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)
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"
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
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
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
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
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
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
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
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
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
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
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