Data Labeling¶

AI Lab provides the data labeling feature. By adding labels or annotations to raw data such as images, videos, text, and audio, it provides high-quality training data for machine learning models, thereby improving the comprehension and accuracy of the models.

Create a Data Labeling Task¶

1. In the left navigation bar, click Data Management -> Data Labeling, and then click the Create button on the right.

2. Select the worker cluster, namespace, and queue to which the data labeling task belongs, configure the source data, type, and labeling results of the task, and then click OK.

3. Upon successful creation, you will be returned to the data labeling task list. You can perform more actions by clicking ┇ on the right.

Download Labeling Results¶

The labeling results can be downloaded with one click. On the right side of the data labeling task list, click ┇, then choose Download Labeling Results from the dropdown menu.

Delete a Data Labeling Task¶

If you find a data labeling task to be redundant or no longer needed, you can delete it from the data labeling task list.

1. Click the ┇ on the right side of the data labeling task list, then choose Delete from the dropdown menu.

2. In the pop-up window, confirm the data labeling task you want to delete, and then click Delete.

3. A confirmation message will appear indicating successful deletion, and the task will disappear from the list.

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