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-3.8+-aff.svg"></a> <a href=""><img src="https://img.shields.io/badge/os-linux%2C%20win%2C%20mac-pink.svg"></a> <a href="https://github.com/CVHub520/X-AnyLabeling/stargazers"><img src="https://img.shields.io/github/stars/CVHub520/X-AnyLabeling?color=ccf"></a> </p>  <img src="https://github.com/user-attachments/assets/0b1e3c69-a800-4497-9bad-4332c1ce1ebf" width="100%" /> <div align="center"><strong>Segment Anything 2.1</strong></div> <br> [](https://www.youtube.com/watch?v=QtoVMiTwXqk) <div align="center"><strong>Interactive Visual-Text Prompting for Generic Vision Tasks</strong></div> </br> | **Tracking by HBB Detection** | **Tracking by OBB Detection** | | :---: | :---: | | <img src="https://github.com/user-attachments/assets/be67d4f8-eb31-4bb3-887c-d954bb4a5d6d" width="100%" /> | <img src="https://github.com/user-attachments/assets/d85b1102-124a-4971-9332-c51fd2b1c47b" width="100%" /> | | **Tracking by Instance Segmentation** | **Tracking by Pose Estimation** | | <img src="https://github.com/user-attachments/assets/8d412dc6-62c7-4bb2-9a1e-026448acf2bf" width="100%" /> | <img src="https://github.com/user-attachments/assets/bab038a7-3023-4097-bdcc-90e5009477c0" width="100%" /> | ## 🥳 What's New - Dec. 2024: - 🍊🍊🍊 Added support for [Hyper-YOLO](https://github.com/iMoonLab/Hyper-YOLO) model. - 🎉🎉🎉 Release version [2.5.0](https://github.com/CVHub520/X-AnyLabeling/releases/tag/v2.5.0). - 🤡🤡🤡 Added support for [Open Vision](./examples/detection/hbb/README.md) model. [[Youtube](https://www.youtube.com/watch?v=QtoVMiTwXqk) | [Bilibili](https://www.bilibili.com/video/BV1jyqrYyE74)] - 👻👻👻 Added support for [Segment Anything 2.1](./docs/en/model_zoo.md) model. - 🤗🤗🤗 Added support for [Florence-2](./examples/vision_language/florence2/README.md), a unified vision foundation model for multi-modal tasks. - Nov. 2024: - ✨✨✨ Added support for the [UPN](./examples/detection/hbb/README.md) model to generate proposal boxes. - 🌟🌟🌟 Added support for [YOLOv5-SAHI](./anylabeling/configs/auto_labeling/yolov5s_sahi.yaml). - Oct. 2024: - 🎯🎯🎯 Added support for [DocLayout-YOLO](examples/optical_character_recognition/document_layout_analysis/README.md) model. - Sep. 2024: - Release version [2.4.4](https://github.com/CVHub520/X-AnyLabeling/releases/tag/v2.4.4) - 🐻‍❄️🐻‍❄️🐻‍❄️ Added support for [YOLO11-Det/OBB/Pose/Seg/Track model](https://github.com/ultralytics/ultralytics). - 🧸🧸🧸 Added support for image matting based on [RMBG v1.4 model](https://huggingface.co/briaai/RMBG-1.4). - 🦄🦄🦄 Added support for interactive video object tracking based on [Segment-Anything-2](https://github.com/CVHub520/segment-anything-2). [[Tutorial](examples/interactive_video_object_segmentation/README.md)] <br> <details> <summary>Click to view more news.</summary> - Aug. 2024: - Release version [2.4.1](https://github.com/CVHub520/X-AnyLabeling/releases/tag/v2.4.1) - Support [tracking-by-det/obb/seg/pose](./examples/multiple_object_tracking/README.md) tasks. - Support [Segment-Anything-2](https://github.com/facebookresearch/segment-anything-2) model! - Support [Grounding-SAM2](./docs/en/model_zoo.md) model. - Support lightweight model for Japanese recognition. - Jul. 2024: - Add PPOCR-Recognition and KIE import/export functionality for training PP-OCR task. - Add ODVG import/export functionality for training grounding task. - Add support to annotate KIE linking field. - Support [RT-DETRv2](https://github.com/lyuwenyu/RT-DETR) model. - Support [Depth Anything