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Deepfake Detection System

🚀 Quick Start (How to Run)

1. Install Dependencies

Open your terminal in this folder and run:

pip install -r requirements.txt

2. Run the Web App

To start the User Interface (Streamlit):

streamlit run src/app.py

3. Run Training (Optional)

If you have data in data/train/real and data/train/fake, you can train the model:

python src/train.py --epochs 5

📂 Project Structure

  • src/app.py: The Main Web Interface (for the demo).
  • src/inference.py: The logic that finds the timestamps.
  • src/model.py: The AI (ResNet + LSTM).
  • README_EXPLAINER.md: Explanation for judges.

About

The project follows a modular and explainable architecture, separating spatial image-based detection from temporal video reasoning, enabling robust detection under real-world conditions such as compression, low resolution, and mixed real/fake content.

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