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- _base_ = './rtmdet_l_8xb32-300e_coco.py'
- checkpoint = 'https://download.openmmlab.com/mmdetection/v3.0/rtmdet/cspnext_rsb_pretrain/cspnext-s_imagenet_600e.pth' # noqa
- model = dict(
- backbone=dict(
- deepen_factor=0.33,
- widen_factor=0.5,
- # init_cfg=dict(
- # type='Pretrained', prefix='backbone.', checkpoint=checkpoint)
- ),
- neck=dict(in_channels=[128, 256, 512], out_channels=128, num_csp_blocks=1),
- bbox_head=dict(in_channels=128, feat_channels=128, exp_on_reg=False))
- train_pipeline = [
- dict(type='LoadImageFromFile', backend_args={{_base_.backend_args}}),
- dict(type='LoadAnnotations', with_bbox=True),
- dict(type='CachedMosaic', img_scale=(640, 640), pad_val=114.0),
- dict(
- type='RandomResize',
- scale=(1280, 1280),
- ratio_range=(0.5, 2.0),
- keep_ratio=True),
- dict(type='RandomCrop', crop_size=(640, 640)),
- dict(type='YOLOXHSVRandomAug'),
- dict(type='RandomFlip', prob=0.5),
- dict(type='Pad', size=(640, 640), pad_val=dict(img=(114, 114, 114))),
- dict(
- type='CachedMixUp',
- img_scale=(640, 640),
- ratio_range=(1.0, 1.0),
- max_cached_images=20,
- pad_val=(114, 114, 114)),
- dict(type='PackDetInputs')
- ]
- train_pipeline_stage2 = [
- dict(type='LoadImageFromFile', backend_args={{_base_.backend_args}}),
- dict(type='LoadAnnotations', with_bbox=True),
- dict(
- type='RandomResize',
- scale=(640, 640),
- ratio_range=(0.5, 2.0),
- keep_ratio=True),
- dict(type='RandomCrop', crop_size=(640, 640)),
- dict(type='YOLOXHSVRandomAug'),
- dict(type='RandomFlip', prob=0.5),
- dict(type='Pad', size=(640, 640), pad_val=dict(img=(114, 114, 114))),
- dict(type='PackDetInputs')
- ]
- train_dataloader = dict(dataset=dict(pipeline=train_pipeline))
- custom_hooks = [
- dict(
- type='EMAHook',
- ema_type='ExpMomentumEMA',
- momentum=0.0002,
- update_buffers=True,
- priority=49),
- dict(
- type='PipelineSwitchHook',
- switch_epoch=280,
- switch_pipeline=train_pipeline_stage2)
- ]
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