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_base_ = '../retinanet/retinanet_r50_fpn_1x_coco.py'
# model settings
model = dict(
type='FSAF',
bbox_head=dict(
type='FSAFHead',
num_classes=80,
in_channels=256,
stacked_convs=4,
feat_channels=256,
reg_decoded_bbox=True,
# Only anchor-free branch is implemented. The anchor generator only
# generates 1 anchor at each feature point, as a substitute of the
# grid of features.
anchor_generator=dict(
type='AnchorGenerator',
octave_base_scale=1,
scales_per_octave=1,
ratios=[1.0],
strides=[8, 16, 32, 64, 128]),
bbox_coder=dict(_delete_=True, type='TBLRBBoxCoder', normalizer=4.0),
loss_cls=dict(
type='FocalLoss',
use_sigmoid=True,
gamma=2.0,
alpha=0.25,
loss_weight=1.0,
reduction='none'),
loss_bbox=dict(
_delete_=True,
type='IoULoss',
eps=1e-6,
loss_weight=1.0,
reduction='none')),
# training and testing settings
train_cfg=dict(
assigner=dict(
_delete_=True,
type='CenterRegionAssigner',
pos_scale=0.2,
neg_scale=0.2,
min_pos_iof=0.01),
allowed_border=-1,
pos_weight=-1,
debug=False))
optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0001)
optimizer_config = dict(
_delete_=True, grad_clip=dict(max_norm=10, norm_type=2))
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