v2](https://github.com/DepthAnything/Depth-Anything-V2) model. - Jun. 2024: - Support [YOLOv8-Pose](https://docs.ultralytics.com/tasks/pose/) model. - Add [yolo-pose](./docs/en/user_guide.md) import/export functionality. - May. 2024: - Support [YOLOv8-World](https://docs.ultralytics.com/models/yolo-world), [YOLOv8-oiv7](https://docs.ultralytics.com/models/yolov8), [YOLOv10](https://github.com/THU-MIG/yolov10) model. - Release version [2.3.6](https://github.com/CVHub520/X-AnyLabeling/releases/tag/v2.3.6). - Add feature to display confidence score. - Mar. 2024: - Release version [2.3.5](https://github.com/CVHub520/X-AnyLabeling/releases/tag/v2.3.5). - Feb. 2024: - Release version [2.3.4](https://github.com/CVHub520/X-AnyLabeling/releases/tag/v2.3.4). - Enable label display feature. - Release version [2.3.3](https://github.com/CVHub520/X-AnyLabeling/releases/tag/v2.3.3). - Release version [2.3.2](https://github.com/CVHub520/X-AnyLabeling/releases/tag/v2.3.2). - Support [YOLOv9](https://github.com/WongKinYiu/yolov9) model. - Support the conversion from a horizontal bounding box to a rotated bounding box. - Supports label deletion and renaming. For more details, please refer to the [document](./docs/zh_cn/user_guide.md). - Support for quick tag correction is available; please refer to this [document](./docs/en/user_guide.md) for guidance. - Release version [2.3.1](https://github.com/CVHub520/X-AnyLabeling/releases/tag/v2.3.1). - Jan. 2024: - Combining CLIP and SAM models for enhanced semantic and spatial understanding. An example can be found [here](./anylabeling/configs/auto_labeling/edge_sam_with_chinese_clip.yaml). - Add support for the [Depth Anything](https://github.com/LiheYoung/Depth-Anything.git) model in the depth estimation task. - Release version [2.3.0](https://github.com/CVHub520/X-AnyLabeling/releases/tag/v2.3.0). - Support [YOLOv8-OBB](https://github.com/ultralytics/ultralytics) model. - Support [RTMDet](https://github.com/open-mmlab/mmyolo/tree/main/configs/rtmdet) and [RTMO](https://github.com/open-mmlab/mmpose/tree/main/projects/rtmpose) model. - Release a [chinese license plate](https://github.com/we0091234/Chinese_license_plate_detection_recognition) detection and recognition model based on YOLOv5. - Dec. 2023: - Release version [2.2.0](https://github.com/CVHub520/X-AnyLabeling/releases/tag/v2.2.0). - Support [EdgeSAM](https://github.com/chongzhou96/EdgeSAM) to optimize for efficient execution on edge devices with minimal performance compromise. - Support YOLOv5-Cls and YOLOv8-Cls model. - Nov. 2023: - Release version [2.1.0](https://github.com/CVHub520/X-AnyLabeling/releases/tag/v2.1.0). - Support [InternImage](https://arxiv.org/abs/2211.05778) model (**CVPR'23**). - Release version [2.0.0](https://github.com/CVHub520/X-AnyLabeling/releases/tag/v2.0.0). - Added support for Grounding-SAM, combining [GroundingDINO](https://github.com/wenyi5608/GroundingDINO) with [HQ-SAM](https://github.com/SysCV/sam-hq) to achieve sota zero-shot high-quality predictions! - Enhanced support for [HQ-SAM](https://github.com/SysCV/sam-hq) model to achieve high-quality mask predictions. - Support the [PersonAttribute](https://github.com/PaddlePaddle/PaddleClas/blob/release%2F2.5/docs/en/PULC/PULC_person_attribute_en.md) and [VehicleAttribute](https://github.com/PaddlePaddle/PaddleClas/blob/release%2F2.5/docs/en/PULC/PULC_vehicle_attribute_en.md) model for multi-label classification task. - Introducing a new multi-label attribute annotation functionality. - Release version [1.1.0](https://github.com/CVHub520/X-AnyLabeling/releases/tag/v1.1.0). - Support