X-AnyLabeling

X-AnyLabeling

Effortless data labeling with AI support from Segment Anything and other awesome models.

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X-AnyLabeling is a robust annotation tool that seamlessly incorporates an AI inference engine alongside an array of sophisticated features. Tailored for practical applications, it is committed to delivering comprehensive, industrial-grade solutions for image data engineers. This tool excels in swiftly and automatically executing annotations across diverse and intricate tasks.

README:

X-AnyLabeling

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Auto-Labeling
Text/Visual Prompting and Prompt-free for Detection & Segmentation
Detect Anything
Segment Anything
Chatbot
VQA

🥳 What's New

  • Bump version to 3.2.2
  • Add AI Assistant and prompt template management for VQA
  • Add support for batch editing multiple shapes simultaneously
  • Add support for Show/Hide shape attributes on canvas
  • Add support for automated training platform with Ultralytics tasks in X-AnyLabeling Link
  • For more details, please refer to the CHANGELOG

X-AnyLabeling

X-AnyLabeling is a powerful annotation tool that integrates an AI engine for fast and automatic labeling. It's designed for multi-modal data engineers, offering industrial-grade solutions for complex tasks.

Features

  • Processes both images and videos.
  • Accelerates inference with GPU support.
  • Allows custom models and secondary development.
  • Supports one-click inference for all images in the current task.
  • Enable import/export for formats like COCO, VOC, YOLO, DOTA, MOT, MASK, PPOCR, MMGD, VLM-R1.
  • Handles tasks like classification, detection, segmentation, caption, rotation, tracking, estimation, ocr and so on.
  • Supports diverse annotation styles: polygons, rectangles, rotated boxes, circles, lines, points, and annotations for text detection, recognition, and KIE.

Model library

Task Category Supported Models
🖼️ Image Classification YOLOv5-Cls, YOLOv8-Cls, YOLO11-Cls, InternImage, PULC
🎯 Object Detection YOLOv5/6/7/8/9/10, YOLO11/12, YOLOX, YOLO-NAS, D-FINE, DAMO-YOLO, Gold_YOLO, RT-DETR, RF-DETR
🖌️ Instance Segmentation YOLOv5-Seg, YOLOv8-Seg, YOLO11-Seg, Hyper-YOLO-Seg
🏃 Pose Estimation YOLOv8-Pose, YOLO11-Pose, DWPose, RTMO
👣 Tracking Bot-SORT, ByteTrack
🔄 Rotated Object Detection YOLOv5-Obb, YOLOv8-Obb, YOLO11-Obb
📏 Depth Estimation Depth Anything
🧩 Segment Anything SAM, SAM-HQ, SAM-Med2D, EdgeSAM, EfficientViT-SAM, MobileSAM,
✂️ Image Matting RMBG 1.4/2.0
💡 Proposal UPN
🏷️ Tagging RAM, RAM++
📄 OCR PP-OCR
🗣️ VLM Florence2
🛣️ Land Detection CLRNet
📍 Grounding CountGD, GeCO, Grunding DINO, YOLO-World, YOLOE
📚 Other 👉 model_zoo 👈

Docs

  1. Installation & Quickstart
  2. Usage
  3. Customize a model
  4. Chatbot
  5. VQA

Examples

Contribute

We believe in open collaboration! X‑AnyLabeling continues to grow with the support of the community. Whether you're fixing bugs, improving documentation, or adding new features, your contributions make a real impact.

To get started, please read our Contributing Guide and make sure to agree to the Contributor License Agreement (CLA) before submitting a pull request.

If you find this project helpful, please consider giving it a ⭐️ star! Have questions or suggestions? Open an issue or email us at [email protected].

A huge thank you 🙏 to everyone helping to make X‑AnyLabeling better.

License

This project is licensed under the GPL-3.0 license and is only free to use for personal non-commercial purposes. For academic, research, or educational use, it is also free but requires registration via this form here. If you intend to use this project for commercial purposes or within a company, please contact [email protected] to obtain a commercial license.

Acknowledgement

I extend my heartfelt thanks to the developers and contributors of AnyLabeling, LabelMe, LabelImg, roLabelImg, PPOCRLabel and CVAT, whose work has been crucial to the success of this project.

Citing

If you use this software in your research, please cite it as below:

@misc{X-AnyLabeling,
  year = {2023},
  author = {Wei Wang},
  publisher = {Github},
  organization = {CVHub},
  journal = {Github repository},
  title = {Advanced Auto Labeling Solution with Added Features},
  howpublished = {\url{https://github.com/CVHub520/X-AnyLabeling}}
}

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