Top 10 Open Source Data Labeling/Annotation Platforms in 2024

Data labeling/annotation identifies targeted raw data such as images, text documents, audio files, etc., that are used to train ML models to make accurate predictions about future events. For example, before an ML model can predict whether an image contains a person or not, it must be trained on a large dataset with correctly labeled pictures.

To label data, organizations need a tool. However, these pre-built solutions may not meet the specific needs of each company. Therefore, modifiable open source platforms for data labeling can be a more effective alternative.

In this article, we will explore open-source data labeling platforms and their applicability and then briefly introduce 10 of them.

What are open source data labeling platforms?

Open-source data labeling platforms enable firms to customize existing data labeling solutions without having to build software from scratch. Companies’ strategies vary, so using template solutions is not effective in all cases. In such cases, where the budget or time of the companies is limited, using open code data labeling platforms is an effective solution for them.

Using open-source software allows IT to implement new code into the company’s data labeling facilities to customize functionality and achieve the desired result.

What are the examples of open source platforms for data labeling?

Here is a list of the top ten open source data labeling platforms:

To choose the data annotation tool or service that best suits your business needs, check out our sortable and filterable lists:

• Medical data annotation services
• Data annotation services
• Video annotation tools

Further reading

• data labeling
• data annotation
• video annotation
• video annotation tools

We can also guide you to choose the right vendor for your data labeling purposes:

This article was drafted by former AIMultiple industry analyst Görkem Gençer.