annotation.mp4
Visual Prompting for Detection
Visual Prompting for Segmentation
Chatbot
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.
- Processes both
imagesandvideos. - Accelerates inference with
GPUsupport. - 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,ocrand so on. - Supports diverse annotation styles:
polygons,rectangles,rotated boxes,circles,lines,points, and annotations fortext detection,recognition, andKIE.
| 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 |
| 📍 Grounding | CountGD, GeCO, Grunding DINO, YOLO-World |
| 💡 Proposal | UPN |
| 🏷️ Tagging | RAM, RAM++ |
| 📄 OCR | PP-OCR |
| 🗣️ VLM | Florence2, |
| 🛣️ Land Detection | CLRNet |
| 📚 Other | 👉 model_zoo 👈 |
- Classification
- Detection
- Segmentation
- Description
- Estimation
- OCR
- MOT
- iVOS
- Matting
- Vision-Language
- Counting
If you find this project helpful, please give it a ⭐star⭐, and for any questions or issues, feel free to create an issue or email cv_hub@163.com.
This project is released under the GPL-3.0 license.
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.
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}}
}
