X-AnyLabeling — AI-Powered Image Annotation Tool

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/