dual cross attention RGB image and LiDAR sensor fusion model for AV perception in snow
- Generate a concatenated matrix of RGB images and LiDAR data, as well as the corresponding labels by running the data_load.py
- Generate patches by running the data_prepare.py
- Augment the patches by running the data_augmentation.py
- Update file paths in model.py according to the saved locations of the patch sets and groundtruth labels
- Confirm that file path locations in model.py are correct
- Run model.py or run Colab notebook
- Code to visualize model predictions per sample image available in last cell of Colab notebook