File size: 1,095 Bytes
e8f2571 |
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 |
_base_ = '../mask_rcnn/mask-rcnn_r50_fpn_1x_coco.py'
train_pipeline = [
dict(type='LoadImageFromFile', backend_args={{_base_.backend_args}}),
dict(
type='InstaBoost',
action_candidate=('normal', 'horizontal', 'skip'),
action_prob=(1, 0, 0),
scale=(0.8, 1.2),
dx=15,
dy=15,
theta=(-1, 1),
color_prob=0.5,
hflag=False,
aug_ratio=0.5),
dict(type='LoadAnnotations', with_bbox=True, with_mask=True),
dict(type='Resize', scale=(1333, 800), keep_ratio=True),
dict(type='RandomFlip', prob=0.5),
dict(type='PackDetInputs')
]
train_dataloader = dict(dataset=dict(pipeline=train_pipeline))
max_epochs = 48
param_scheduler = [
dict(
type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500),
dict(
type='MultiStepLR',
begin=0,
end=max_epochs,
by_epoch=True,
milestones=[32, 44],
gamma=0.1)
]
train_cfg = dict(max_epochs=max_epochs)
# only keep latest 3 checkpoints
default_hooks = dict(checkpoint=dict(max_keep_ckpts=3))
|