Image Segmentation
Transformers
PyTorch
upernet
Inference Endpoints
test2 / mmseg /datasets /chase_db1.py
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import os.path as osp
from .builder import DATASETS
from .custom import CustomDataset
@DATASETS.register_module()
class ChaseDB1Dataset(CustomDataset):
"""Chase_db1 dataset.
In segmentation map annotation for Chase_db1, 0 stands for background,
which is included in 2 categories. ``reduce_zero_label`` is fixed to False.
The ``img_suffix`` is fixed to '.png' and ``seg_map_suffix`` is fixed to
'_1stHO.png'.
"""
CLASSES = ('background', 'vessel')
PALETTE = [[120, 120, 120], [6, 230, 230]]
def __init__(self, **kwargs):
super(ChaseDB1Dataset, self).__init__(
img_suffix='.png',
seg_map_suffix='_1stHO.png',
reduce_zero_label=False,
**kwargs)
assert osp.exists(self.img_dir)