AI‑Powered System to Detect Deepfake Images & Videos
Preventing misinformation, fraud, and digital manipulation

🛡️ Truth Seeker (DeepGuard)

Truth Seeker (DeepGuard) is an AI-powered system designed to detect deepfake images and videos with high accuracy.
It helps prevent misinformation, fraud, identity misuse, and digital manipulation across social media and online platforms.

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🚨 Problem Statement

Deepfake images and videos generated using AI are rapidly spreading on social media.
These fake contents are used to spread misinformation, damage reputations, commit fraud, and manipulate public opinion.

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🧠 Solution Overview

Truth Seeker uses deep learning models to analyze images and videos and classify them as Real or Fake, along with a confidence score.
The system is optimized for accuracy, performance, and scalability.

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🏗️ System Architecture

flowchart TD
    A[User Uploads Image / Video] --> B[Preprocessing Module]
    B --> C[Deepfake Detection Model]
    C --> D[Confidence Scoring Engine]
    D --> E[Final Prediction: Real / Fake]

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Key Features

🔍 AI-based deepfake image & video detection

⚡ High-performance optimized models

📊 Confidence score with predictions

🔐 Secure & privacy-focused processing

📈 Scalable architecture for future upgrades

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🧰 Tech Stack

🌐 Frontend

• HTML, CSS, JavaScript
• React (UI Framework)

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⚙️ Backend

• Python
• FastAPI / Flask

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🤖 AI / Machine Learning

• CNN & Transformer‑based Models
• OpenCV
• PyTorch / TensorFlow

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🔐 Authentication (Google)

• Firebase Authentication
  • Email & Password based login
  • Secure user access control

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⚡ Optimization

• Faster inference
• Optimized CPU performance

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🚀 Deployment

• Vercel
• Docker

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🚀 Getting Started

Prerequisites Python 3.9+

pip

Clone repository

git clone https://github.com/Khushal-93/truth-seeker.git
cd truth-seeker

Backend setup

pip install -r requirements_server.txt
python server.py

Frontend setup

npm install
npm run dev

Start the Server

python server.py

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📂 Project Structure

truth-seeker/
├── public/
├── src/
├── video_deepfake/
├── server.py
├── requirements_server.txt
├── README.md

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📊 Project Status

✔ Image Deepfake Detection

✔ Video Deepfake Detection

🔄 Model Accuracy Improvements (Ongoing)

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👥 Team

Name	Role
Khushal Choudhary	Frontend & UI
Tushar kumar	AI Model & Integration
Pushkar Shinde	Backend & APIs
Ruchita Naik	PPT and coordination

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🎙️ Voice Over Credit

Thanks to Riya Patil for providing the voice-over for our official YouTube project video.

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🤝 Contributing

Contributions are welcome and appreciated!
If you have ideas to improve Truth Seeker / DeepGuard, feel free to contribute.

How to Contribute

1. Fork this repository
2. Create a new branch (git checkout -b feature-name)
3. Make your changes
4. Commit your changes (git commit -m "Add feature")
5. Push to your branch (git push origin feature-name)
6. Open a Pull Request

Please ensure your code follows the project structure and does not break existing functionality.

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📜 License

This project is licensed under the MIT License. See the LICENSE file for details.