base on Effortless data labeling with AI support from Segment Anything and other awesome models. <div align="center"> <p> <a href="https://github.com/CVHub520/X-AnyLabeling/" target="_blank"> <img alt="X-AnyLabeling" height="200px" src="https://github.com/user-attachments/assets/0714a182-92bd-4b47-b48d-1c5d7c225176"></a> </p> [English](README.md) | [简体中文](README_zh-CN.md) </div> <p align="center"> <a href="./LICENSE"><img src="https://img.shields.io/badge/License-LGPL%20v3-blue.svg"></a> <a href=""><img src="https://img.shields.io/github/v/release/CVHub520/X-AnyLabeling?color=ffa"></a> <a href=""><img src="https://img.shields.io/badge/python-3.10+-aff.svg"></a> <a href=""><img src="https://img.shields.io/badge/os-linux%2C%20win%2C%20mac-pink.svg"></a> <a href=""><img src="https://img.shields.io/github/downloads/CVHub520/X-AnyLabeling/total?label=downloads"></a> <a href="https://modelscope.cn/collections/X-AnyLabeling-7b0e1798bcda43"><img src="https://img.shields.io/badge/modelscope-X--AnyLabeling-6750FF?link=https%3A%2F%2Fmodelscope.cn%2Fcollections%2FX-AnyLabeling-7b0e1798bcda43"></a> </p>  https://github.com/user-attachments/assets/f517fa94-c49c-4f05-864e-96b34f592079 https://github.com/user-attachments/assets/52cbdb5d-cc60-4be5-826f-903ea4330ca8 <div align="center"><strong>Text/Visual Prompting and Prompt-free for Detection & Segmentation</strong></div> <br> <img src="https://github.com/user-attachments/assets/7f43bcec-96fd-48d1-bd36-9e5a440a66f6" width="100%" /> <div align="center"><strong>Detect Anything</strong></div> <br> <img src="https://github.com/user-attachments/assets/208dc9ed-b8c9-4127-9e5b-e76f53892f03" width="100%" /> <div align="center"><strong>Segment Anything</strong></div> <br> <img src="https://github.com/user-attachments/assets/56c9a20b-c836-47aa-8b54-bad5bb99b735" width="100%" /> <div align="center"><strong>Chatbot</strong></div> ## 🥳 What's New - Add rectangle scaling and edge adjustment with mouse wheel support - Add GUI support for uploading custom label classes - Add real-time preview dialog for image matting and depth estimation results - Support `RMBG v2.0` model for image matting - Bump version to [3.0.3](https://github.com/CVHub520/X-AnyLabeling/releases/tag/v3.0.3) - 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 <img src="https://github.com/user-attachments/assets/c65db18f-167b-49e8-bea3-fcf4b43a8ffd" width="100%" /> - 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, 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/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) ## 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) ## 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 [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](./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 [email protected] 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}} } ``` <div align="right"><a href="#top">🔝 Back to Top</a></div>", Assign "at most 3 tags" to the expected json: {"id":"5057","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"