17 Best Data Annotation and Data Labeling Tools in 2024
Data annotation and labeling are essential for training machine learning models. These tools enable businesses to prepare their data for AI applications by labeling images, text, and video content. The rise of AI-driven solutions in industries like healthcare, autonomous driving, and e-commerce has increased the demand for high-quality data labeling tools.
Here are the 17 best data annotation and labeling tools for 2024:
Labelbox
Amazon SageMaker Ground Truth
Scale AI
SuperAnnotate
Diffgram
V7
Supervisely
Dataturks
CVAT (Computer Vision Annotation Tool)
Prodigy
Hive Data
Appen
Lionbridge AI
Clarifai
Playment
Datasaur
Dataloop
These tools provide essential features for labeling large datasets, such as automated labeling, collaboration tools, and AI-assisted annotations. Labelbox and Amazon SageMaker Ground Truth stand out for their comprehensive solutions, offering integration with machine learning platforms for seamless model training. Scale AI is renowned for its speed and accuracy in labeling, making it a top choice for industries requiring large volumes of annotated data.
SuperAnnotate and Supervisely offer powerful collaboration features, allowing teams to work together on annotation projects, which is ideal for complex, large-scale AI initiatives. CVAT is an open-source tool that provides essential annotation capabilities, making it a popular choice for businesses with in-house development teams.
In conclusion, data annotation and labeling tools are critical for AI development. Whether you’re working with images, video, or text, these tools will help you prepare high-quality datasets to train your machine learning models effectively.
This text was generated using a large language model, and select text has been reviewed and moderated for purposes such as readability.
