MotionBEV-semantickitti.yaml

# Config format schema number
format_version: 4

###################
## Model options
model_params:
  grid_size:
    - 480
    - 360
    - 32

  fea_dim: 9
  ppmodel_init_dim: 32
  use_norm: True
  dropout: 0.5  # 0.2

  use_co_attention: True  # use co-attention gate


###################
## Data_loader options
data_loader:
  data_path: "/home/ubuntu/xjp/data/KITTI"
  return_ref: True  # reflectivity(intensity)
  residual: 8  # residual 1-8, 0 for none
  residual_path: "/home/ubuntu/xjp/data/KITTI/mos/residual-polar-sequential-480-360"
  batch_size: 8
  shuffle: True
  drop_few_static_frames: True  # drop_few_static_frames for training, speed up training while slightly reduce the accuracy
  num_workers: 4  # Set to four times the number of available GPUs

  dataset_type: "polar"
  ignore_label: 255
  fixed_volume_space: True

  rotate_aug: True
  flip_aug: True
  transform_aug: True


###################
## Train params
train_params:
  name: "MotionBEV"
  model_load_path: "/home/ubuntu/Desktop/MotionBEV/pretrain/MotionBEV-kitti-val-76.54.pt" # none for training from scratch
  checkpoint_every_n_steps: 500
  max_num_epochs: 100
  eval_every_n_steps: 1048  #1411 #1048
  learning_rate: 0.01
  optimizer: "SGD" # "SGD" "Adam" "AdamW"
  weight_decay: 0.0001   # weight decay
  momentum: 0.9          # sgd momentum
  wup_epochs: 1          # warmup during first XX epochs (can be float)
  lr_decay: 0.95         # learning rate decay per epoch after initial cycle (from min lr)