|
- _base_ = './solo_r50_fpn_1x_coco.py'
-
- 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, with_mask=True),
- dict(
- type='Resize',
- img_scale=[(1333, 800), (1333, 768), (1333, 736), (1333, 704),
- (1333, 672), (1333, 640)],
- multiscale_mode='value',
- 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', 'gt_masks']),
- ]
- data = dict(train=dict(pipeline=train_pipeline))
-
- lr_config = dict(
- policy='step',
- warmup='linear',
- warmup_iters=500,
- warmup_ratio=1.0 / 3,
- step=[27, 33])
- runner = dict(type='EpochBasedRunner', max_epochs=36)
|