| # This implements the workflow for applying the network to a directory of images and measuring network performance with metrics. | |
| # these transforms are used for inference to load and regularise inputs | |
| transforms: | |
| - _target_: AsDiscreted | |
| keys: ['@pred', '@label'] | |
| argmax: [true, false] | |
| to_onehot: '@num_classes' | |
| - _target_: ToTensord | |
| keys: ['@pred', '@label'] | |
| device: '@device' | |
| postprocessing: | |
| _target_: Compose | |
| transforms: $@transforms | |
| # inference handlers to load checkpoint, gather statistics | |
| val_handlers: | |
| - _target_: CheckpointLoader | |
| _disabled_: $not os.path.exists(@ckpt_path) | |
| load_path: '@ckpt_path' | |
| load_dict: | |
| model: '@network' | |
| - _target_: StatsHandler | |
| name: null # use engine.logger as the Logger object to log to | |
| output_transform: '$lambda x: None' | |
| - _target_: MetricsSaver | |
| save_dir: '@output_dir' | |
| metrics: ['val_accuracy'] | |
| metric_details: ['val_accuracy'] | |
| batch_transform: "$lambda x: [xx['image'].meta for xx in x]" | |
| summary_ops: "*" | |
| initialize: | |
| - "$monai.utils.set_determinism(seed=123)" | |
| - "$setattr(torch.backends.cudnn, 'benchmark', True)" | |
| run: | |
| - [email protected]() | |