File size: 1,624 Bytes
7226a40 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 |
{
"test_datalist": "$monai.data.load_decathlon_datalist(@data_list_file_path, is_segmentation=True, data_list_key='validation', base_dir=@dataset_dir)",
"validate#dataset": {
"_target_": "Dataset",
"data": "$@test_datalist",
"transform": "@validate#preprocessing"
},
"validate#key_metric": {
"val_coco": {
"_target_": "scripts.cocometric_ignite.IgniteCocoMetric",
"coco_metric_monai": "$monai.apps.detection.metrics.coco.COCOMetric(classes=['nodule'], iou_list=[0.1], max_detection=[100])",
"output_transform": "$monai.handlers.from_engine(['pred', 'label'])",
"box_key": "box",
"label_key": "label",
"pred_score_key": "label_scores",
"reduce_scalar": false
}
},
"validate#handlers": [
{
"_target_": "CheckpointLoader",
"load_path": "$@ckpt_dir + '/model.pt'",
"load_dict": {
"model": "@network"
}
},
{
"_target_": "StatsHandler",
"iteration_log": false
},
{
"_target_": "MetricsSaver",
"save_dir": "@output_dir",
"metrics": [
"val_coco"
],
"metric_details": [
"val_coco"
],
"batch_transform": "$lambda x: [xx['image'].meta for xx in x]",
"summary_ops": "*"
}
],
"initialize": [
"$setattr(torch.backends.cudnn, 'benchmark', True)"
],
"run": [
"$@validate#evaluator.run()"
]
}
|