annotex 2.0.8

Annotation Tool for Computer Vision Datasets

Annotex 🚀

AI-Powered Annotation Tool for Computer Vision Datasets

Annotex is a professional-grade annotation tool designed for creating high-quality computer vision datasets. With AI-powered assistance and an intuitive interface, it streamlines the annotation process for machine learning practitioners.

✨ Features

🎯 Professional Annotation Tools

• Rectangle Annotation - Precise bounding box creation
• AI-Assisted Annotation - Auto-annotation with pre-trained YOLO models
• Batch Processing - Process multiple images simultaneously

🔧 Advanced Workflow

• Project Management - Save/load projects (.anno format)
• Class Management - Dynamic class creation with custom colors
• Export Formats - YOLO11, YOLOv8, compatible
• Quality Control - Confidence scoring and validation

🚀 Performance Optimized

• Memory Efficient - Handles large datasets smoothly
• Real-time Preview - Instant annotation feedback
• Keyboard Shortcuts - Professional workflow acceleration

📦 Installation

Quick Install

pip install annotex

🚀 Quick Start

Launch Annotex

# Start the GUI
annotex

# Or
python -m annotex.main

# Load a project
annotex --project my_project.anno

# Load images from directory
annotex --images /path/to/images

Basic Workflow

1. Load Images - Import your image dataset
2. Create Classes - Define annotation classes
3. Annotate - Create bounding boxes manually or with AI
4. Export - Generate YOLO-format dataset

📚 Documentation

Keyboard Shortcuts

Category	Shortcut	Action
Navigation	Left Arrow	Previous image
	Right Arrow	Next image
	Home	First image
	End	Last image
	Ctrl + +	Zoom in
	Ctrl + -	Zoom out
	Ctrl + 0	Zoom fit
	Ctrl + R	Reset view
File Operations	Ctrl + N	New project
	Ctrl + O	Open project
	Ctrl + S	Save current
	Ctrl + Shift + S	Save project
	Ctrl + I	Load images
	Ctrl + E	Export dataset
Editing	Ctrl + Z	Undo
	Ctrl + C	Copy annotation
	Ctrl + V	Paste annotation
	Delete	Delete selected
	Ctrl + Shift + C	Clear all
	R	Rectangle tool
Tools & Classes	1-9	Select class by number
	F1	Show shortcuts
	Middle Click + Drag	Pan image
	Mouse Wheel	Zoom in/out
	Right Click	Context menu

🎨 Interface Overview

Main Components

• Tools Panel - Annotation tools and class management
• Image Viewer - Zoomable canvas with annotation overlay
• Image List - Project image management
• Export Panel - Dataset export configuration

Advanced Features

• Semi-Automated Annotation - Pre-trained AI model integration
• Batch Processing - Multi-image operations
• Quality Metrics - Annotation statistics and validation
• Custom Export - Flexible dataset formats (Currently:only YOLO formats)

🤖 AI Integration

Supported Models

• YOLO11 - Proven performance
• Custom Models - Load your own trained models

Auto-Annotation Workflow

1. Load pre-trained model (.pt file)
2. Set confidence threshold
3. Run individual or batch annotation
4. Review and refine results
5. Export final dataset

Possible Usage: Pre-train your AI model on a small dataset and use that model to annotate the rest of the dataset.

🏗️ Roadmap

Version 2.2 (Coming Soon)

• Polygon annotation tool
• Point annotation support
• Brush/segmentation tool
• COCO format export
• Pascal VOC format support

Version 2.3 (Planned)

• Team collaboration features
• Advanced AI suggestions

📞 Support

• 📧 Email: [e-mail]

🌟 Acknowledgments

• Ultralytics for YOLO implementation
• OpenCV for computer vision tools
• Tkinter for GUI framework

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⭐ Star us on GitHub if Annotex helps your projects!

Made by Randika