Auto-LabelingText/Visual Prompting and Prompt-free for Detection & SegmentationDetect AnythingSegment AnythingChatbotVQA
## 🥳 What's New
- Add Re-recognition feature for PP-OCR models [[example](./examples/optical_character_recognition/text_recognition/README.md)]
- Add support for [PP-OCRv5](https://github.com/PaddlePaddle/PaddleOCR/tree/main/docs/version3.x/algorithm/PP-OCRv5) model
- Add copy coordinates to clipboard feature
- Add Navigator feature for high-resolution image navigation and zoom control
- Bump version to [3.2.2](https://github.com/CVHub520/X-AnyLabeling/releases/tag/v3.2.2)
- 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](./examples/training/ultralytics/README.md)]
- For more details, please refer to the [CHANGELOG](./CHANGELOG.md)
## 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-OCRv4, PP-OCRv5 |
| 🗣️ VLM | Florence2 |
| 🛣️ Land Detection | CLRNet |
| 📍 Grounding | CountGD, GeCO, Grunding DINO, YOLO-World, YOLOE |
| 📚 Other | 👉 [model_zoo](./docs/en/model_zoo.md) 👈 |
## Docs
1. [Installation & Quickstart](./docs/en/get_started.md)
2. [Usage](./docs/en/user_guide.md)
3. [Customize a model](./docs/en/custom_model.md)
4. [Chatbot](./docs/en/chatbot.md)
5. [VQA](./docs/en/vqa.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/)
- [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/README.md)
- [Matting](./examples/matting/)
- [Image Matting](./examples/matting/image_matting/README.md)
- [Vision-Language](./examples/vision_language/)
- [Florence 2](./examples/vision_language/florence2/README.md)
- [Counting](./examples/counting/)
- [GeCo](./examples/counting/geco/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 [GPL-3.0 license](./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](https://forms.gle/MZCKhU7UJ4TRSWxR7). If you intend to use this project for commercial purposes or within a company, please contact cv_hub@163.com to obtain a commercial license.
## 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/labelIm), [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 = {Advanced Auto Labeling Solution with Added Features},
howpublished = {\url{https://github.com/CVHub520/X-AnyLabeling}}
}
```
---
