Complete code?

[surya-venkatesan]

Is this a complete code of deepfake image detection using wavelet packets

[v0lta]

Yes, you can see for yourself! To reproduce the FFHQ-style-gan pair: Download the zipped data from https://drive.google.com/file/d/1MOHKuEVqURfCKAN9dwp1o2tuR19OTQCF/view?usp=sharing . You can follow the data perperation steps and train your own classifier. To do so extract the zip file into a data folder and run:

$ python -m freqdect.prepare_dataset ./data/source_data/ --log-packets 
$ python -m freqdect.prepare_dataset ./data/source_data/

the prepare the data. Once the preparation has finished train a classifier using:

$ python -m freqdect.train_classifier \
    --data-prefix ./data/source_data_log_packets_haar_reflect_3 \
    --calc-normalization \
    --features packets

You should end up with a log folder containing the classifier and intermediated loss logs.

[NarendranM08]

Will it indicate that the input image is real or fake or it just makes an analysis

[v0lta]

It will indicate if the image is real or fake, based on the wavelet packet coefficients. In the paper we have measured the performance on standard scientific data-sets and found promising performance However, the code is not production-ready. Two goals of this repository are to prove that deepfake identification based on wavelet packets is possible and that the packet representation has advantages compared to the pixel form.

[NarendranM08]

May I know what type of architecture are used in it

[v0lta]

Sure, you can read the description in the paper or look at the code ( https://github.com/gan-police/frequency-forensics/blob/main/src/freqdect/models.py ).

[NarendranM08]

what type of cnn model is used ? is it Resnext 50?