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_base_ = [
'../../_base_/default_runtime.py',
'../../_base_/schedules/schedule_sgd_100k_iters.py',
'../../_base_/det_models/dbnet_r50dcnv2_fpnc.py',
'../../_base_/det_datasets/synthtext.py',
'../../_base_/det_pipelines/dbnet_pipeline.py'
]
train_list = {{_base_.train_list}}
test_list = {{_base_.test_list}}
img_norm_cfg_r50dcnv2 = dict(
mean=[122.67891434, 116.66876762, 104.00698793],
std=[58.395, 57.12, 57.375],
to_rgb=True)
train_pipeline_r50dcnv2 = [
dict(type='LoadImageFromFile', color_type='color_ignore_orientation'),
dict(
type='LoadTextAnnotations',
with_bbox=True,
with_mask=True,
poly2mask=False),
dict(type='ColorJitter', brightness=32.0 / 255, saturation=0.5),
dict(type='Normalize', **img_norm_cfg_r50dcnv2),
dict(
type='ImgAug',
args=[['Fliplr', 0.5],
dict(cls='Affine', rotate=[-10, 10]), ['Resize', [0.5, 3.0]]],
clip_invalid_ploys=False),
dict(type='EastRandomCrop', target_size=(640, 640)),
dict(type='DBNetTargets', shrink_ratio=0.4),
dict(type='Pad', size_divisor=32),
dict(
type='CustomFormatBundle',
keys=['gt_shrink', 'gt_shrink_mask', 'gt_thr', 'gt_thr_mask'],
visualize=dict(flag=False, boundary_key='gt_shrink')),
dict(
type='Collect',
keys=['img', 'gt_shrink', 'gt_shrink_mask', 'gt_thr', 'gt_thr_mask'])
]
test_pipeline_4068_1024 = {{_base_.test_pipeline_4068_1024}}
data = dict(
samples_per_gpu=16,
workers_per_gpu=8,
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=999999, metric='hmean-iou') # do not evaluate
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