Multimodal driving-state modeling code with a public synthetic sample dataset.
The original training data and model weights are not included because they are
private. The repository ships with data/sample/sample_train.pkl and
data/sample/sample_survey.csv, which are synthetic files that only match the
loader schema.
pip install -r requirements.txt
python main.py --profile sample --smokeWhen the private dataset exists at data/data/train/train_ver2.pkl, python main.py uses the full profile automatically. In a public clone without that
file, the code falls back to the sample profile and runs the smoke check.
Runtime paths are resolved from the repository root, so the command works even when invoked from another current working directory.
Use environment variables if local private files live outside the repository:
MUST_PROFILE=full \
MUST_PKL_ALL=/path/to/train_ver2.pkl \
MUST_SURVEY_CSV=/path/to/survey.csv \
python main.pyOptional pretrained checkpoint overrides:
MUST_EMOTION_CKPT=/path/to/best_emotion.pt \
MUST_MOTION_CKPT=/path/to/best_motion.pt \
python main.py --profile fullpython scripts/create_sample_data.py