Translator-AI

A Python-based AI translator application that extracts text from images and provides language detection and translation capabilities.

Project Structure

Translator-AI/
├── src/                    # Main source code
│   ├── main.py            # Application entry point
│   ├── MLrecognition.py   # Machine learning language recognition
│   ├── Translator.py      # Translation functionality
│   ├── ExtractTextFromImg.py  # Text extraction from images
│   ├── frontends.py       # Frontend UI implementation
│   └── d.py               # Additional UI components
├── utils/                 # Utility functions and text processing
│   ├── TextExtractedModificator.py  # Text modification pipeline
│   ├── Abreviation_Slang.py        # Abbreviation and slang processing
│   ├── Contractions.py             # Contraction expansion
│   ├── EmojiRemover.py             # Emoji removal
│   ├── LowerCaracter.py            # Text lowercasing
│   ├── NumberRemover.py            # Number removal
│   ├── NumberRemoverForText.py     # Text-specific number removal
│   ├── PunctuationRemover.py       # Punctuation removal
│   └── URLRemover.py               # URL removal
├── data/                  # Datasets and sample images
│   ├── dataset.csv
│   ├── language-identification-datasets.csv
│   ├── ImageWithText.jpg
│   ├── IMG.png
│   └── IMG_20221113_114712.png
├── assets/                # UI assets
│   └── frontend.kv        # Kivy UI layout file
├── models/                # Machine learning models (empty)
├── tests/                 # Unit and integration tests (empty)
├── docs/                  # Documentation (empty)
└── README.md             # This file

Features

• Image Text Extraction: Extract text from images using OCR (Optical Character Recognition)
• Language Detection: Automatically detect the language of extracted text using machine learning
• Translation: Translate text to different languages
• GUI Interface: User-friendly interface built with Kivy/KivyMD
• Text Processing: Comprehensive text cleaning and preprocessing utilities

Installation

Prerequisites

• Python 3.6+
• Tesseract OCR engine

Install Python Dependencies

pip install -r requirements.txt

Or install packages individually:

pip install opencv-python
pip install pytesseract
pip install pandas
pip install scikit-learn
pip install googletrans==3.1.0a0
pip install kivy
pip install kivymd
pip install pillow

Tesseract Installation

Windows

Download and install Tesseract from: https://github.com/UB-Mannheim/tesseract/wiki

Linux (Ubuntu/Debian)

sudo apt-get install tesseract-ocr

macOS

brew install tesseract

Usage

Command Line

Run the main application:

cd src/
python main.py

GUI Application

Run the GUI frontend:

cd src/
python frontends.py

How It Works

1. Text Extraction: The application uses OpenCV and Tesseract to extract text from images
2. Text Processing: Raw extracted text is cleaned using various utility functions:
   • Convert to lowercase
   • Remove URLs, numbers, punctuation
   • Remove emojis
   • Expand contractions
   • Process abbreviations and slang
3. Language Detection: Uses machine learning (Decision Tree Classifier) to identify the language
4. Translation: Uses Google Translate API to translate text to the target language

Configuration

• Update the Tesseract executable path in src/ExtractTextFromImg.py if needed
• Modify language datasets in the data/ directory
• Customize UI layouts in assets/frontend.kv

Contributing

1. Fork the repository
2. Create a feature branch
3. Add your changes
4. Add tests in the tests/ directory
5. Submit a pull request

License

This project is open source. Please check the repository for license details.

Known Issues

• textscanner.py module is referenced but not present in the codebase
• Hardcoded Tesseract path may need adjustment for different systems
• Some imports may need adjustment based on your Python environment

Future Enhancements

• Add comprehensive unit tests
• Implement the missing textscanner module
• Add support for more image formats
• Improve language detection accuracy
• Add more translation services
• Containerize the application