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tutorial_detection_3d.md

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1. Setup environment

See tutorial_installation to set up the environment.

2. Train and evaluation

In this tutorial, we use CenterPoint. If you want to know the tools in detail, please see detection3d and CenterPoint.

2.1. Prepare T4dataset

  • Run docker
docker run -it --rm --gpus '"device=0"' --shm-size=64g --name awml -p 6006:6006 -v $PWD/:/workspace -v $PWD/data:/workspace/data autoware-ml
  • (Choice) Make info files for T4dataset XX1
    • This process takes time.
python tools/detection3d/create_data_t4dataset.py --root_path ./data/t4dataset --config autoware_ml/configs/detection3d/dataset/t4dataset/xx1.py --version xx1 --max_sweeps 2 --out_dir ./data/t4dataset/info/user_name
  • (Choice) Make info files for T4dataset X2
    • This process takes time.
python tools/detection3d/create_data_t4dataset.py --root_path ./data/t4dataset --config autoware_ml/configs/detection3d/dataset/t4dataset/x2.py --version x2 --max_sweeps 2 --out_dir ./data/t4dataset/info/user_name

2.2. Train

python tools/detection3d/train.py projects/CenterPoint/configs/t4dataset/second_secfpn_2xb8_121m_base.py

2.3. Evaluation

python tools/detection3d/test.py projects/CenterPoint/configs/t4dataset/second_secfpn_2xb8_121m_base.py work_dirs/centerpoint/t4dataset/second_secfpn_2xb8_121m_base/epoch_50.pth

2.4. Visualization

  • frame-range: the range of frames to visualize.
python projects/CenterPoint/scripts/inference.py projects/CenterPoint/configs/t4dataset/second_secfpn_2xb8_121m_base.py work_dirs/centerpoint/t4dataset/second_secfpn_2xb8_121m_base/epoch_50.pth --ann-file-path <info pickle file> --bboxes-score-threshold 0.35 --frame-range 700 1100

2.5. Deploy the ONNX file

python projects/CenterPoint/scripts/deploy.py projects/CenterPoint/configs/t4dataset/second_secfpn_2xb8_121m_base.py work_dirs/centerpoint/t4dataset/second_secfpn_2xb8_121m_base/epoch_50.pth --replace_onnx_models --device gpu --rot_y_axis_reference

Tips for developer

Build docker on your own

  • Build docker
    • Note that this process need for long time.
    • You may need sudo to use docker command.
DOCKER_BUILDKIT=1 docker build -t autoware-ml .