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LiDAR point cloud segmentation with classic ML approaches.

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lidar_pcl_features

LiDAR point cloud segmentation with classic ML approaches.

Config: Hydra

Getting started

  1. Follow instructions to install Poetry:
    # Unix/MacOs installation
    curl -sSL https://install.python-poetry.org | python3 -
  2. Check that poetry was installed successfully:
    poetry --version
  3. Setup workspace:
    make setup_ws
  4. Setup ClearML:
    clearml-init
  5. Migrate dataset to your ClearML workspace:
    make migrate_dataset
  6. (Optional) Configure and run Jupyter lab:
    make jupyterlab_start

Train

make run_training

Results

🧪 Experiment link

              precision    recall  f1-score
           0       0.52      0.73      0.61
           1       0.99      0.85      0.91
           2       0.35      0.50      0.41
           3       0.89      0.94      0.91
           4       0.45      0.25      0.32
    accuracy                           0.82
   macro avg       0.64      0.65      0.63
weighted avg       0.83      0.82      0.82

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LiDAR point cloud segmentation with classic ML approaches.

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