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_base_ = [ | |
'../../_base_/default_runtime.py', | |
'../../_base_/schedules/schedule_sgd_100k_iters.py', | |
'../../_base_/det_models/dbnetpp_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=200000, metric='hmean-iou') # do not evaluate | |