x-anylabeling-cvhub 3.3.0b0

Advanced Auto Labeling Solution with Added Features

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Auto-Labeling

Text/Visual Prompting and Prompt-free for Detection & Segmentation

Detect Anything

Segment Anything

Chatbot

VQA

Image Classifier

🥳 What's New

• Add multi-label classification mode to Image Classifier
• Bump version to 3.2.6
• Add support for using backspace key to delete the last vertex when creating polygon and line shapes (#1151)
• Add DEIMv2: A real-time object detector powered by DINOv3 features
• Add the ability to process all images at once with the Florence-2 model (#1152)
• Add max_det parameter for maximum detections in YOLO model (#1142)
• Bump version to 3.2.5
• Add --qt-platform argument for improved performance on Fedora KDE environments (#1145)
• Add auto_use_last_gid feature with Ctrl+Shift+G shortcut (1143)
• Implement async EXIF detection to eliminate loading delays
• Bump version to 3.2.4
• Add support for deleting group IDs from objects (#1141)
• Add support for Ultralytics image classification task training [Toturial]
• Add loop select labels functionality for sequential shape selection (#1138)
• Add checkboxes for description and labels visibility control in the labeling widget (#1139)
• Add support for radiobutton widgets in shape attributes for faster single-click selection [Toturial]
• Add automatic attributes panel display when finishing shape drawing
• Fix linestrip vertex drawing issues (#1134)
• Add support for drawing rectangle shapes outside canvas with auto-clipping (#1137)
• Add dedicated multi-class image classifier with streamlined workflow [Docs]
• Add select/deselect all shapes feature
• Add custom provider support and enhance model dropdown feature for Chatbot
• Add option to preserve existing annotations when uploading YOLO labels
• Add cross-component and annotation data reference tokens for VQA AI prompts
• Bump version to 3.2.3
• Add mask fineness control slider for SAM series models to adjust segmentation precision
• Add Re-recognition feature for PP-OCR models [Example]
• Add support for 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
• 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]
• For more details, please refer to the CHANGELOG

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, DEIMv2
🖌️ 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
🗣️ Vision Foundation Models	Florence2
👁️ Vision Language Models	Qwen-VL, Gemini, ChatGPT
🛣️ Land Detection	CLRNet
📍 Grounding	CountGD, GeCO, Grunding DINO, YOLO-World, YOLOE
📚 Other	👉 model_zoo 👈

Docs

1. Installation & Quickstart
2. Usage
3. Customize a model
4. Chatbot
5. VQA
6. Multi-class Image Classifier

Examples

• Classification
  • Image-Level
  • Shape-Level
• Detection
  • HBB Object Detection
  • OBB Object Detection
• Segmentation
  • Instance Segmentation
  • Binary Semantic Segmentation
  • Multiclass Semantic Segmentation
• Description
  • Tagging
  • Captioning
• Estimation
  • Pose Estimation
  • Depth Estimation
• OCR
  • Text Recognition
  • Key Information Extraction
• MOT
  • Tracking by HBB Object Detection
  • Tracking by OBB Object Detection
  • Tracking by Instance Segmentation
  • Tracking by Pose Estimation
• iVOS
• Matting
  • Image Matting
• Vision-Language
  • Florence 2
• Counting
  • GeCo
• Training
  • Ultralytics

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 and make sure to agree to the Contributor License Agreement (CLA) before submitting a pull request.

If you find this project helpful, please consider giving it a ⭐️ star! Have questions or suggestions? Open an issue or email us at [e-mail].

A huge thank you 🙏 to everyone helping to make X‑AnyLabeling better.

License

This project is licensed under the GPL-3.0 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. If you intend to use this project for commercial purposes or within a company, please contact [e-mail] to obtain a commercial 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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