YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/model-cards#model-card-metadata)

Deepfake Image Detection Tool Using Xception Architecture

This project is a web-based Deepfake Image Detection Tool developed for Apex Broadcasting Network Ltd to verify the authenticity of digital images before publication. The system uses a deep learning model based on the Xception architecture to accurately distinguish between real and manipulated images.

Features

  • Image upload and deepfake detection
  • Xception-based deep learning detection engine
  • Confidence score for each prediction
  • Deepfake literacy and awareness content
  • Secure image handling with CSRF protection and rate limiting

Technology Stack

  • Backend: Python (Flask)
  • Frontend: HTML, CSS, JavaScript
  • Deep Learning Model: Xception (TensorFlow/Keras)
  • Security: CSRF protection, rate limiting, secure headers

Project Structure

  • app.py โ€“ Flask backend and detection logic
  • templates/index.html โ€“ User interface
  • static/ โ€“ Images and frontend assets
  • best_xception_model_finetuned.keras โ€“ Trained model
  • uploads/ โ€“ Temporary image storage

How to Run Locally

pip install -r requirements.txt
python app.py
"# deepfake-tool" 
Downloads last month
10
Inference Providers NEW
This model isn't deployed by any Inference Provider. ๐Ÿ™‹ Ask for provider support