Baidu Data Labeling Platform Tutorial282

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Baidu Data Labeling Platform (BDP) is a powerful tool that allows you to quickly and easily label large datasets of images, text, and audio. This makes it an ideal platform for tasks such as object detection, image classification, natural language processing, and speech recognition.
In this tutorial, we will walk you through the basics of using BDP. We will cover how to create a project, import data, label data, and export the results.
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To create a project, click on the "Create Project" button on the BDP homepage. You will then need to select a project name and template. The template will determine the types of data that you can label and the tools that will be available to you.
Once you have selected a template, click on the "Create" button. Your project will then be created and you will be redirected to the project dashboard.
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The next step is to import the data that you want to label. BDP supports a variety of data formats, including images, text, and audio.
To import data, click on the "Import Data" button on the project dashboard. You can then select the data that you want to import from your local computer or from a cloud storage service.
Once you have selected the data that you want to import, click on the "Start Import" button. The data will then be imported into your project and you will be able to start labeling it.
## Labeling Data
To label data, click on the "Label Data" tab on the project dashboard. You will then be presented with a list of the data that you have imported.
To label a data item, click on the "Label" button. You will then be presented with a variety of tools that you can use to label the data. The tools that are available to you will depend on the type of data that you are labeling.
Once you have labeled the data, click on the "Save" button. The label will then be saved to your project.
## Exporting Results
Once you have labeled all of the data in your project, you can export the results. To do this, click on the "Export Results" tab on the project dashboard.
You can then select the format that you want to export the results in. BDP supports a variety of formats, including JSON, CSV, and XML.
Once you have selected the format that you want to export the results in, click on the "Start Export" button. The results will then be exported to your local computer or to a cloud storage service.
## Conclusion
BDP is a powerful tool that can help you to quickly and easily label large datasets of data. This makes it an ideal platform for tasks such as object detection, image classification, natural language processing, and speech recognition.
In this tutorial, we have walked you through the basics of using BDP. We have covered how to create a project, import data, label data, and export the results.

2025-02-01

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