|
_base_ = '../cascade_rcnn/cascade_rcnn_r50_fpn_1x_coco.py' |
|
model = dict( |
|
backbone=dict( |
|
_delete_=True, |
|
type='HRNet', |
|
extra=dict( |
|
stage1=dict( |
|
num_modules=1, |
|
num_branches=1, |
|
block='BOTTLENECK', |
|
num_blocks=(4, ), |
|
num_channels=(64, )), |
|
stage2=dict( |
|
num_modules=1, |
|
num_branches=2, |
|
block='BASIC', |
|
num_blocks=(4, 4), |
|
num_channels=(32, 64)), |
|
stage3=dict( |
|
num_modules=4, |
|
num_branches=3, |
|
block='BASIC', |
|
num_blocks=(4, 4, 4), |
|
num_channels=(32, 64, 128)), |
|
stage4=dict( |
|
num_modules=3, |
|
num_branches=4, |
|
block='BASIC', |
|
num_blocks=(4, 4, 4, 4), |
|
num_channels=(32, 64, 128, 256))), |
|
init_cfg=dict( |
|
type='Pretrained', checkpoint='open-mmlab://msra/hrnetv2_w32')), |
|
neck=dict( |
|
_delete_=True, |
|
type='HRFPN', |
|
in_channels=[32, 64, 128, 256], |
|
out_channels=256)) |
|
|
|
lr_config = dict(step=[16, 19]) |
|
runner = dict(type='EpochBasedRunner', max_epochs=20) |
|
|
