model-vs-human
Discover 'modelvshuman,' a Python toolkit offering benchmarks for the performance gap between human and machine vision. This tool evaluates PyTorch and TensorFlow models across 17 out-of-distribution datasets with human comparison data. Key features include an extensive model zoo with over 20 standard supervised models, self-supervised contrastive models, vision transformers, and adversarially robust models. It provides straightforward installation and management, ideal for researchers and developers assessing model generalization. Determine if models achieve human-like behavior and OOD robustness with precise evaluations.
