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.. _training:
Training models
===============
.. _training_pointcloud_classification:
Traning point cloud classification
----------------------------------
Collect point cloud dataset as describe in :ref:`3d_dataset_collection`, and
preprocess them as explained in :ref:`3d_dataset_preprocessing`.
To train the models, you need to clone `this repo <https://github.com/mhwasil/pointcloud_classification>`_, and
install the requirements to train the model.
Training deep learning model
^^^^^^^^^^^^^^^^^^^^^^^^^^^^
The supported models are available under `config/config.yaml`.
.. code-block:: bash
#python trainer.py --model <model_name> --train
#an example for training DGCNN with color (DGCNNC)
python trainer.py --model DGCNNC --train
Adding new model
^^^^^^^^^^^^^^^^
ToDo
.. _training_2d_object_detection:
Training 2D object detection
----------------------------
ToDo
.. note::
You can train the model on `H-BRS Scientific Computing Cluster <https://wr0.wr.inf.h-brs.de/wr/index.html>`_,
provided that you have access to it. The tutorial on how to submit job and train
your model on the cluster can be found `here <https://github.com/mhwasil/pointcloud_classification/blob/master/hbrs_cluster_usage.md>`_. |