# X-AnyLabeling — AI-Powered Image Annotation Tool

> A desktop annotation tool with built-in AI models for auto-labeling images and videos across detection, segmentation, and classification tasks.

## Install

Save in your project root:

# X-AnyLabeling — AI-Powered Image Annotation Tool

## Quick Use
```bash
pip install x-anylabeling
x-anylabeling
# Or run from source:
git clone https://github.com/CVHub520/X-AnyLabeling.git
cd X-AnyLabeling && pip install -r requirements.txt
python anylabeling/app.py
```

## Introduction
X-AnyLabeling is an open-source image and video annotation tool that integrates AI models for semi-automatic labeling. It combines manual annotation workflows with one-click AI-assisted labeling using models like SAM, YOLO, and GroundingDINO.

## What X-AnyLabeling Does
- Provides manual annotation for bounding boxes, polygons, and keypoints
- Integrates Segment Anything (SAM) for one-click instance segmentation
- Supports YOLO-based auto-detection for rapid bounding box creation
- Handles video annotation with frame-by-frame tracking
- Exports labels in COCO, YOLO, VOC, and other standard formats

## Architecture Overview
X-AnyLabeling is a PyQt-based desktop application that loads ONNX-format AI models on demand. When a user triggers auto-labeling, the selected model runs inference on the current frame, and detected objects are converted into editable annotations. The modular model loader supports swapping in custom ONNX models without code changes.

## Self-Hosting & Configuration
- Install via pip or run from source with Python 3.8+
- Works on Windows, macOS, and Linux
- GPU acceleration via ONNX Runtime with CUDA provider
- Download AI model weights from the built-in model zoo
- Customize keyboard shortcuts and label presets in the settings

## Key Features
- 20+ built-in AI models for detection, segmentation, and OCR
- Cross-platform desktop application with familiar labeling UX
- One-click SAM-based segmentation for pixel-accurate masks
- Multi-format export compatible with major training frameworks
- Active development with frequent model and feature updates

## Comparison with Similar Tools
- **LabelImg** — manual-only bounding box tool; X-AnyLabeling adds AI assistance
- **CVAT** — web-based team tool; X-AnyLabeling is a lightweight desktop alternative
- **Label Studio** — broader data types; X-AnyLabeling is more focused on vision tasks
- **Roboflow** — cloud platform; X-AnyLabeling runs fully offline and is free

## FAQ
**Q: Can I add my own custom models?**
A: Yes, export your model to ONNX format and register it in the model config.

**Q: Does it support video annotation?**
A: Yes, including frame navigation, object tracking, and interpolation.

**Q: Is GPU required?**
A: No, CPU inference works but GPU accelerates AI-assisted labeling significantly.

**Q: What annotation types does it support?**
A: Bounding boxes, polygons, polylines, points, rotated boxes, and text.

## Sources
- https://github.com/CVHub520/X-AnyLabeling
- https://x-anylabeling.com/

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Source: https://tokrepo.com/en/workflows/asset-da207b8c
Author: AI Open Source