training.yaml

parking_model:
  # train
  data_dir: './e2e_parking/'
  log_dir: './log/'
  checkpoint_dir: './ckpt'
  log_every_n_steps: 10
  check_val_every_n_epoch: 5

  epochs: 155
  learning_rate: 0.0001
  weight_decay: 0.0001
  batch_size: 12

  training_map: "Town04_Opt"
  validation_map: "Town04_Opt_Val"
  future_frame_nums: 4
  hist_frame_nums: 10
  token_nums: 204
  image_crop: 256

  # bev encoder
  bev_encoder_in_channel: 64
  bev_encoder_out_channel: 258  # 256 + 2

  # bev model
  bev_x_bound: [-10.0, 10.0, 0.1]
  bev_y_bound: [-10.0, 10.0, 0.1]
  bev_z_bound: [-10.0, 10.0, 20.0]
  d_bound: [0.5, 12.5, 0.25]
  final_dim: [256, 256]
  bev_down_sample: 8
  use_depth_distribution: 1
  backbone: "efficientnet-b4"

  # segmentation
  seg_classes: 3
  seg_vehicle_weights: [1.0, 2.0, 2.0]

  # transformer encoder
  tf_en_dim: 258
  tf_en_heads: 6
  tf_en_layers: 4
  tf_en_dropout: 0.05
  tf_en_bev_length: 256
  tf_en_motion_length: 3

  # transformer decoder
  tf_de_dim: 258
  tf_de_heads: 6
  tf_de_layers: 4
  tf_de_dropout: 0.05
  tf_de_tgt_dim: 15