Help Center> ModelArts> Data Labeling> Introduction to Data Labeling
Updated on 2024-04-12 GMT+08:00

Introduction to Data Labeling

Data management is being upgraded and is invisible to users who have not used data management.

Model training requires a large amount of labeled data. Therefore, before training a model, label data. ModelArts provides you with the following labeling functions:

  • Manual Labeling: allows you to manually label data.
  • Auto Labeling: allows you to automatically label remaining data after a small amount of data is manually labeled.
  • Team Labeling: allows you to perform collaborative labeling for a large amount of data.

Manual Labeling

Create a labeling job based on the dataset type. ModelArts supports the following types of labeling jobs:

  • Images
    • Image classification: identifies a class of objects in images.
    • Object detection: identifies the position and class of each object in an image.
    • Image segmentation: segments an image into different areas based on objects in the image.
  • Audio
    • Sound classification: classifies and identifies different sounds.
    • Speech labeling: labels speech content.
    • Speech paragraph labeling: segments and labels speech content.
  • Text
    • Text classification: assigns labels to text according to its content.
    • Named entity recognition: assigns labels to named entities in text, such as time and locations.
    • Text triplet: assigns labels to entity segments and entity relationships in the text.
  • Video

    Video labeling: identifies the position and class of each object in a video. Only the MP4 format is supported.

Auto Labeling

In addition to manual labeling, ModelArts also provides the auto labeling function to quickly label data, reducing the labeling time by more than 70%. Auto labeling means learning and training are performed based on the labeled images and an existing model is used to quickly label the remaining images.

Only datasets of image classification and object detection types support the auto labeling function.

Team Labeling

Generally, a small data labeling task can be completed by an individual. However, team work is required to label a large dataset. ModelArts provides the team labeling function. A labeling team can be formed to manage labeling for the same dataset.

The team labeling function supports only datasets for image classification, object detection, text classification, named entity recognition, text triplet, and speech paragraph labeling.

Dataset Functions

Dataset functions vary depending on dataset types. For details, see Table 1.

Table 1 Functions supported by different types of datasets

Dataset Type

Labeling Type

Manual Labeling

Auto Labeling

Team Labeling

Images

Image classification

Supported

Supported

Supported

Object detection

Supported

Supported

Supported

Image segmentation

Supported

N/A

N/A

Audio

Sound classification

Supported

N/A

N/A

Speech labeling

Supported

N/A

N/A

Speech paragraph labeling

Supported

N/A

Supported

Text

Text classification

Supported

N/A

Supported

Named entity recognition

Supported

N/A

Supported

Text triplet

Supported

N/A

Supported

Video

Video labeling

Supported

N/A

N/A

Free format

N/A

N/A

N/A

N/A

Table

N/A

N/A

N/A

N/A