Multi-Language-Text-Detection

Multi-Language Text Detection

Problem Statement: Enable piracy detection for non-English text by translating the text into English and matching it against piracy-related keywords.

Requirements:

Use Google Translate API or Hugging Face Transformers for translation.

Detect piracy keywords using NLTK or spaCy.

Deliverables:

Python script for text translation and keyword detection.

Documentation detailing multi-language support.

Instructions to Candidate

Documentation: Provide step-by-step documentation, including the tools, libraries, and resources used.

Open-Source Only: Use free libraries and APIs for implementation.

Focus Areas: Highlight Full Stack Development, AI integration, and Media & Entertainment relevance in solutions.

Multi-Language Text Detection System

Introduction

This repository contains the implementation of the Multi-Language Text Detection System. The system is designed to detect piracy-related keywords from non-English text inputs. It uses a combination of translation models and natural language processing techniques to achieve this. Key features of this project include:

Translating non-English text to English using Hugging Face Transformers. Identifying piracy-related keywords using spaCy. This project has applications in industries like media, entertainment, and cybersecurity for combating piracy effectively.

Requirements

• Python Version
• Python 3.7+
• Python Packages
• Flask
• transformers
• torch
• langdetect
• spacy

Additional Tools (optional)

Hugging Face translation models: To perform language translation.

Install these libraries using the following command:

pip install -r requirements.txt

Project Structure

.

• ├── app.py # Main Flask application
• ├── text_process.py # Text processing functions (translation and keyword detection)
• ├── templates/
• │ └── index.html # Webpage template
• ├── requirements.txt # Python dependencies

How to Use

Install dependencies:

pip install -r requirements.txt

Run the Flask application:

python app.py

Open your browser and navigate to:

http://127.0.0.1:5000/

Enter non-English text, click "Detect", and view the results.

Future Enhancements

• Extend keyword detection to include more context-aware piracy identifiers.
• Add support for detecting text from uploaded files (e.g., PDFs, images with OCR).
• Include additional languages for keyword detection directly.