Training

This project should contain all our training code for the model car project. For instructions on contributing, please see CONTRIBUTING.md

Workflow

Explanation of directory structure:

training
|- configs      > configuration files to easily manage training/validation hyperparameters
|- logs         > log files for debugging
|- nets         > all pytorch neural network models stored here
|- preprocess   > scripts for preprocessing video data into h5py files
|- save         > default save location for all nets

If you wish to run a new experiment, please add your config.json file into the configs folder. See configs/CONFIGS.md for a detailed explanation of how to structure your configuration file. To run your experiment, simply use the command line command bdd-docker python Train.py --config <config filepath>.

If you wish to add a new network, please add your network to the nets folder. Set a variable Net to point to your class so the training script can automatically find your network.

Standards

This is a version of the repository that follows PEP8 guidelines, please comment on GitHub code, file an issue, or correct any errors with a pull request.