|
|
|
model = dict( |
|
type='RPN', |
|
backbone=dict( |
|
type='ResNet', |
|
depth=50, |
|
num_stages=3, |
|
strides=(1, 2, 2), |
|
dilations=(1, 1, 1), |
|
out_indices=(2, ), |
|
frozen_stages=1, |
|
norm_cfg=dict(type='BN', requires_grad=False), |
|
norm_eval=True, |
|
style='caffe', |
|
init_cfg=dict( |
|
type='Pretrained', |
|
checkpoint='open-mmlab://detectron2/resnet50_caffe')), |
|
neck=None, |
|
rpn_head=dict( |
|
type='RPNHead', |
|
in_channels=1024, |
|
feat_channels=1024, |
|
anchor_generator=dict( |
|
type='AnchorGenerator', |
|
scales=[2, 4, 8, 16, 32], |
|
ratios=[0.5, 1.0, 2.0], |
|
strides=[16]), |
|
bbox_coder=dict( |
|
type='DeltaXYWHBBoxCoder', |
|
target_means=[.0, .0, .0, .0], |
|
target_stds=[1.0, 1.0, 1.0, 1.0]), |
|
loss_cls=dict( |
|
type='CrossEntropyLoss', use_sigmoid=True, loss_weight=1.0), |
|
loss_bbox=dict(type='L1Loss', loss_weight=1.0)), |
|
|
|
train_cfg=dict( |
|
rpn=dict( |
|
assigner=dict( |
|
type='MaxIoUAssigner', |
|
pos_iou_thr=0.7, |
|
neg_iou_thr=0.3, |
|
min_pos_iou=0.3, |
|
ignore_iof_thr=-1), |
|
sampler=dict( |
|
type='RandomSampler', |
|
num=256, |
|
pos_fraction=0.5, |
|
neg_pos_ub=-1, |
|
add_gt_as_proposals=False), |
|
allowed_border=0, |
|
pos_weight=-1, |
|
debug=False)), |
|
test_cfg=dict( |
|
rpn=dict( |
|
nms_pre=12000, |
|
max_per_img=2000, |
|
nms=dict(type='nms', iou_threshold=0.7), |
|
min_bbox_size=0))) |
|
|
