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_base_ = [
'_base_psenet_resnet50_fpnf.py',
'../_base_/datasets/icdar2015.py',
'../_base_/default_runtime.py',
'../_base_/schedules/schedule_adam_600e.py',
]
# optimizer
optim_wrapper = dict(optimizer=dict(lr=1e-4))
train_cfg = dict(val_interval=40)
param_scheduler = [
dict(type='MultiStepLR', milestones=[200, 400], end=600),
]
# dataset settings
icdar2015_textdet_train = _base_.icdar2015_textdet_train
icdar2015_textdet_test = _base_.icdar2015_textdet_test
# use quadrilaterals for icdar2015
model = dict(
backbone=dict(style='pytorch'),
det_head=dict(postprocessor=dict(text_repr_type='quad')))
# pipeline settings
icdar2015_textdet_train.pipeline = _base_.train_pipeline
icdar2015_textdet_test.pipeline = _base_.test_pipeline
train_dataloader = dict(
batch_size=16,
num_workers=8,
persistent_workers=False,
sampler=dict(type='DefaultSampler', shuffle=True),
dataset=icdar2015_textdet_train)
val_dataloader = dict(
batch_size=1,
num_workers=1,
persistent_workers=False,
sampler=dict(type='DefaultSampler', shuffle=False),
dataset=icdar2015_textdet_test)
test_dataloader = val_dataloader
auto_scale_lr = dict(base_batch_size=64 * 4)
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