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