engynzss / end-to-end-learning-for-self-driving-cars

Build a self driving car using deep reinforcement learning.

End-to-End-Learning-for-Self-Driving-Cars

This code helps in getting the steering angle of self driving car. The inspiraion is taken from Udacity Self driving car module as well End to End Learning for Self-Driving Cars module from NVIDIA.

The End to End Learning for Self-Driving Cars research paper can be found at (https://arxiv.org/abs/1604.07316) This repository uses CNNs to predict steering angle of the car according to the different roads.

1. Implementation 1
2. Implementation 2

Code Requirements

pip install requirements.txt

Dataset

You can download the dataset from here for Implementation 1.
You can download the dataset and extract into the repository folder from here for Implementation 2.

Python Implementation

1. Network Used- Convolutional Neural Network(CNN)
2. Keras-Tensorflow Architecture

Procedure in Implementation 1

1. First use python LoadData.py which will get dataset from folder and store it in a pickle file.
2. Now you need to have the data, use python TrainModel.py which will load data from pickle and augment it. After this, the training process begins.
3. For testing it on the video you need to use python DriveApp.py

Procedure in Implementation 2

1. Use python train.py to train the model.
2. Use python run.py to run the model on a live webcam feed.
3. Use python run_dataset.py to run the model on the dataset

References and Credits:

1. This implementation is inspired by Akshay Bahadur's project
2. This implementation also took a lot of inspiration from the Sully Chen's work.