mmsegmentation/configs/pspnet/pspnet_r50-d8_512x1024_80k_...

30 lines
992 B
Python

_base_ = [
'../_base_/models/pspnet_r50-d8.py', '../_base_/datasets/cityscapes.py',
'../_base_/default_runtime.py', '../_base_/schedules/schedule_80k.py'
]
img_norm_cfg = dict(
mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
test_pipeline = [
dict(type='LoadImageFromFile'),
dict(
type='MultiScaleFlipAug',
img_scale=(1920, 1080),
# img_ratios=[0.5, 0.75, 1.0, 1.25, 1.5, 1.75],
flip=False,
transforms=[
dict(type='Resize', keep_ratio=True),
dict(type='RandomFlip'),
dict(type='Normalize', **img_norm_cfg),
dict(type='ImageToTensor', keys=['img']),
dict(type='Collect', keys=['img']),
])
]
data = dict(
test=dict(
type='NightDrivingDataset',
data_root='data/NighttimeDrivingTest/',
img_dir='leftImg8bit/test/night',
ann_dir='gtCoarse_daytime_trainvaltest/test/night',
pipeline=test_pipeline))