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Overview

Omniscient Autotagger is a powerful, intelligent tool designed to automatically tag your files with precision. This project combines cutting-edge algorithms with a user-friendly interface to streamline the tagging process for various file types.
This repository is an ongoing project.
Current implementation works on Linux and Windows.

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Quick Navigation

Overview Features Installation Usage Configuration TO DO Contributing License

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Features

• Automatic Tagging: Intelligent algorithms that tag files quickly and accurately.
• Cross-Platform Compatibility: Currently implemented for Linux and Windows.
• Customizable Workflow: Easily integrate with your existing file management systems.
• Optimized Performance: Uses proper multithreading for smooth and responsive operation.
• User-Friendly Interface: Built with PyQt6, featuring a sleek dark grey aesthetic.
• Persistent Settings: Saves configuration data in an OS-specific folder (AppData on Windows or the equivalent on Linux) to reload your preferences upon launch.

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Installation

Clone the repository and install the required packages:

git clone https://github.com/BrechtCorbeel/Omniscient-Autotagger.git
cd Omniscient-Autotagger
pip install -r requirements.txt

Note: For full GUI functionality, ensure that PyQt6 is installed.

Usage

Run the main application using:

bash Copy python main.py The application will automatically create a folder in your OS's application data directory (e.g., AppData on Windows or the corresponding location on Linux) to store and reload GUI settings and user preferences.

Configuration

Customize the autotagging parameters by editing the configuration file located in the application data folder. This file allows you to adjust settings to better match your workflow and performance requirements.

TO DO

Expand and enhance settings. Drag-and-drop window frame image file. Support basic Windows frame scaling. Add tracking features. Proper threading and implementation for tracking progress. Cloud features. Large + lite version. Paid features. Image tags. Basic drawing and editing features. Video tagging. ...

Contributing

Contributions are welcome! Follow these steps to contribute:

Fork the repository. Create a new branch: git checkout -b feature/YourFeature Commit your changes: git commit -m 'Add some feature' Push to the branch: git push origin feature/YourFeature Open a pull request. For any major changes, please open an issue first to discuss what you would like to modify.

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