DEVELOPER STUDENT CLUBS TIET

Autonomous-Driving

This repository contains the code for steering a self-driving vehicle.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Installation and Setup

Fork the repo and clone it.

git clone https://github.com/developer-student-club-thapar/Autonomous-Driving.git

Go in the repo and setup virtual environment using python -m virtualenv env or by using anaconda
conda create --name env
Then activate the environment using source env/Scripts/activate (For Windows Users using CMD or Powershell env/Scripts/activate) or conda activate env
Then install the necessary required packages from requirements.txt

pip install -r requirements.txt

Running the demo

Run the following command :

python autolabeler.py --basedir "all" --datafile "angles.csv" --savefile "./output.csv"

basedir : Path to folder that dataset folder
datafile : Path to angles.csv
savefile : Path to store output.csv

Training the Neural Network

Make sure your dataset-images are in folder named 'all' at the root directory.
Make sure your angles.csv and actions.csv are in the root directory named 'angles.csv' and 'actions.csv' respectively.
The models.py contain architectures of 5-different neural networks named:
- comma.ai
- pretrained_vgg16
- nvidia-dave2
- 3D-CNN
- CNN LSTM
Run the following command :

python steering-model.py --model "model_name from above list"

For Example :

python steering-model.py --model "comma.ai"

NOTE : Use exact name as mentioned above to avoid unnecessary bugs.

LICENSE

This project is licensed under the MIT License - see the LICENSE.md file for details