| # MONAI | |
| * **apps**: high level medical domain specific deep learning applications. | |
| * **config**: for system configuration and diagnostic output. | |
| * **data**: for the datasets, readers/writers, and synthetic data | |
| * **engines**: engine-derived classes for extending Ignite behaviour. | |
| * **handlers**: defines handlers for implementing functionality at various stages in the training process. | |
| * **inferers**: defines model inference methods. | |
| * **losses**: classes defining loss functions. | |
| * **metrics**: defines metric tracking types. | |
| * **networks**: contains network definitions, component definitions, and Pytorch specific utilities. | |
| * **transforms**: defines data transforms for preprocessing and postprocessing. | |
| * **utils**: generic utilities intended to be implemented in pure Python or using Numpy, | |
| and not with Pytorch, such as namespace aliasing, auto module loading. | |
| * **visualize**: utilities for data visualization. |