DeepFake Image Detection Details 

Detects whether an image is real or deepfake using Transformers

Project Description 

This project focuses on detecting deepfake images by analyzing visual patterns using advanced deep learning techniques. A Vision Transformer–based model is used to classify images as real or manipulated. The system provides an easy-to-use web interface where users can upload images and instantly get prediction results, making it suitable for real-world and academic use cases. 

Features 

• Detects real vs deepfake images with high accuracy

• Uses Vision Transformer (ViT) for image classification

• Image upload–based prediction through web interface

• Clean and well-documented source code

• Suitable for academic and final-year projects

Tech Stack

• Python

• Hugging Face (Pre-trained Models)

• Vision Transformer (ViT)

• Flask (Backend Framework)

• HTML, JavaScript (Frontend)

• NumPy, Pandas, and other essential Python libraries

System Requirements

• Python 3.10+

• Anaconda

• No GPU required

Deliverables 

• Jupyter Notebook

• Dataset

• Setup over video call 

• WhatsApp support