https://github.com/babyhamsta/yoable
An easy to use C# open source image labeler for YOLO with AI auto label abilities via YOLO/Onnx models.
https://github.com/babyhamsta/yoable
ai annotation annotation-tool annotations assisted csharp label labeling labeling-tool object-detection onnx onnxruntime tool wpf yolo
Last synced: 4 months ago
JSON representation
An easy to use C# open source image labeler for YOLO with AI auto label abilities via YOLO/Onnx models.
- Host: GitHub
- URL: https://github.com/babyhamsta/yoable
- Owner: Babyhamsta
- Created: 2025-01-29T20:57:06.000Z (8 months ago)
- Default Branch: master
- Last Pushed: 2025-02-17T15:42:18.000Z (8 months ago)
- Last Synced: 2025-06-14T15:58:42.894Z (4 months ago)
- Topics: ai, annotation, annotation-tool, annotations, assisted, csharp, label, labeling, labeling-tool, object-detection, onnx, onnxruntime, tool, wpf, yolo
- Language: C#
- Homepage:
- Size: 207 KB
- Stars: 18
- Watchers: 1
- Forks: 3
- Open Issues: 4
Awesome Lists containing this project
README
# Yoable
**Yoable** is an AI-powered image annotation tool designed to make dataset labeling faster and more efficient. It supports **YOLO v5/v8 (ONNX)** models for automatic object detection and labeling. Yoable provides an intuitive interface for managing images, running AI-assisted labeling, and exporting labels in a format compatible with machine learning models.
For non-WPF version you can build the legacy source or use v1.2.0 from releases - [Legacy branch](https://github.com/Babyhamsta/Yoable/tree/legacy).
## 🚀 Features
- **AI-Powered Auto Labeling** - Automatically detects objects using **YOLO v5/v8 (ONNX)** models.
- **Manual Labeling Tools** - Easily add, edit, and remove bounding boxes.
- **Bulk Image Import** - Load multiple images at once.
- **YOLO Label Format Support** - Import and export annotations in **YOLO format**.
- **Optional Cloud Upload** - Choose to upload labeled datasets during export to contribute to better models.
- **Customizable UI** - Light/Dark theme and customizable label appearance.
- **Crosshair Overlay** - Align annotations with precision.
- **Adjustable AI Confidence** - Set detection confidence thresholds for better accuracy.
- **Auto Updates** - Get the latest features and fixes with built-in update checks. (Can be disabled via settings, updates will show change log on next launch.)
## 📥 Installation
1. Download the latest release from our [GitHub Releases](https://github.com/Babyhamsta/Yoable/releases).
2. Download and run Yoable (No install required!).
3. (Optional) Load a **YOLO v5/v8 (ONNX)** model for AI-assisted labeling.
## 🛠️ How to Use
### Importing Images
- Click **"Import Image"** or **"Import Directory"** to load images.
- The images will appear in the **image list**.
### Applying Labels
- **Manual Labeling**: Use the drawing tools to create bounding boxes.
- **AI Auto-Labeling**: Click **"Auto Label Images"** to apply AI detections.
### Managing Labels
- Labels appear in the **label list**.
- Click on a label to edit it.
- Press **Delete** to remove selected labels.
- Use arrow keys for precise label movement.
### Importing & Exporting Labels
- **Import Labels**: Load existing YOLO-format label files.
- **Export Labels**: Save labeled data in YOLO format.
- **Cloud Upload (Optional)**: When exporting, users are asked if they want to upload their dataset. This can be disabled in settings.
### Updating Yoable
- Yoable automatically checks for updates.
- If a new version is available, you'll be prompted to update.
## 🌍 Contributing
Yoable is **open-source**! Contribute by reporting issues, suggesting features, or improving the code.
## 📌 Support
For help and troubleshooting, visit our [GitHub Issues](https://github.com/Babyhamsta/Yoable/issues) or join our community.
---
⭐ **Star this repo** if you find it useful!