The goal of the detector is to distinguish real faces from generated ones. For this purpose thousands of photos of people (https://github.com/NVlabs/ffhq-dataset) and thousands of pictures of "generated" people (https://futurism.com/incredibly-realistic-faces-generated-neural-network) were used. The detector was trained with the library FastAI and the technique Transfer Learning. Accuracy was surprisingly good, with over 90% on test data. Further action in the area of Explainable AI is needed to verify that the model is robust.
- Login in with Username: admin Password: admin
- Click on "Pay with Card"
- Fill the boxes
- Use the credit card number 4242424242424242
- Upload a photo with a face on it
- Click on "Predict"
- Clone or download repo
- Insert your Stripe API key in app.py
- Deploy at render.com or somewhere else
git clone https://github.com/anfederico/Flaskex
cd Flaskex
pip install -r requirements.txt
python app.py
- Encrypted user authorizaton
- Database initialization
- New user signup
- User login/logout
- User settings
- Modern user interface
- Limited custom css/js
- Easily customizable