifies whether to annotates image orientation. This parameter takes effect only when you select OCR for the Template parameter.
    Flip Text Specifies whether to annotates text orientation. If the text in an image is placed in the same direction as the image, you can turn off the switch. This parameter takes effect only when you select OCR for the Template parameter.
    Text Type The labels that are used to classify the text. This parameter takes effect only when you select OCR for the Template parameter.
    Add Custom Label The custom labels that are used to classify the text. This parameter takes effect only when you select OCR for the Template parameter.
    Labeling Type Valid values: Single-label and Multi-label. You can select the labeling type based on your needs. This parameter takes effect only when you select Image Classification for the Template parameter.
    Labels The labels that are used to classify images. Labels are displayed in different colors. This parameter takes effect only when you select Image Classification for the Template parameter.
  5. In the Basic Information step, set the parameters and click Next.
    Parameter Description
    Task Name The name must be 1 to 30 characters in length and can contain underscores (_) and hyphens (-). It must start with a letter or a digit.
    Description The description must be 1 to 64 characters in length and can contain underscores (_) and hyphens (-). It must start with a letter or a digit.
    Input Dataset Select one or more datasets to create a labeling job. The datasets must correspond to the topic of the labeling job. If no dataset is available, click Register Dataset next to Input Dataset to register a dataset.
    Output Dataset Path The Object Storage Service (OSS) path to which the labeling results are stored. When you handle a labeling job, every time you click Generate Result Dataset, a result dataset is generated in the specified OSS path. The dataset contains the results of all topics that you have completed.
  6. In the Labeling Policy step, set the parameters and click Submit.
    Parameter Description
    Dispatch Policy The default dispatch policy is Number of topics collected by a worker each time and cannot be changed.
    Topics per Collection The number of topics collected by each worker each time.
    Note The value of the Topics per Collection parameter can be smaller than the total number of topics divided by the total number of workers. This allows workers with high efficiency to collect more topics and improves the overall efficiency of data labeling.
    Add Worker You can specify one or more workers. You can select both Alibaba Cloud accounts and RAM users.