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# Copyright (c) OpenMMLab. All rights reserved.
import copy
import os.path as osp
from typing import List
from mmengine.fileio import load
from mmseg.registry import DATASETS
from .basesegdataset import BaseSegDataset
@DATASETS.register_module()
class DecathlonDataset(BaseSegDataset):
"""Dataset for Dacathlon dataset.
The dataset.json format is shown as follows
.. code-block:: none
{
"name": "BRATS",
"tensorImageSize": "4D",
"modality":
{
"0": "FLAIR",
"1": "T1w",
"2": "t1gd",
"3": "T2w"
},
"labels": {
"0": "background",
"1": "edema",
"2": "non-enhancing tumor",
"3": "enhancing tumour"
},
"numTraining": 484,
"numTest": 266,
"training":
[
{
"image": "./imagesTr/BRATS_306.nii.gz"
"label": "./labelsTr/BRATS_306.nii.gz"
...
}
]
"test":
[
"./imagesTs/BRATS_557.nii.gz"
...
]
}
"""
def load_data_list(self) -> List[dict]:
"""Load annotation from directory or annotation file.
Returns:
list[dict]: All data info of dataset.
"""
# `self.ann_file` denotes the absolute annotation file path if
# `self.root=None` or relative path if `self.root=/path/to/data/`.
annotations = load(self.ann_file)
if not isinstance(annotations, dict):
raise TypeError(f'The annotations loaded from annotation file '
f'should be a dict, but got {type(annotations)}!')
raw_data_list = annotations[
'training'] if not self.test_mode else annotations['test']
data_list = []
for raw_data_info in raw_data_list:
# `2:` works for removing './' in file path, which will break
# loading from cloud storage.
if isinstance(raw_data_info, dict):
data_info = dict(
img_path=osp.join(self.data_root, raw_data_info['image']
[2:]))
data_info['seg_map_path'] = osp.join(
self.data_root, raw_data_info['label'][2:])
else:
data_info = dict(
img_path=osp.join(self.data_root, raw_data_info)[2:])
data_info['label_map'] = self.label_map
data_info['reduce_zero_label'] = self.reduce_zero_label
data_info['seg_fields'] = []
data_list.append(data_info)
annotations.pop('training')
annotations.pop('test')
metainfo = copy.deepcopy(annotations)
metainfo['classes'] = [*metainfo['labels'].values()]
# Meta information load from annotation file will not influence the
# existed meta information load from `BaseDataset.METAINFO` and
# `metainfo` arguments defined in constructor.
for k, v in metainfo.items():
self._metainfo.setdefault(k, v)
return data_list
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