🎬 Text-to-Video Generation Project

🚀 Overview

The Text-to-Video Generator is an AI-powered tool that converts a simple college name input into a fully generated narrated video using real content from the college’s official website. It automatically:

• Visits the college website
• Extracts useful text and images
• Summarizes the content
• Generates audio narration using text-to-speech
• Combines images and audio to produce a video

This project is ideal for educational platforms, virtual campus tours, and informational content automation.

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🧠 Features

• 🖥️ Web scraping to extract real-time content
• 🧾 Summarization of long content into simple highlights
• 🎤 Audio narration using text-to-speech (TTS)
• 🖼️ Downloading and filtering relevant images
• 🎞️ Slideshow video generation with narration
• 🔁 Modular and customizable structure

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⚙️ Tools & Technologies Used

Component	Tool/Library	Purpose
Backend Framework	Django, FastAPI	REST API and backend logic
Web Scraping	BeautifulSoup, requests	Extract data and media from websites
Text Summarization	transformers, BART, T5	NLP for text simplification
Text-to-Speech	gTTS, pyttsx3, ElevenLabs	Generate narration audio
Video Creation	moviepy, OpenCV	Combine images and audio into MP4
Frontend (optional)	Streamlit, HTML-CSS	User input interface
Deployment	Render.com	Cloud hosting and deployment
Version Control	Git, GitHub	Source control and collaboration

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📂 Project Structure

text-to-video-project/
│
├── backend/               # Backend logic
│   ├── scraper.py         # Scrapes website content
│   ├── summarizer.py      # NLP-based summarization
│   ├── tts_generator.py   # Converts text to audio
│   ├── video_creator.py   # Creates video from media
│   └── api.py             # Backend API endpoints
│
├── media/                 # Stores images/audio
├── static/                # CSS, JS (optional)
├── templates/             # HTML templates (optional)
├── requirements.txt       # Project dependencies
└── README.md              # Project documentation

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🛠️ How to Run the Project Locally

🔹 1. Clone the Repository

git clone https://github.com/your-username/text-to-video-project.git
cd text-to-video-project

🔹 2. Create a Python Virtual Environment

For Windows:

python -m venv venv
venv\Scripts\activate

For macOS/Linux:

python3 -m venv venv
source venv/bin/activate

🔹 3. Install Dependencies

pip install -r requirements.txt

🔹 4. Run the Backend Server

If using FastAPI:

uvicorn backend.api:app --reload

If using Django:

python manage.py runserver

The backend server will start at http://localhost:8000 or your configured port.

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💡 Use Cases

• 🎓 Virtual campus tours for colleges and universities
• 📹 Automated video creation for educational platforms
• 🛍️ E-commerce product showcase generator
• 📚 Text-to-video converters for e-learning
• 📰 News summarization and video generation
• 📢 Marketing videos for institutions and organizations

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🌐 Deployment Information

The project is cloud-ready and can be deployed to platforms such as:

Platform	Purpose	Example URL
Render	Full-stack deployment	https://blueplanettexttovideo.onrender.com
GitHub Pages	Frontend hosting (optional)	For static UIs only
Heroku	Python backend (deprecated)	Alternative to Render
AWS/GCP/Azure	Scalable production hosting	Enterprise-level deployments

You can containerize the project using Docker for better portability.

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🙌 Contributors

• 👨‍💻 Sanjay Kumar S – AI Developer & Backend Engineer
• 🧪 Internship Project under Python AI

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📃 License

This project is licensed under the MIT License. You are free to use, modify, and distribute it with proper attribution.

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📬 Contact

Sanjay Kumar S 📧 [email protected] 📍 Chennai, India 🎓 B.Tech Artificial Intelligence and Data Science, Panimalar Engineering College Chennai