pose estimation: [YOLOv8-Pose](https://github.com/ultralytics/ultralytics). - Support object-level tag with yolov5_ram. - Add a new feature enabling batch labeling for arbitrary unknown categories based on Grounding-DINO. - Oct. 2023: - Release version [1.0.0](https://github.com/CVHub520/X-AnyLabeling/releases/tag/v1.0.0). - Add a new feature for rotation box. - Support [YOLOv5-OBB](https://github.com/hukaixuan19970627/yolov5_obb) with [DroneVehicle](https://github.com/VisDrone/DroneVehicle) and [DOTA](https://captain-whu.github.io/DOTA/index.html)-v1.0/v1.5/v2.0 model. - SOTA Zero-Shot Object Detection - [GroundingDINO](https://github.com/wenyi5608/GroundingDINO) is released. - SOTA Image Tagging Model - [Recognize Anything](https://github.com/xinyu1205/Tag2Text) is released. - Support YOLOv5-SAM and YOLOv8-EfficientViT_SAM union task. - Support YOLOv5 and YOLOv8 segmentation task. - Release [Gold-YOLO](https://github.com/huawei-noah/Efficient-Computing/tree/master/Detection/Gold-YOLO) and [DAMO-YOLO](https://github.com/tinyvision/DAMO-YOLO) models. - Release MOT algorithms: [OC_Sort](https://github.com/noahcao/OC_SORT) (**CVPR'23**). - Add a new feature for small object detection using [SAHI](https://github.com/obss/sahi). - Sep. 2023: - Release version [0.2.4](https://github.com/CVHub520/X-AnyLabeling/releases/tag/v0.2.4). - Release [EfficientViT-SAM](https://github.com/mit-han-lab/efficientvit) (**ICCV'23**),[SAM-Med2D](https://github.com/OpenGVLab/SAM-Med2D), [MedSAM](https://arxiv.org/abs/2304.12306) and YOLOv5-SAM. - Support [ByteTrack](https://github.com/ifzhang/ByteTrack) (**ECCV'22**) for MOT task. - Support [PP-OCRv4](https://github.com/PaddlePaddle/PaddleOCR) model. - Add `video` annotation feature. - Add `yolo`/`coco`/`voc`/`mot`/`dota` export functionality. - Add the ability to process all images at once. - Aug. 2023: - Release version [0.2.0]((https://github.com/CVHub520/X-AnyLabeling/releases/tag/v0.2.0)). - Release [LVMSAM](https://arxiv.org/abs/2306.11925) and it's variants [BUID](https://github.com/CVHub520/X-AnyLabeling/tree/main/assets/examples/buid), [ISIC](https://github.com/CVHub520/X-AnyLabeling/tree/main/assets/examples/isic), [Kvasir](https://github.com/CVHub520/X-AnyLabeling/tree/main/assets/examples/kvasir). - Support lane detection algorithm: [CLRNet](https://github.com/Turoad/CLRNet) (**CVPR'22**). - Support 2D human whole-body pose estimation: [DWPose](https://github.com/IDEA-Research/DWPose/tree/main) (**ICCV'23 Workshop**). - Jul. 2023: - Add [label_converter.py](./tools/label_converter.py) script. - Release [RT-DETR](https://github.com/PaddlePaddle/PaddleDetection/blob/develop/configs/rtdetr/README.md) model. - Jun. 2023: - Release [YOLO-NAS](https://github.com/Deci-AI/super-gradients/tree/master) model. - Support instance segmentation: [YOLOv8-seg](https://github.com/ultralytics/ultralytics). - Add [README_zh-CN.md](README_zh-CN.md) of X-AnyLabeling. - May. 2023: - Release version [0.1.0](https://github.com/CVHub520/X-AnyLabeling/releases/tag/v0.1.0). - Release [YOLOv6-Face](https://github.com/meituan/YOLOv6/tree/yolov6-face) for face detection and facial landmark detection. - Release [SAM](https://arxiv.org/abs/2304.02643) and it's faster version [MobileSAM](https://arxiv.org/abs/2306.14289). - Release [YOLOv5](https://github.com/ultralytics/yolov5), [YOLOv6](https://github.com/meituan/YOLOv6), [YOLOv7](https://github.com/WongKinYiu/yolov7), [YOLOv8](https://github.com/ultralytics/ultralytics), [YOLOX](https://github.com/Megvii-BaseDetection/YOLOX). </details> ## X-AnyLabeling **X-AnyLabeling** is a powerful annotation tool that integrates an AI engine for fast and automatic labeling. It’s designed for visual 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. - 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 <div align="center"> | **Object Detection** | **SOD with [SAHI](https://github.com/obss/sahi)** | **Facial Landmark Detection** | **Pose Estimation** | | :---: | :---: | :---: | :---: | | <img src='https://user-images.githubusercontent.com/72010077/273488633-fc31da5c-dfdd-434e-b5d0-874892807d95.png' height="126px" width="180px"> | <img src='https://user-images.githubusercontent.com/61035602/206095892-934be83a-f869-4a31-8e52-1074184149d1.jpg' height="126px" width="180px"> | <img src='https://user-images.githubusercontent.com/61035602/206095684-72f42233-c9c7-4bd8-9195-e34859bd08bf.jpg' height="126px" width="180px"> | <img src='https://user-images.githubusercontent.com/61035602/206100220-ab01d347-9ff9-4f17-9718-290ec14d4205.gif' height="126px" width="180px"> | | **Lane Detection** | **OCR** | **MOT** | **Instance Segmentation** | | <img src='https://user-images.githubusercontent.com/72010077/273764641-65f456ed-27ce-4077-8fce-b30db093b988.jpg' height="126px" width="180px"> | <img src='https://user-images.githubusercontent.com/72010077/273421210-30d20e08-3b72-4f4d-8976-05b564e13d87.png' height="126px" width="180px"> | <img src='https://user-images.githubusercontent.com/61035602/206111753-836e7827-968e-4c80-92ef-7a78766892fc.gif' height="126px" width="180px" > | <img src='https://user-images.githubusercontent.com/61035602/206095831-cc439557-1a23-4a99-b6b0-b6f2e97e8c57.jpg' height="126px" width="180px"> | | **Tagging** | **Grounding** | **Recognition** | **Rotation** | | <img src='https://user-images.githubusercontent.com/72010077/277670825-8797ac7e-e593-45ea-be6a-65c3af17b12b.png' height="126px" width="180px"> | <img src='https://user-images.githubusercontent.com/72010077/277395884-4d500af3-3e4e-4fb3-aace-9a56a09c0595.png' height="126px" width="180px"> | <img src='https://user-images.githubusercontent.com/72010077/277396071-79daec2c-6b0a-4d42-97cf-69fd098b3400.png' height="126px" width="180px"> | <img src='https://user-images.githubusercontent.com/72010077/277395955-aab54ea0-88f5-41af-ab0a-f4158a673f5e.png' height="126px" width="180px"> | | **Segment Anything** | **BC-SAM** | **Skin-SAM** | **Polyp-SAM** | | <img src='https://user-images.githubusercontent.com/72010077/273421331-2c0858b5-0b92-405b-aae6-d061bc25aa3c.png' height="126px" width="180px"> | <img src='https://user-images.githubusercontent.com/72010077/273764259-718dce97-d04d-4629-b6d2-95f17670ce2a.png' height="126px" width="180px"> | <img src='https://user-images.githubusercontent.com/72010077/273764288-e26767d1-3c44-45cb-a72e-124efb4e8263.png' height="126px" width="180px"> | <img src='https://user-images.githubusercontent.com/72010077/273764318-e8b6a197-e733-478e-a210-e4386bafa1e4.png' height="126px" width="180px"> | For more details, please refer to 👉 [model_zoo](./docs/en/model_zoo.md) 👈 </div> ## 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) ## 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) ## Contact If you find this project helpful, please give it a ⭐star⭐, and for any questions or issues, feel free to [create an issue](https://github.com/CVHub520/X-AnyLabeling/issues) or email [email protected]. ## License This project is released under the [GPL-3.0 license](./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"