- model_sixteen_class: Contains code that uses linear classifier to compute hyperplane distances of images used in the human dataset
- human_model_correlation: Contains the code that computes the correlation between the human data and the harmonized and baseline models hyperplane distances
- layer_sixteen_way: Contains code that computes hyperplane distances for layer by layer of images used in the human dataset
- wordnet_functions.py & human_categories.py: Contain code from model_vs_human repo that maps imagenet classes to the sixteen categories used in human experiments. Link to model_vs_human to get images: https://github.com/bethgelab/model-vs-human/