Skip to content

Latest commit

 

History

History
44 lines (34 loc) · 1.51 KB

GETTING_STARTED.md

File metadata and controls

44 lines (34 loc) · 1.51 KB

Getting Started

The dataset configs are located within tools/cfgs/dataset_configs, and the model configs are located within tools/cfgs for different datasets, like tools/cfgs/kitti_models/.

Test and evaluate the pretrained models

  • Test with a pretrained model:
python test.py --cfg_file ${CONFIG_FILE} --batch_size ${BATCH_SIZE} --ckpt ${CKPT}
  • To test all the saved checkpoints of a specific training setting and draw the performance curve on the Tensorboard, add the --eval_all argument:
python test.py --cfg_file ${CONFIG_FILE} --batch_size ${BATCH_SIZE} --eval_all
  • To test with multiple GPUs:
sh scripts/slurm_test_mgpu.sh ${PARTITION} ${NUM_GPUS} \ 
    --cfg_file ${CONFIG_FILE} --batch_size ${BATCH_SIZE}

Train a model

Note that the --batch_size depends on the number of your training GPUs, please refer to Model Zoo of README.md for the setting of batch_size for different models.

  • Train with multiple GPUs:
sh scripts/dist_train.sh ${NUM_GPUS} \ 
    --cfg_file ${CONFIG_FILE} --batch_size ${BATCH_SIZE}  --epochs 80
  • Train with multiple machines:
sh scripts/slurm_train.sh ${PARTITION} ${JOB_NAME} ${NUM_GPUS} \ 
    --cfg_file ${CONFIG_FILE} --batch_size ${BATCH_SIZE} --epochs 80
  • Train with a single GPU:
python train.py --cfg_file ${CONFIG_FILE} --batch_size ${BATCH_SIZE} --epochs 50