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5 best data annotation tools in 2024
Data annotation plays a key role in the development of a wide range of technologies: from autopilots and voice assistants to agriculture and heavy industry. But the annotation process itself can be labor-intensive and time-consuming.
To simplify this task, it is important to choose tools that are suitable for your task and can make the work faster and more convenient.
In this guide, we will analyze the most popular data markup solutions and figure out which one is right for you.
CVAT
CVAT (Computer Vision Annotation Tool) has become one of the most popular tools for image annotation due to its functionality and ease of use. By the way, not everyone knows that the tool was created by guys from Nizhny Novgorod. At Data Light, we often use it for completely different projects. Here is a list of the main advantages and disadvantages of the tool:
Advantages of CVAT
Convenient web version: CVAT offers users the ability to work through a web interface, eliminating the need to install the program on a computer.
Customization: CVAT, as an open-source solution, provides users with complete freedom to customize the platform to their needs. This makes the tool flexible and adaptable, allowing it to be integrated into various workflows. The CVAT documentation contains detailed instructions on customization, making the setup process more accessible even for beginners.
Multifunctionality: CVAT supports various types of annotations, including bounding boxes, polygons, key points, and others. This makes it a versatile tool for different projects.
Teamwork: One of the strengths of CVAT is the ability to organize collaborative work. The tool allows multiple users to work on the same project simultaneously, distributing tasks among team members.
And one more feature: project managers have full access to all tasks, while performers see only those assigned to them. This allows for efficient workflow management and increases team productivity.
Cost-effective pricing policy: CVAT offers competitive usage conditions, making it an attractive option compared to other tools.
Active community: Like many open-source projects, CVAT has an active community of users and developers. This community constantly works on improving the platform, sharing ideas, solving emerging problems, and offering new features.
Detailed documentation: CVAT documentation includes detailed descriptions of functionality, usage examples, life hacks, and images. Regular updates to the documentation ensure that users are always aware of the latest changes and improvements.
Disadvantages of CVAT
High resource requirements: One of the main disadvantages of CVAT is its high server resource requirements, which can be a problem for some teams. For example, in one of our projects, where image annotation with a large number of small ore bubbles was required, CVAT simply could not load the data. We had to split each image into four parts, annotate them separately, and then merge them back together.
Complex installation and setup: Although CVAT has extensive customization capabilities, the process of installing and setting it up can be quite complex, especially for those who do not have experience with such tools, while in some of the other applications on the list, you can simply register and start working right away.
LabelMe
LabelMe is an open-source web tool developed in Python, and it is mainly used for image annotation. This tool provides various capabilities for creating different types of annotations and exporting data in various formats.
Advantages:
Flexibility: LabelMe allows creating and adapting annotations for specific project tasks, making it a versatile tool.
Simple interface: The intuitive interface makes the tool easy to use even for those without deep technical skills.
Stable and easy to use: The tool can be accessed from anywhere, and it allows annotating images without installing the program or copying large datasets to your computers.
Customization capability: Users can create custom functions using HTML and JavaScript. And a separate plus: the tool allows extracting segmentation masks.
Disadvantages:
Limited formats: Data can only be saved in JSON format, and working with other formats requires using third-party scripts.
Does not support team coordination: LabelMe does not provide convenient tools for collaboration. It also does not allow monitoring annotation performance and quality control in real-time.
Limited capabilities for working with large datasets: The tool does not support backup and management of large datasets, making it less suitable for large-scale projects. Additionally, it requires manually distributing and collecting statistics, which increases operational costs.
LabelImg
LabelImg — is one of the simplest and most convenient tools for quick image annotation. It supports many data annotation formats and is easy to install on Windows operating systems.
Advantages:
Ease of use: LabelImg is perfect for quickly creating annotations on small datasets due to its ease of learning.
Convenient application compatible with different systems: LabelImg is written in Python and uses Qt for its graphical interface. This makes it an excellent choice for Linux-based systems, which are not supported by many annotation programs.
In addition, for Windows, LabelImg offers a standalone application that does not require installation and is just over 13 MB in size.
Disadvantages:
Limited features: LabelImg is limited to annotating objects in the form of bounding boxes, which narrows its application to object and face detection and recognition tasks. Moreover, LabelImg's annotation export does not support popular formats such as COCO and OpenImages.
Does not support data augmentation with images: this limits the use of the tool for creating datasets. Data augmentation often has to be done during training using deep learning libraries.
Supervisely
Supervisely is a platform designed for the complete support of computer vision projects. It covers the entire development and research cycle, from data annotation to model training.
Advantages:
User-friendly interface: Users appreciate Supervisely for its intuitive and customizable interface, which simplifies working with the platform.
Developed ecosystem of applications: Supervisely Apps already offers many ready-made widgets that allow you to extend the functionality of any part of the platform. Each of them has open source code and is available on GitHub, which allows not only modifying existing applications but also creating new ones.
Flexible pricing: The cost of use depends on the selected modules and the number of users, rather than the volume of annotations, which allows you to control costs.
Efficiency when working with large images: Unlike CVAT, Supervisely provides high-quality annotation of large images without the need for compression.
Disadvantages:
High cost: Despite its extensive capabilities, Supervisely may be a less cost-effective choice compared to other tools.
Label Studio
Label Studio is a multifunctional tool used for data annotation in computer vision tasks. Thanks to its modular architecture, its functionality is easily extended and adapted to the specific needs of the project.
Advantages:
Simplicity and convenience: The Label Studio interface is intuitive and allows you to get started quickly. All major actions can be performed in one window, saving time.
Extensibility: The modular structure makes it easy to add new features and integrate additional types of annotations.
Flexibility: Users can create annotations using code, which opens up new customization possibilities.
Disadvantages:
High resource requirements: Full use of Label Studio may require a significant amount of resources, making it less convenient for users with limited capabilities.
Bounding Boxes annotation limitations: While, for example, CVAT offers a more convenient and faster tool for Bounding Boxes annotation, Label Studio is better suited for audio data annotation.
The choice of annotation tool depends on the specifics of the project, data volumes, and functional requirements. If your goal is flexibility and ease of use, then LabelMe and LabelImg can be excellent choices for small projects. However, Supervisely and Label Studio offer broader capabilities and are suitable for working with large data sets and complex tasks.
If you are interested in learning more about annotation in CVAT, how Data Light uses the tool in projects, and what life hacks we have found, read this article:
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