This repository contains the File Manager and Advanced File Manager projects with a focus on clean design, modern functionality, and user-friendliness.
A lightweight script with a simple GUI to help users organize files by type.
Key Features:
- Organizes files into categories like Images, Documents, Videos, Music, and Archives.
- Moves unrecognized files to an "Others" folder.
- Tkinter-based GUI.
Usage:
Run the file_manager.py
script to start the application and select a folder to organize.
An enhanced file manager with a modern design and additional features for intelligent file management.
Key Features:
- Organize Files by Type: Automatically categorizes files into folders based on their extensions.
- Cluster Files: Groups text files into clusters based on their content using KMeans clustering.
- Predict Categories: Analyzes text files and predicts their categories using a machine learning model.
- Extract Text from Images (OCR): Extracts text from image files using Tesseract OCR.
- Unpack Subfolders: Copies all files from the selected folder and its subfolders into a single "Unpacked" folder.
- Modern Design: A sleek, Apple-inspired GUI with clean aesthetics and enhanced UX.
- Detailed Logs: Tracks actions with color-coded log messages for errors, successes, and actions.
Usage:
Run the final_advanced_file_manager_modern_design.py
script to start the application. Use the modern GUI to:
- Organize files, cluster them, predict categories, or extract text using OCR.
- Unpack subfolders into a unified folder while preserving the original files.
Install the required libraries using:
pip install pandas scikit-learn pillow pytesseract
Install Tesseract OCR for text extraction from images:
- Windows: Download the installer from Tesseract OCR GitHub.
- Linux: Install via:
sudo apt-get install tesseract-ocr
- macOS: Install via Homebrew:
brew install tesseract
After installation, verify by running:
tesseract --version
Here are the highlights of the modern design:
-
Clean and Modern Layout
Buttons are styled with rounded edges and hover effects for an Apple-inspired look. -
Detailed Logs with Colors
Logs are color-coded for better visibility:- Blue: Informational messages.
- Green: Success messages.
- Red: Errors.
We welcome contributions to enhance the features or improve the design. Submit a pull request with your changes.
This project is licensed under the MIT License.
Disclaimer: Always back up your files before using these tools to prevent accidental data loss.