48 lines
1.5 KiB
Python
48 lines
1.5 KiB
Python
# dataset settings
|
|
dataset_type = 'CityscapesDataset'
|
|
data_root = 'data/cityscapes/'
|
|
crop_size = (512, 1024)
|
|
train_pipeline = [
|
|
dict(type='LoadImageFromFile'),
|
|
dict(type='LoadAnnotations'),
|
|
dict(type='RandomResize', scale=(2048, 1024), ratio_range=(0.5, 2.0)),
|
|
dict(type='RandomCrop', crop_size=crop_size, cat_max_ratio=0.75),
|
|
dict(type='RandomFlip', prob=0.5),
|
|
dict(type='PhotoMetricDistortion'),
|
|
dict(type='PackSegInputs')
|
|
]
|
|
test_pipeline = [
|
|
dict(type='LoadImageFromFile'),
|
|
dict(type='Resize', scale=(2048, 1024), keep_ratio=True),
|
|
# add loading annotation after ``Resize`` because ground truth
|
|
# does not need to do resize data transform
|
|
dict(type='LoadAnnotations'),
|
|
dict(type='PackSegInputs')
|
|
]
|
|
train_dataloader = dict(
|
|
batch_size=2,
|
|
num_workers=2,
|
|
persistent_workers=True,
|
|
sampler=dict(type='InfiniteSampler', shuffle=True),
|
|
dataset=dict(
|
|
type=dataset_type,
|
|
data_root=data_root,
|
|
data_prefix=dict(
|
|
img_path='leftImg8bit/train', seg_map_path='gtFine/train'),
|
|
pipeline=train_pipeline))
|
|
val_dataloader = dict(
|
|
batch_size=1,
|
|
num_workers=4,
|
|
persistent_workers=True,
|
|
sampler=dict(type='DefaultSampler', shuffle=False),
|
|
dataset=dict(
|
|
type=dataset_type,
|
|
data_root=data_root,
|
|
data_prefix=dict(
|
|
img_path='leftImg8bit/val', seg_map_path='gtFine/val'),
|
|
pipeline=test_pipeline))
|
|
test_dataloader = val_dataloader
|
|
|
|
val_evaluator = dict(type='IoUMetric', metrics=['mIoU'])
|
|
test_evaluator = val_evaluator
|