Selecting the best annotation tools for your computer vision projects can significantly affect your workflow. How quickly you can reach your ultimate goal, which is a reliable and useful computer vision model, depends on how well the tool you choose helps you get things done.
At Roboflow, we are always working to reduce the amount of time and work needed to label data, so that you can put your models into production sooner. In order to do this, we have done a lot of research on the different annotation tools that are currently on the market. Below we have mentioned the best annotation tools.
Features to Consider When Choosing an Annotation Tool
🧩 Attraction: Types of Annotations Before you begin using an annotation tool, consider the types of annotations you require for your project. These could include bounding boxes, polygons, image segmentation, named entity recognition, sentiment analysis, or audio transcription.
🖥️ Attraction: Simple to Use Ensure that the chosen tool is user-friendly and features a straightforward interface. This simplicity will facilitate the learning curve for annotators, making the annotation process smoother.
🤝 Attraction: Collaboration and Taking Care of Users When selecting an annotation tool, look for collaborative features that allow multiple annotators to work on the same project simultaneously. Additionally, consider tools that offer role-based access control, ensuring secure project management.
🚀 Attraction: Automation and Help from AI Some annotation tools incorporate AI-assisted annotation capabilities. These AI features can greatly accelerate the annotation process by providing suggestions or even pre-annotating data.
📤 Attraction: Import/Export of Data Don’t forget to check if the tool supports the import and export of annotated data in various formats. This functionality ensures compatibility with your existing data pipelines and machine learning frameworks.
Best Annotation Tools Comparison Table
The table below compares the best annotation tools, showing their main features, prices, and how well they work for different tasks. This resource gives users the information they need to choose the best annotation tool for their needs, whether it’s for labeling images, annotating text, or analyzing data.
| Annotation Tool | Pricing Model | Ease of Use | Collaboration | Data Security | Supported Formats |
|---|---|---|---|---|---|
| Scale AI | Subscription | User-friendly | Yes | Yes | Images, Videos |
| Labelbox | Subscription | User-friendly | Yes | Yes | Images, Videos |
| Make Sense | Subscription | User-friendly | Yes | Yes | Images, Videos |
| CVAT | Open Source | Moderate | Yes | Customizable | Images, Videos |
| Roboflow Annotate | Subscription | User-friendly | Yes | Yes | Images, Videos |
Scale AI
Features
- High-quality data annotation services.
- Offers a range of annotation types like bounding boxes, segmentation, and more.
- Integrates with various machine learning frameworks.
- Provides a large and skilled annotator workforce.
- Supports data security and compliance.
Scale AI has a set of tools for annotating data in images, text, video, and audio, among other things. The Scale Data Engine, which is their tool for annotating images, has tools for both curating your dataset to make sure you have all the images you need and annotating your data. Overall, this is one of the best Annotation Tools you can consider now.
Like Labelbox, Scale JSON can be changed to other formats so that different models can be trained on it. Scale also has a tool for evaluating models that helps you find ways to make your dataset better. Scale has an integration that lets you ask outside annotators for help labeling your datasets, which is great if you don’t already have an internal annotation team.
Pros
- High-quality annotations with human annotators.
- Scalable and suitable for a wide range of tasks.
- Strong quality control and project management features.
Cons
- Can be relatively expensive.
- May not be as fast as fully automated solutions for some tasks.
Labelbox
Features
- Versatile annotation platform for computer vision tasks.
- Collaboration tools for teams.
- Customizable annotation workflows.
- Integrates with popular ML frameworks.
- Offers automation and active learning features.
Labelbox is a tool for adding notes to data. It has a visual interface that lets you both add notes and look through your data. You can add comments to images, videos, geospatial imagery, natural language documents, audio, and HTML using Labelbox. Once you’ve labeled your data, you can export it to the Labelbox JSON format and then convert it to one of 19 other formats, depending on what your training model needs.
The Labelbox platform comes with a set of tools for working together that are meant to make it easier to add annotations to large datasets. Labelbox has a review queue where images can be approved or sent back to be changed. It also has tools to see how much time was spent labeling and how labels are spread across a dataset, as well as tools for commenting and more. Still, this is one of the best Annotation Tools you can consider now.
Pros
- Versatile and user-friendly platform.
- Supports both manual and automated annotation.
- Integrations with popular machine learning frameworks.
Cons
- Costs can add up, especially for large-scale projects.
- Learning curve for advanced features.
Make Sense
Features
- User-friendly annotation tool.
- Supports image and video annotation.
- Includes object detection, segmentation, and keypoint annotation.
- Real-time collaboration and comments.
- Easy sharing and exporting of annotated data.
Make Sense is a free, open-source, GPLv3-licensed computer vision annotation tool. The hosted version of Make Sense, which can be found at makesense.ai, does not need to be signed up for or installed. The tool runs entirely in your browser, and your data never leaves your browser.
After you add notes to images, you need to save those notes to your own computer. Make Sense lets you export in YOO, VOC XML, and VGG JSON, among other formats. You can use bounding boxes, lines, points, and polygons to make annotations. Overall, this is one of the best Annotation Tools you can consider now.
Pros
- Simple and intuitive user interface.
- Good for small to medium-sized projects.
- Cost-effective.
Cons
- Limited advanced features compared to some other tools.
- May not be suitable for complex tasks.
CVAT
Features
- Open-source annotation platform.
- Supports various annotation formats.
- Offers both 2D and 3D annotation capabilities.
- Team collaboration and user management features.
- Customizable and extendable through plugins.
CVAT is a free tool for adding notes to images. This tool was originally made by Intel, but it is now kept up to date by OpenCV, which makes many widely used image and vision tools. You can use CVAT online at cvat.ai, or you can download the software and run it on your own computer. Over 60,000 developers use CVAT.
One of the ways CVAT automates labeling is by integrating with the Roboflow platform. To help you label images in CVAT, you can use any of your private models or models hosted on Roboflow Universe. This cuts down on the number of manual annotations you have to make, making it easier than ever to get your dataset ready. Thus, this is one of the best Annotation Tools you can consider now.
Pros
- Open-source and free to use.
- Customizable for specific annotation needs.
- Supports a variety of annotation types.
Cons
- Requires technical expertise for setup and maintenance.
- Limited support and documentation compared to commercial tools.
Roboflow Annotate
Features
- An annotation tool by Roboflow.
- Supports object detection and segmentation.
- Offers model-assisted annotation for faster labeling.
- Integrates with Roboflow’s data management and training platform.
- Collaboration and versioning features for teams.
Roboflow Annotate is a web-based annotation tool that more than 250,000 engineers use to label images for tasks like object detection, classification, and segmentation. Roboflow Annotate has a powerful feature called Label Assist that can automatically label images in your dataset by using an older version of your model or one of the more than 50,000 public models on Roboflow Universe.
The rest of the Roboflow ecosystem works with Roboflow Annotate. When images are labeled, you can use them with our AutoML solution to train a model and make an API that can be used by anyone to ask questions about the model. We also have SDKs that make deployment to devices like the NVIDIA Jetson and the Luxonis OAK faster. Overall, this is one of the best Annotation Tools you can consider now.
Pros
- Integration with Roboflow’s comprehensive computer vision platform.
- Simplified annotation process.
- Cost-effective for small to medium-sized projects.
Cons
- May lack advanced features required for complex tasks.
- Limited flexibility compared to some other tools.
Benefits of Using Annotation Tools
📌 Enhanced Communication: Annotations provide a clear and concise way to communicate feedback, instructions, or information. They help in conveying ideas and highlighting specific points within content.
📌 Collaboration: Annotation tools facilitate collaboration by enabling multiple users to review and comment on the same content simultaneously, regardless of their physical location. This is especially valuable for remote teams and distributed workforces.
📌 Efficient Document Review: In industries like legal, healthcare, and research, annotations streamline the review process for documents, contracts, medical records, and research papers. Users can leave comments, highlight important sections, and suggest changes, which helps in error identification and revision.
📌 Education and Training: Annotation tools are valuable in educational settings. Teachers can provide feedback on students’ assignments, and students can annotate textbooks or lecture notes for better comprehension. They are also useful for eLearning platforms and online courses.
📌 Content Curation: Content creators, marketers, and researchers can use annotation tools to curate and organize content. Annotations can be used to categorize, tag, or add context to content, making it easier to find and reference later.
FAQs
CVAT is one of the most popular open-source tools in the field, with over 1 million downloads since 2021. 3D Slicer, Labelimg, VoTT (Visual Object Tagging Tool, made by Microsoft), VIA (VGG Image Annotator), LabelMe, and Label Studio are also popular free alternatives to CVAT for annotating images.
When it comes to finding an OCR annotation tool, Abbyy FineReader, OmniPage Ultimate, and Adobe Acrobat Pro are the best. Tesseract is a good example of open source.
