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- _base_ = '../mask_rcnn/mask-rcnn_r50_fpn_1x_coco.py'
- norm_cfg = dict(type='GN', num_groups=32, requires_grad=True)
- model = dict(
- data_preprocessor=dict(
- mean=[103.530, 116.280, 123.675],
- std=[1.0, 1.0, 1.0],
- bgr_to_rgb=False),
- backbone=dict(
- norm_cfg=norm_cfg,
- init_cfg=dict(
- type='Pretrained',
- checkpoint='open-mmlab://detectron/resnet50_gn')),
- neck=dict(norm_cfg=norm_cfg),
- roi_head=dict(
- bbox_head=dict(
- type='Shared4Conv1FCBBoxHead',
- conv_out_channels=256,
- norm_cfg=norm_cfg),
- mask_head=dict(norm_cfg=norm_cfg)))
- # learning policy
- max_epochs = 24
- train_cfg = dict(max_epochs=max_epochs)
- # learning rate
- param_scheduler = [
- dict(
- type='LinearLR', start_factor=0.001, by_epoch=False, begin=0, end=500),
- dict(
- type='MultiStepLR',
- begin=0,
- end=max_epochs,
- by_epoch=True,
- milestones=[16, 22],
- gamma=0.1)
- ]
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