bev-project/configs/nuscenes/det/centerhead/default.yaml

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YAML

gt_paste_stop_epoch: 15
model:
heads:
object:
type: CenterHead
in_channels: null
train_cfg:
point_cloud_range: ${point_cloud_range}
grid_size: [1024, 1024, 1]
voxel_size: ${voxel_size}
out_size_factor: 8
dense_reg: 1
gaussian_overlap: 0.1
max_objs: 500
min_radius: 2
code_weights: [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.2, 0.2]
test_cfg:
post_center_limit_range: [-61.2, -61.2, -10.0, 61.2, 61.2, 10.0]
max_per_img: 500
max_pool_nms: false
min_radius: [4, 12, 10, 1, 0.85, 0.175]
score_threshold: 0.1
out_size_factor: 8
voxel_size: ${voxel_size[:2]}
nms_type: rotate
pre_max_size: 1000
post_max_size: 83
nms_thr: 0.2
tasks:
- ["car"]
- ["truck", "construction_vehicle"]
- ["bus", "trailer"]
- ["barrier"]
- ["motorcycle", "bicycle"]
- ["pedestrian", "traffic_cone"]
common_heads:
reg: [2, 2]
height: [1, 2]
dim: [3, 2]
rot: [2, 2]
vel: [2, 2]
share_conv_channel: 64
bbox_coder:
type: CenterPointBBoxCoder
pc_range: ${point_cloud_range}
post_center_range: [-61.2, -61.2, -10.0, 61.2, 61.2, 10.0]
max_num: 500
score_threshold: 0.1
out_size_factor: 8
voxel_size: ${voxel_size[:2]}
code_size: 9
separate_head:
type: SeparateHead
init_bias: -2.19
final_kernel: 3
loss_cls:
type: GaussianFocalLoss
reduction: mean
loss_bbox:
type: L1Loss
reduction: mean
loss_weight: 0.25
norm_bbox: true