BEVNet

Datasets

Datasets should be put inside data/. For example, data/semantic_kitti_4class_100x100.

Training

BEVNet-S

Example:

cd experiments
bash train_kitti4-unknown_single.sh kitti4_100/single/include_unknown/default.yaml 
   
     arg1 arg2 ...

   

Logs and model weights will be stored in a subdirectory of the config file like this: experiments/kitti4_100/single/include_unknown/default- -logs/

• is useful when you want to use the same config file but different hyperparameters. For example, if you want to do some debugging you can use set to debug.
• arg1 arg2 ... are command line arguments supported by train_single.py. For example, you can pass --batch_size=4 --log_interval=100, etc.

BEVNet-R

The command line formats are the same as BEVNet-S Example:

cd experiments
bash train_kitti4-unknown_recurrent.sh kitti4_100/recurrent/include_unknown/default.yaml 
   
     \
--n_frame=6 --seq_len=20 --frame_strides 1 10 20 \
--resume kitti4_100/single/include_unknown/default-logs/model.pth.4 \
--resume_epoch 0

   

Logs and model weights will be stored in a subdirectory of the config file experiments/kitti4_100/recurrent/include_unknown/default- -logs/ .