CSC490H1: Making Your Self-driving Car Perceive the World

This repository contains the starter code for CSC490H1: We then filled functions required to detect cars from LIDAR Data, predict its trajectory five seconds into the future, and collect appropriate metrics and visualizations.

Getting started

1. Install Miniconda:

   curl 'https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh' > Miniconda.sh
   bash Miniconda.sh
   rm Miniconda.sh

2. Close and re-open your terminal session.

3. Change directories (cd) to where you cloned this repository.

4. Create a new conda environment:

   conda env create --file environment.yml

   To update the conda environment with new packages:

   conda env update --file environment.yml

5. Activate your new environment:

   conda activate csc490

6. Download PandaSet. After submitting your request to download the dataset, you will receive an email from Scale AI with instructions to download PandaSet in three parts. Download Part 1 only. After you have downloaded pandaset_0.zip, unzip the dataset as follows:

   unzip pandaset_0.zip -d <your_path_to_dataset>

7. To switch between the Gaussian and Regular Prediction model:

   1. Open /prediction/main.py
   2. In line 22, set MODEL=0 for regular, and MODEL=1 for Gaussian.