Awesome
<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> </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 v2</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%" /> |
๐ฅณ What's New
- Nov. 2024:
- ๐๐๐ Added support for YOLOv5-SAHI.
- Oct. 2024:
- โจโจโจ Added support for DocLayout-YOLO model.
- Sep. 2024:
- Release version 2.4.4
- ๐๐๐ Added support for YOLO11-Det/OBB/Pose/Seg/Track model.
- ๐งธ๐งธ๐งธ Added support for image matting based on RMBG v1.4 model.
- ๐ฅ๐ฅ๐ฅ Added support for interactive video object tracking based on Segment-Anything-2. [Tutorial]
- Aug. 2024:
- Release version 2.4.1
- Support tracking-by-det/obb/seg/pose tasks.
- Support Segment-Anything-2 model! (Recommended)
- Support Grounding-SAM2 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 model.
- Support Depth Anything v2 model.
- Jun. 2024:
- Support YOLOv8-Pose model.
- Add yolo-pose import/export functionality.
- May. 2024:
- Support YOLOv8-World, YOLOv8-oiv7, YOLOv10 model.
- Release version 2.3.6.
- Add feature to display confidence score.
- Mar. 2024:
- Release version 2.3.5.
- Feb. 2024:
- Release version 2.3.4.
- Enable label display feature.
- Release version 2.3.3.
- Release version 2.3.2.
- Support 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.
- Support for quick tag correction is available; please refer to this document for guidance.
- Release version 2.3.1.
- Jan. 2024:
- Combining CLIP and SAM models for enhanced semantic and spatial understanding. An example can be found here.
- Add support for the Depth Anything model in the depth estimation task.
- Release version 2.3.0.
- Support YOLOv8-OBB model.
- Support RTMDet and RTMO model.
- Release a chinese license plate detection and recognition model based on YOLOv5.
- Dec. 2023:
- Nov. 2023:
- Release version 2.1.0.
- Support InternImage model (CVPR'23).
- Release version 2.0.0.
- Added support for Grounding-SAM, combining GroundingDINO with HQ-SAM to achieve sota zero-shot high-quality predictions!
- Enhanced support for HQ-SAM model to achieve high-quality mask predictions.
- Support the PersonAttribute and VehicleAttribute model for multi-label classification task.
- Introducing a new multi-label attribute annotation functionality.
- Release version 1.1.0.
- Support pose estimation: YOLOv8-Pose.
- 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.
- Add a new feature for rotation box.
- Support YOLOv5-OBB with DroneVehicle and DOTA-v1.0/v1.5/v2.0 model.
- SOTA Zero-Shot Object Detection - GroundingDINO is released.
- SOTA Image Tagging Model - Recognize Anything is released.
- Support YOLOv5-SAM and YOLOv8-EfficientViT_SAM union task.
- Support YOLOv5 and YOLOv8 segmentation task.
- Release Gold-YOLO and DAMO-YOLO models.
- Release MOT algorithms: OC_Sort (CVPR'23).
- Add a new feature for small object detection using SAHI.
- Sep. 2023:
- Aug. 2023:
- Jul. 2023:
- Add label_converter.py script.
- Release RT-DETR model.
- Jun. 2023:
- Release YOLO-NAS model.
- Support instance segmentation: YOLOv8-seg.
- Add README_zh-CN.md of X-AnyLabeling.
- May. 2023:
X-AnyLabeling
X-AnyLabeling is a powerful annotation tool that integrates an AI engine for fast and automatic labeling. Itโs 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
andvideos
. - 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 fortext detection
,recognition
, andKIE
.
Model library
<div align="center">Object Detection | SOD with 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 ๐ model_zoo ๐
</div>Docs
Examples
Contact
If you find this project helpful, please give it a โญstarโญ, and for any questions or issues, feel free to create an issue or email cv_hub@163.com.
License
This project is released under the GPL-3.0 license.
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}}
}
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