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- _base_ = './gfl_r50_fpn_1x_coco.py'
- # learning policy
- lr_config = dict(step=[16, 22])
- runner = dict(type='EpochBasedRunner', max_epochs=24)
- # multi-scale training
- img_norm_cfg = dict(
- mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
- train_pipeline = [
- dict(type='LoadImageFromFile'),
- dict(type='LoadAnnotations', with_bbox=True),
- dict(
- type='Resize',
- img_scale=[(1333, 480), (1333, 800)],
- multiscale_mode='range',
- keep_ratio=True),
- dict(type='RandomFlip', flip_ratio=0.5),
- dict(type='Normalize', **img_norm_cfg),
- dict(type='Pad', size_divisor=32),
- dict(type='DefaultFormatBundle'),
- dict(type='Collect', keys=['img', 'gt_bboxes', 'gt_labels']),
- ]
- data = dict(train=dict(pipeline=train_pipeline))
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