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| _base_ = [ | |
| '_base_svtr-tiny.py', | |
| '../_base_/default_runtime.py', | |
| '../_base_/datasets/mjsynth.py', | |
| '../_base_/datasets/synthtext.py', | |
| '../_base_/datasets/cute80.py', | |
| '../_base_/datasets/iiit5k.py', | |
| '../_base_/datasets/svt.py', | |
| '../_base_/datasets/svtp.py', | |
| '../_base_/datasets/icdar2013.py', | |
| '../_base_/datasets/icdar2015.py', | |
| '../_base_/schedules/schedule_adam_base.py', | |
| ] | |
| train_cfg = dict(type='EpochBasedTrainLoop', max_epochs=20, val_interval=1) | |
| optim_wrapper = dict( | |
| type='OptimWrapper', | |
| optimizer=dict( | |
| type='AdamW', | |
| lr=5 / (10**4) * 2048 / 2048, | |
| betas=(0.9, 0.99), | |
| eps=8e-8, | |
| weight_decay=0.05)) | |
| param_scheduler = [ | |
| dict( | |
| type='LinearLR', | |
| start_factor=0.5, | |
| end_factor=1., | |
| end=2, | |
| verbose=False, | |
| convert_to_iter_based=True), | |
| dict( | |
| type='CosineAnnealingLR', | |
| T_max=19, | |
| begin=2, | |
| end=20, | |
| verbose=False, | |
| convert_to_iter_based=True), | |
| ] | |
| # dataset settings | |
| train_list = [_base_.mjsynth_textrecog_train, _base_.synthtext_textrecog_train] | |
| test_list = [ | |
| _base_.cute80_textrecog_test, _base_.iiit5k_textrecog_test, | |
| _base_.svt_textrecog_test, _base_.svtp_textrecog_test, | |
| _base_.icdar2013_textrecog_test, _base_.icdar2015_textrecog_test | |
| ] | |
| val_evaluator = dict( | |
| dataset_prefixes=['CUTE80', 'IIIT5K', 'SVT', 'SVTP', 'IC13', 'IC15']) | |
| test_evaluator = val_evaluator | |
| train_dataloader = dict( | |
| batch_size=512, | |
| num_workers=24, | |
| persistent_workers=True, | |
| pin_memory=True, | |
| sampler=dict(type='DefaultSampler', shuffle=True), | |
| dataset=dict( | |
| type='ConcatDataset', | |
| datasets=train_list, | |
| pipeline=_base_.train_pipeline)) | |
| val_dataloader = dict( | |
| batch_size=128, | |
| num_workers=8, | |
| persistent_workers=True, | |
| pin_memory=True, | |
| drop_last=False, | |
| sampler=dict(type='DefaultSampler', shuffle=False), | |
| dataset=dict( | |
| type='ConcatDataset', | |
| datasets=test_list, | |
| pipeline=_base_.test_pipeline)) | |
| test_dataloader = val_dataloader | |