Spaces:
Runtime error
Runtime error
File size: 2,082 Bytes
412c852 |
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 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 |
# dataset settings
dataset_type = 'NYUDataset'
data_root = 'data/nyu'
train_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='LoadDepthAnnotation', depth_rescale_factor=1e-3),
dict(type='RandomDepthMix', prob=0.25),
dict(type='RandomFlip', prob=0.5),
dict(type='RandomCrop', crop_size=(480, 480)),
dict(
type='Albu',
transforms=[
dict(type='RandomBrightnessContrast'),
dict(type='RandomGamma'),
dict(type='HueSaturationValue'),
]),
dict(
type='PackSegInputs',
meta_keys=('img_path', 'depth_map_path', 'ori_shape', 'img_shape',
'pad_shape', 'scale_factor', 'flip', 'flip_direction',
'category_id')),
]
test_pipeline = [
dict(type='LoadImageFromFile'),
dict(type='Resize', scale=(2000, 480), keep_ratio=True),
dict(dict(type='LoadDepthAnnotation', depth_rescale_factor=1e-3)),
dict(
type='PackSegInputs',
meta_keys=('img_path', 'depth_map_path', 'ori_shape', 'img_shape',
'pad_shape', 'scale_factor', 'flip', 'flip_direction',
'category_id'))
]
train_dataloader = dict(
batch_size=8,
num_workers=8,
persistent_workers=True,
sampler=dict(type='InfiniteSampler', shuffle=True),
dataset=dict(
type=dataset_type,
data_root=data_root,
data_prefix=dict(
img_path='images/train', depth_map_path='annotations/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,
test_mode=True,
data_prefix=dict(
img_path='images/test', depth_map_path='annotations/test'),
pipeline=test_pipeline))
test_dataloader = val_dataloader
val_evaluator = dict(
type='DepthMetric',
min_depth_eval=0.001,
max_depth_eval=10.0,
crop_type='nyu_crop')
test_evaluator = val_evaluator
|