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