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CSCE633 class project -- Lighten the Face Forgery Detection Network by using MobileNet

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CSCE633

CSCE633 class project -- Lighten the Face Forgery Detection Network by using MobileNet

This is our implementation of the CSCE633 course project. After downloading all files, you should first unzip the "original_database" and "extended_database" in the "dataset" file and move these two datasets to the main directory. After that, you can simply use train.py to train a model based on a chosen dataset and use test.py to get the prediction accuracy of a trained model. You can also use roc_curve.py to draw the ROC curve based on a trained model.

The report is also attached.

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CSCE633 class project -- Lighten the Face Forgery Detection Network by using MobileNet

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