MMOCR / configs /textdet /dbnet /dbnet_r50dcnv2_fpnc_1200e_icdar2015.py
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_base_ = [
'../../_base_/runtime_10e.py',
'../../_base_/schedules/schedule_sgd_1200e.py',
'../../_base_/det_models/dbnet_r50dcnv2_fpnc.py',
'../../_base_/det_datasets/icdar2015.py',
'../../_base_/det_pipelines/dbnet_pipeline.py'
]
train_list = {{_base_.train_list}}
test_list = {{_base_.test_list}}
train_pipeline_r50dcnv2 = {{_base_.train_pipeline_r50dcnv2}}
test_pipeline_4068_1024 = {{_base_.test_pipeline_4068_1024}}
load_from = 'checkpoints/textdet/dbnet/res50dcnv2_synthtext.pth'
data = dict(
samples_per_gpu=8,
workers_per_gpu=4,
val_dataloader=dict(samples_per_gpu=1),
test_dataloader=dict(samples_per_gpu=1),
train=dict(
type='UniformConcatDataset',
datasets=train_list,
pipeline=train_pipeline_r50dcnv2),
val=dict(
type='UniformConcatDataset',
datasets=test_list,
pipeline=test_pipeline_4068_1024),
test=dict(
type='UniformConcatDataset',
datasets=test_list,
pipeline=test_pipeline_4068_1024))
evaluation = dict(interval=100, metric='hmean-iou')