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AI-generated image detection

(Work In Progress)

  • Refactor code
  • Review dependencies
  • Containerize (Docker)
  • Update documentation

AI-Generated Image detection

This part handles the detection of AI-generated images. The current code contains two classifiers to detect AI-generated images from two types of architectures:

  • GANs

Model weights

1. CNN Detection

Run the download_weights_CNN.sh script:

bash download_weights_CNN.sh

Note: you need wget installed on your system (it is by default for most Linux systems).

2. Diffusion

TODO

Run the models

Make sure you have the weights available before doing so.

TODO: environments

1. CNN Detection

python CNN_model_classifier.py

Available options:

  • -f / --file (default='examples_realfakedir')
  • -m / --model_path (default='weights/blur_jpg_prob0.5.pth')
  • -c / --crop (default=None): Specify crop size (int) by default, do not crop.
  • --use_cpu: use cpu (by default uses GPU) -> TODO: remove (obsolete)

Example usage:

python CNN_model_classifier.py -f examples/real.png -m weights/blur_jpg_prob0.5.pth

2. Diffusion detection

TODO

References

Based on: