Model weights and predictions for reproducible benchmarking experiments in MedMNIST v2

This data repository is associated with our GitHub code <code>weights_*.zip</code>: PyTorch, AutoKeras and Google AutoML Vision are provided for MedMNIST2D. PyTorch and AutoKeras are provided for MedMNIST3D. If you are using PyTorch model weights, please note that the ResNet18_224 / ResNet50_224 models are trained with images resized to 224 x 224 by <code>PIL.Image.NEAREST</code>. Snapshots for <code>auto-sklearn</code> are not uploaded due to the embarrassingly large model sizes (lots of model ensemble). <code>predictions.zip</code>: We also provide all standard prediction files by PyTorch, auto-sklearn, AutoKeras and Google AutoML Vision, which works with <code>medmnist.Evaluator</code>. Each file is named as <code>{flag}_{split}_[AUC]{auc:.3f}_[ACC]{acc:.3f}@{run}.csv</code>, e.g., <code>bloodmnist_test_[AUC]0.997_[ACC]0.957@autokeras_3.csv</code>.