X-AnyLabeling

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X-AnyLabeling: A lightweight, efficient, and unified cross-platform desktop application for annotating text, image, video, and multimodal data, combining versatile built-in tools with state-of-the-art AI models and flexible multi-format export.

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[English](README.md) | [简体中文](README_zh-CN.md)

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## 🥳 What's New

- `2026-08-12`: Release X-AnyLabeling v4.0.2.
- `2026-08-12`: Add support for [D-FINE-seg](https://github.com/ArgoHA/D-FINE-seg) instance segmentation models.
- `2026-08-08`: Add support for the [RT-DETRv2-OBB](https://xanylabeling.com/examples/detection/obb) rotated object detection model.
- `2026-08-08`: Add the [Magic Wand tool](https://xanylabeling.com/docs/x-anylabeling/user_guide#21-creating-shapes) for quickly creating polygons from contiguous color regions.
- `2026-08-05`: Release X-AnyLabeling v4.0.0.
- For more details, please refer to the [CHANGELOG](./CHANGELOG.md)

## Introduction

**X-AnyLabeling** is a lightweight, efficient, and unified cross-platform desktop application for AI-assisted annotation of text, image, video, and multimodal data. It combines versatile built-in tools, automated labeling workflows, state-of-the-art deep learning models, and flexible multi-format import and export. For remote inference, [X-AnyLabeling-Server](https://github.com/CVHub520/X-AnyLabeling-Server) provides a lightweight, extensible backend for connecting custom models and compute resources.

## Key Features

* Unified support for annotating and processing text, image, video, and multimodal data.
* Covers tasks such as image classification, object detection, instance segmentation, pose estimation, oriented object detection, multi-object tracking, optical character recognition, lane annotation, image captioning, visual question answering, and document parsing.
* Provides polygons, rectangles, cuboids, rotated boxes, quadrilaterals, circles, lines, polylines, points, masks, and task-specific tools for text detection, text recognition, and KIE.
* Integrates a wide range of state-of-the-art deep learning models for AI-assisted annotation, automated labeling, and batch dataset prediction.
* Supports both local and remote inference through engines and serving frameworks such as `ONNX Runtime`, `TensorRT`, `OpenCV DNN`, `vLLM`, and `SGLang`.
* Supports importing and exporting formats such as `COCO`, `VOC`, `YOLO`, `DOTA`, `MOT`, `MASK`, `PPOCR`, `MMGD`, `VLM-R1`, and `ShareGPT`.
* Runs on Windows, Linux, and macOS, with interfaces available in English, Simplified Chinese, Japanese, and Korean.
* Supports custom model integration, flexible extension, and secondary development.

## Model library

## Docs

0. [Remote Inference Service](https://github.com/CVHub520/X-AnyLabeling-Server)
1. [Installation & Quickstart](./docs/en/get_started.md)
2. [Usage](./docs/en/user_guide.md)
3. [Command Line Interface](./docs/en/cli.md)
4. [Customize a model](./docs/en/custom_model.md)
5. [Chatbot](./docs/en/chatbot.md)
6. [VQA](./docs/en/vqa.md)
7. [Image Classifier](./docs/en/image_classifier.md)
8. [Video Classifier](./docs/en/video_classifier.md)
9. [Document Parsing and Intelligent Text Recognition](./docs/en/paddle_ocr.md)

## Examples

- [Classification](./examples/classification/)
  - [Image-Level](./examples/classification/image-level/README.md)
  - [Shape-Level](./examples/classification/shape-level/README.md)
- [Detection](./examples/detection/)
  - [HBB Object Detection](./examples/detection/hbb/README.md)
  - [OBB Object Detection](./examples/detection/obb/README.md)
- [Segmentation](./examples/segmentation/README.md)
  - [Instance Segmentation](./examples/segmentation/instance_segmentation/)
  - [Binary Semantic Segmentation](./examples/segmentation/binary_semantic_segmentation/)
  - [Multiclass Semantic Segmentation](./examples/segmentation/multiclass_semantic_segmentation/)
- [Description](./examples/description/)
  - [Tagging](./examples/description/tagging/README.md)
  - [Captioning](./examples/description/captioning/README.md)
- [Estimation](./examples/estimation/)
  - [Face Estimation](./examples/estimation/face_estimation/README.md)
  - [Pose Estimation](./examples/estimation/pose_estimation/README.md)
  - [Depth Estimation](./examples/estimation/depth_estimation/README.md)
- [OCR](./examples/optical_character_recognition/)
  - [Text Recognition](./examples/optical_character_recognition/text_recognition/)
  - [Key Information Extraction](./examples/optical_character_recognition/key_information_extraction/README.md)
- [MOT](./examples/multiple_object_tracking/README.md)
  - [Tracking by HBB Object Detection](./examples/multiple_object_tracking/README.md)
  - [Tracking by OBB Object Detection](./examples/multiple_object_tracking/README.md)
  - [Tracking by Instance Segmentation](./examples/multiple_object_tracking/README.md)
  - [Tracking by Pose Estimation](./examples/multiple_object_tracking/README.md)
- [iVOS](./examples/interactive_video_object_segmentation)
  - [SAM2-Video](./examples/interactive_video_object_segmentation/sam2/README.md)
  - [SAM3-Video](./examples/interactive_video_object_segmentation/sam3/README.md)
- [Matting](./examples/matting/)
  - [Image Matting](./examples/matting/image_matting/README.md)
- [Vision-Language](./examples/vision_language/)
  - [Rex-Omni](./examples/vision_language/rexomni/README.md)
  - [Florence 2](./examples/vision_language/florence2/README.md)
- [Counting](./examples/counting/)
  - [GeCo](./examples/counting/geco/README.md)
  - [GeCo2](./examples/counting/geco2/README.md)
- [Grounding](./examples/grounding/)
  - [YOLOE](./examples/grounding/yoloe/README.md)
  - [SAM 3](./examples/grounding/sam3/README.md)
  - [LocateAnything](./examples/grounding/locateanything/README.md)
- [Training](./examples/training/)
  - [Ultralytics](./examples/training/ultralytics/README.md)

## 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](./CONTRIBUTING.md) and make sure to agree to the [Contributor License Agreement (CLA)](./CLA.md) before submitting a pull request.

If you find this project helpful, please consider giving it a ⭐️ star! Have questions or suggestions? Open an [issue](https://github.com/CVHub520/X-AnyLabeling/issues) or email us at cv_hub@163.com.

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

## License

This project is licensed under the [GNU General Public License v3.0](./LICENSE). You may use, modify, and redistribute the software, including for commercial purposes, provided that you comply with the terms of the license.

## Sponsor

X-AnyLabeling is an actively maintained open-source project. Your sponsorship helps support feature development, model integration, documentation, and community support.

Click the image above to visit the sponsorship page.

## Acknowledgement

I extend my heartfelt thanks to the developers and contributors of [AnyLabeling](https://github.com/vietanhdev/anylabeling), [LabelMe](https://github.com/wkentaro/labelme), [LabelImg](https://github.com/tzutalin/labelImg), [roLabelImg](https://github.com/cgvict/roLabelImg), [PPOCRLabel](https://github.com/PFCCLab/PPOCRLabel) and [CVAT](https://github.com/opencv/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 = {X-AnyLabeling: A Unified Desktop Platform for AI-Assisted Data Annotation},
  howpublished = {\url{https://github.com/CVHub520/X-AnyLabeling}}
}
```

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