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- _base_ = 'fcos_r50-caffe_fpn_gn-head_1x_coco.py'
- # model setting
- model = dict(
- data_preprocessor=dict(
- type='DetDataPreprocessor',
- mean=[103.530, 116.280, 123.675],
- std=[1.0, 1.0, 1.0],
- bgr_to_rgb=False,
- pad_size_divisor=32),
- backbone=dict(
- init_cfg=dict(
- type='Pretrained',
- checkpoint='open-mmlab://detectron2/resnet50_caffe')),
- bbox_head=dict(
- norm_on_bbox=True,
- centerness_on_reg=True,
- dcn_on_last_conv=False,
- center_sampling=True,
- conv_bias=True,
- loss_bbox=dict(type='GIoULoss', loss_weight=1.0)),
- # training and testing settings
- test_cfg=dict(nms=dict(type='nms', iou_threshold=0.6)))
- # learning rate
- param_scheduler = [
- dict(
- type='LinearLR',
- start_factor=1.0 / 3.0,
- by_epoch=False,
- begin=0,
- end=500),
- dict(
- type='MultiStepLR',
- begin=0,
- end=12,
- by_epoch=True,
- milestones=[8, 11],
- gamma=0.1)
- ]
- # optimizer
- optim_wrapper = dict(clip_grad=None)
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