download_and_cut_fits/ contains code for downloading all full-sized fits for object with certain OID, cutting these fits to 28x28pix image, whose center corresponds to the coordinates of the object and saving cuted fits.
download_cuted_fits/ contains code, which download already cuted fits from IPAC.
datasets.py implements frame normalization functions as well as dataset classes for training VAE and RNN.
The files vae.py and rnn.py contain architectures for neural networks and necessary functions for training the models.
VAE training was performed using a notebook train_vae.ipynb. train_rnn_kfold.ipynb was used for training the RNN, which implements k-fold cross-validation. The trained models are saved in a trained_models/.