Introducing Easy Labeling: A Free Web-Based Tool for YOLO Object Detection

Easy Labeling Project Page: https://mouseball54.github.io/easy_labeling/

Hello and welcome to the first post on MouseBall54’s Toolbox!

In this post, I’m excited to introduce Easy Labeling, a web-based image annotation tool I developed to simplify the creation of datasets, especially for YOLO format object detection.

What is Easy Labeling? A Better Way to Build YOLO Datasets

Easy Labeling was created to streamline the often tedious process of building high-quality datasets for object detection models, particularly those in the YOLO family. Its core philosophy is to be a “local-first” application. It runs entirely in your browser and uses the File System Access API to work directly with your local image and label folders. This means you never have to upload your data to a server, ensuring both privacy and speed.

The primary output of the tool is annotation files in the widely-used YOLO text format (.txt), and it includes several convenience features for YOLO users, such as loading class names from .yaml files.

Key Features

• Full YOLO Format Support: Natively creates label files in the YOLO format and enhances workflow by loading class definitions from .yaml files.
• Local File System Integration: Works directly with files on your local machine. No uploads required.
• Comprehensive Annotation Tools:
  • Draw, edit, move, resize, and delete bounding boxes.
  • Switch between dedicated “draw” and “edit” modes for precision.
  • Fine-grained canvas control with zoom, pan, and direct coordinate input.
• Efficient Workflow and UI:
  • Image preview bar, synchronized selection between canvas and label list, and class-based filtering.
  • Extensive keyboard shortcuts to accelerate your workflow.
• Advanced Label Management:
  • Perform bulk actions, such as changing the class for multiple selected bounding boxes at once.
• Flexible Configuration: Supports various image formats (JPG, PNG, TIFF), an auto-save feature, and a persistent dark mode.

Future Plans

I plan to add more features, including data augmentation capabilities and support for other annotation formats. I’ll be sharing development progress and technical challenges right here on this blog.

If you’re interested in the project, please check out the GitHub repository. Your interest and feedback on this YOLO annotation tool are greatly appreciated!

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