bev-project/configs/test_minimal.yaml

117 lines
2.0 KiB
YAML

checkpoint_config:
interval: 1
data:
samples_per_gpu: 1
workers_per_gpu: 0
log_config:
hooks:
- type: TextLoggerHook
interval: 50
lr_config:
min_lr_ratio: 0.001
policy: CosineAnnealing
warmup: linear
warmup_iters: 500
warmup_ratio: 0.33333333
model:
encoders:
lidar:
backbone:
encoder_channels:
- - 16
- 16
- 32
- - 32
- 32
- 64
- - 64
- 64
- 128
- - 128
- 128
encoder_paddings:
- - 0
- 0
- 1
- - 0
- 0
- 1
- - 0
- 0
- - 1
- 1
- 0
- - 0
- 0
in_channels: 5
order:
- conv
- norm
- act
output_channels: 128
sparse_shape:
- 1440
- 1440
- 41
type: SparseEncoder
voxelize:
max_num_points: 10
max_voxels:
- 120000
- 160000
point_cloud_range:
- -54.0
- -54.0
- -5.0
- 54.0
- 54.0
- 3.0
voxel_size:
- 0.075
- 0.075
- 0.2
fuser:
in_channels:
- 256
out_channels: 256
type: ConvFuser
heads:
map:
classes:
- drivable_area
- ped_crossing
- walkway
- stop_line
- carpark_area
- divider
deep_supervision: true
dice_weight: 0.5
focal_alpha: 0.25
focal_gamma: 2.0
grid_transform:
input_scope:
- - -54.0
- 54.0
- 0.75
- - -54.0
- 54.0
- 0.75
output_scope:
- - -50
- 50
- 0.167
- - -50
- 50
- 0.167
in_channels: 256
loss: focal
type: EnhancedBEVSegmentationHead
use_dice_loss: true
type: BEVFusion
optimizer:
lr: 0.0001
type: AdamW
runner:
max_epochs: 1
type: EpochBasedRunner