Fake-Face-Classification

Description

In this classification task using Regnet model with adabelief optimizer. Using pytorch utils for preprocessing and data splitting by fake-face datasets that is generated by StyleGAN 2 models.

How to use:

First clone the repo

git clone https://github.com/suiboli314/Fake-Face-Classification.git

Then install the requirements in the directory

pip install -r requirements.txt

Run main.py file to begin datasets preprocessing and start training

python main.py

Run evaluation.py to evaluate your trained model

python evaluation.py

Result

The final result of the classification evaluation was:
Accuracy: 1.0 Loss: 0.007738873939961195

Confusion matrix scores:
Precision: 100.0 Recall: 100.0, Accuracy: 100.0: ,f1_score: 100.0