SoftGroup/configs/softgroup_default_scannet.yaml
2022-04-08 11:10:38 +00:00

73 lines
1.6 KiB
YAML

model:
channels: 32
num_blocks: 7
semantic_classes: 20
instance_classes: 18
sem2ins_classes: []
semantic_only: False
ignore_label: -100
grouping_cfg:
score_thr: 0.2
radius: 0.04
mean_active: 300
class_numpoint_mean: [-1., -1., 3917., 12056., 2303.,
8331., 3948., 3166., 5629., 11719.,
1003., 3317., 4912., 10221., 3889.,
4136., 2120., 945., 3967., 2589.]
npoint_thr: 0.05 # absolute if class_numpoint == -1, relative if class_numpoint != -1
ignore_classes: [0, 1]
instance_voxel_cfg:
scale: 50
spatial_shape: 20
train_cfg:
max_proposal_num: 200
pos_iou_thr: 0.5
test_cfg:
x4_split: False
cls_score_thr: 0.001
mask_score_thr: -0.5
min_npoint: 100
fixed_modules: ['input_conv', 'unet', 'output_layer', 'semantic_linear', 'offset_linear']
data:
train:
type: 'scannetv2'
data_root: 'dataset/scannetv2'
prefix: 'train'
suffix: '_inst_nostuff.pth'
training: True
voxel_cfg:
scale: 50
spatial_shape: [128, 512]
max_npoint: 250000
min_npoint: 5000
test:
type: 'scannetv2'
data_root: 'dataset/scannetv2'
prefix: 'val'
suffix: '_inst_nostuff.pth'
training: False
voxel_cfg:
scale: 50
spatial_shape: [128, 512]
max_npoint: 250000
min_npoint: 5000
dataloader:
train:
batch_size: 4
num_workers: 4
test:
batch_size: 1
num_workers: 16
optimizer:
type: 'Adam'
lr: 0.001
epochs: 512
step_epoch: 200
save_freq: 8
pretrain: 'hais_ckpt.pth'
work_dir: 'work_dirs/softgroup_scannet'