Download nuScenes dataset and organize it as follows:

# Inside FMF_ws
└── FMF
       └── data    
              └── nuScenes 
                     ├── samples       <-- key frames
                     ├── sweeps        <-- frames without annotation
                     ├── maps          <-- unused
                     |── v1.0-trainval <-- metadata and annotations
                     |── infos_train_10sweeps_withvelo_filter_True.pkl <-- train annotations (after data preparation)
                     |── infos_val_10sweeps_withvelo_filter_True.pkl <-- val annotations     (after data preparation)
                     |── dbinfos_train_10sweeps_withvelo.pkl <-- GT database info files      (after data preparation)
                     |── gt_database_10sweeps_withvelo <-- GT database                       (after data preparation)
                     └── v1.0-test <-- main test folder 
                            ├── samples       <-- key frames
                            ├── sweeps        <-- frames without annotation
                            ├── maps          <-- unused
                            |── v1.0-test <-- metadata and annotations
                            |── infos_test_10sweeps_withvelo.pkl <-- test info               (after data preparation)

Prepare dataset

python3 tools/create_data.py nuscenes_data_prep --root_path=/home/trainer/fmf/FMF/data/nuScenes --version="v1.0-trainval" --nsweeps=10

export PYTHONPATH="${PYTHONPATH}:/home/trainer/fmf/FMF"
export PYTHONPATH="${PYTHONPATH}:/home/trainer/fmf/nuscenes-devkit/python-sdk"

FMF-PointPillars-Base training:

python3 tools/train.py /home/trainer/fmf/FMF/configs/nusc/pp/nusc_centerpoint_pp_02voxel_two_pfn_10sweep_no_neck.py --work_dir nusc_exp/CP-PP-No-Neck 

FMF-PointPillars-Base validation:

Set the Batch_Size = 1 in pointpillars.py file and run this command in terminal:

python3 tools/dist_test.py /home/trainer/fmf/FMF/configs/nusc/pp/nusc_centerpoint_pp_02voxel_two_pfn_10sweep_no_neck.py --work_dir nusc_exp/CP-PointPillars-No-Neck  --checkpoint nusc_exp/CP-PointPillars-No-Neck/epoch_20.pth  --speed_test --gpus 1

FMF-PointPillars-Base test:

python3 tools/dist_test.py /home/trainer/fmf/FMF/configs/nusc/pp/fmf_pp_cat_shared_conv.py --work_dir working_dir/FMF-PointPillars-Base \
  --checkpoint models/pp_20.pth  --speed_test --testset --gpus 1

FMF-PointPillars-Base tracking:

python3 tools/nusc_tracking/pub_test.py --work_dir working_dir/FMF-PointPillars-Base \
 --checkpoint working_dir/FMF-PointPillars-Base/infos_test_10sweeps_withvelo.json  --max_age 3 --version v1.0-test

FMF-VoxelNet-Base training:

python3 tools/train.py /home/trainer/fmf/FMF/configs/nusc/voxelnet/nusc_fmf_voxelnet_0075voxel_fix_bn_z_no_neck.py --work_dir nusc_exp/CP-VoxelNet-No-Neck #--resume_from  working_dir/FMF-VoxelNet-Base/vn_20.pth

FMF-VoxelNet-Base validation:

Set the Batch_Size = 1 in voxelnet.py file and run this command in terminal:

python3 tools/dist_test.py /home/trainer/fmf/FMF/configs/nusc/voxelnet/nusc_fmf_voxelnet_cat_shrared_conv.py --work_dir working_dir/FMF-VoxelNet-Base \
  --checkpoint models/vn_20.pth  --speed_test --gpus 1

FMF-VoxelNet-Base test:

python3 tools/dist_test.py /home/trainer/fmf/FMF/configs/nusc/voxelnet/nusc_fmf_voxelnet_cat_shrared_conv.py --work_dir working_dir/FMF-VoxelNet-Base \
  --checkpoint models/vn_20.pth  --speed_test --testset --gpus 1

FMF-VoxelNet-Base tracking:

python3 tools/nusc_tracking/pub_test.py --work_dir working_dir/FMF-VoxelNet-Base \
 --checkpoint working_dir/FMF-VoxelNet-Base/infos_test_10sweeps_withvelo.json  --max_age 3 --version v1.0-test  

For distributed training

export CUDA_VISIBLE_DEVICES='0,1,2,3' # specify the GPU devices numbers for training
export num_gpus=4 # the number of used GPU devices

FMF-PointPillars-Base

python3 -m torch.distributed.launch --nproc_per_node=2 ./tools/train.py  /home/trainer/fmf/FMF/configs/nusc/pp/nusc_centerpoint_pp_02voxel_two_pfn_10sweep_no_neck.py \
 --work_dir nusc_exp/CP-PP-No-Neck  --resume_from models/pp_20.pth

FMF-VoxelNet-Base

python3 -m torch.distributed.launch --nproc_per_node=4 ./tools/train.py  /home/trainer/fmf/FMF/configs/nusc/voxelnet/nusc_fmf_voxelnet_cat_shrared_conv.py \
 --work_dir working_dir/FMF-VoxelNet-Base --resume_from models/vn_20.pth