Dataset for KBr-KCl replacement using operando synchrotron tomography experiments- part 2:Generative AI

This dataset contains training images and pre-trained models for editing reaction-induced pores from KBr–KCl replacement experiments using the latent space of StyleGAN2-ada. The data include images, models and files for images of resolution 512 and 256: TrainingImgsStyleGAN2-ADA.zip : 29k images of size 512 by 512 from KBr-KCl synchrotron experiments in four parts. The whole 4D dataset are available at previous Zenodo repository. TrainingImgsStyleGAN2-ADA_256.zip: Images of size 256 by 256 of KBr-KCl experiments and SEM images of our natural sample. Similar data and models for resolution of 256 and 512 can be found in res_256.zip and res_512.zip. These are: Labelled_images: a folder containing the labelled image which are inverted to the latent space of the pre-trained generator. TrainedModels: a folder where you can find pre-trained generator, encoder, and VGG model. InversionLog (log.txt): a text file logging the loss functions and metrics during inverting images. labels (df_labels.csv): a csv files showing the labels corresponding to each image in the labelled_images folder. Latent codes (latent_codes.pkl): a pickle file containing the latent codes corresponding to each image in the labelled_images folder. All datasets were acquired at the TOMCAT beamline, Swiss Light Source (PSI, Switzerland). For more details on the original 4D dataset, see our other Zenodo page for the first part of the paper. You can also read the preprint.