_base_ = [
    '../../_base_/default_runtime.py',
    '../../_base_/schedules/schedule_sgd_100k_iters.py',
    '../../_base_/det_models/dbnet_r18_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 = dict(
    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
train_pipeline_r18 = [
    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),
    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_1333_736 = {{_base_.test_pipeline_1333_736}}

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_r18),
    val=dict(
        type='UniformConcatDataset',
        datasets=test_list,
        pipeline=test_pipeline_1333_736),
    test=dict(
        type='UniformConcatDataset',
        datasets=test_list,
        pipeline=test_pipeline_1333_736))

evaluation = dict(interval=999999, metric='hmean-iou')  # do not evaluate