
X-AnyLabeling
Effortless data labeling with AI support from Segment Anything and other awesome models.
Stars: 6474

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:
Auto-Labeling
Text/Visual Prompting and Prompt-free for Detection & Segmentation
VQA
- 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 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.
- Processes both
images
andvideos
. - 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 fortext detection
,recognition
, andKIE
.
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 👈 |
- Classification
- Detection
- Segmentation
- Description
- Estimation
- OCR
- MOT
- iVOS
- Matting
- Vision-Language
- Counting
- Training
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.
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.
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.
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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