x-anylabeling-cvhub 3.3.9

Advanced Auto Labeling Solution with Added Features

English | 简体中文

Auto-Training

Auto-Labeling

Detect Anything

Segment Anything

Promptable Concept Grounding

VQA

Chatbot

Image Classifier

🥳 What's New

• Added PP-DocLayoutV3, supporting multi-point localization (quadrilaterals/polygons) and logical reading order prediction
• Added PaddleOCR-VL-1.5, supporting OCR, table recognition, formula recognition, chart recognition, text spotting, and seal recognition
• Added YOLO26 series models for object detection, instance segmentation, pose estimation, and rotated object detection
• Added Compare View feature for split-screen image comparison (ideal for infrared/visible fusion, mask preview, and super-resolution) [docs]
• Added multimodal large language model Rex-Omni with support for grounding, keypoints, referring pointing, OCR, and visual prompting tasks [docs]
• Added powerful file search feature upporting text search, regular expression search, and attribute-based filtering [docs]
• Added semi-transparent mask rendering for polygon, rectangle, rotation, and circle shapes with toggle support (Ctrl+M)
• Added one-click text and visual prompt video detection and segmentation tracking based on Segment Anything 3 [docs]
• 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.

Also, we highly recommend trying out X-AnyLabeling-Server, a simple, lightweight, and extensible framework that enables remote inference capabilities for X-AnyLabeling.

Features

• Supports remote inference service.
• 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.
• Supports 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, vqa, grounding 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, YOLO11/12/26, YOLOX, YOLO-NAS, D-FINE, DAMO-YOLO, Gold_YOLO, RT-DETR, RF-DETR, DEIMv2
🖌️ Instance Segmentation	YOLOv5-Seg, YOLOv8-Seg, YOLO11-Seg, YOLO26-Seg, Hyper-YOLO-Seg, RF-DETR-Seg
🏃 Pose Estimation	YOLOv8-Pose, YOLO11-Pose, YOLO26-Pose, DWPose, RTMO
👣 Tracking	Bot-SORT, ByteTrack, SAM2/3-Video
🔄 Rotated Object Detection	YOLOv5-Obb, YOLOv8-Obb, YOLO11-Obb, YOLO26-Obb
📏 Depth Estimation	Depth Anything
🧩 Segment Anything	SAM 1/2/3, SAM-HQ, SAM-Med2D, EdgeSAM, EfficientViT-SAM, MobileSAM
✂️ Image Matting	RMBG 1.4/2.0
💡 Proposal	UPN
🏷️ Tagging	RAM, RAM++
📄 OCR	PP-OCRv4, PP-OCRv5, PP-DocLayoutV3, PaddleOCR-VL-1.5
🗣️ Vision Foundation Models	Rex-Omni, Florence2
👁️ Vision Language Models	Qwen3-VL, Gemini, ChatGPT
🛣️ Land Detection	CLRNet
📍 Grounding	CountGD, GeCO, Grounding DINO, YOLO-World, YOLOE
📚 Other	👉 model_zoo 👈

Docs

0. Remote Inference Service
1. Installation & Quickstart
2. Usage
3. Command Line Interface
4. Customize a model
5. Chatbot
6. VQA
7. Multi-class Image Classifier

Examples

• Classification
  • Image-Level
  • Shape-Level
• Detection
  • HBB Object Detection
  • OBB Object Detection
• Segmentation
  • Instance Segmentation
  • Binary Semantic Segmentation
  • Multiclass Semantic Segmentation
• Description
  • Tagging
  • Captioning
• Estimation
  • Pose Estimation
  • Depth Estimation
• OCR
  • Text Recognition
  • Key Information Extraction
• MOT
  • Tracking by HBB Object Detection
  • Tracking by OBB Object Detection
  • Tracking by Instance Segmentation
  • Tracking by Pose Estimation
• iVOS
  • SAM2-Video
  • SAM3-Video
• Matting
  • Image Matting
• Vision-Language
  • Rex-Omni
  • Florence 2
• Counting
  • GeCo
• Grounding
  • YOLOE
  • SAM 3
• Training
  • Ultralytics

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 [e-mail].

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 completely open source and free. The original intention is to enable more developers, researchers, and enterprises to conveniently use this AI application platform, promoting the development of the entire industry. We encourage everyone to use it freely (including commercial use), and you can also add features based on this project and commercialize it, but you must retain the brand identity and indicate the source project address.

Additionally, to understand the ecosystem and usage of X-AnyLabeling, if you use this project for academic, research, teaching, or enterprise purposes, please fill out the registration form. This registration is only for statistical purposes and will not incur any fees. We will strictly keep all information confidential.

X-AnyLabeling is independently developed and maintained by an individual. If this project has been helpful to you, we welcome your support through the donation links below to help sustain the project's continued development. Your support is the greatest encouragement! If you have any questions about the project or would like to collaborate, please feel free to contact via WeChat: ww10874 or email provided above.

Sponsors

• buy-me-a-coffee
• Wechat/Alipay

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}}
}

---

🔝 Back to Top