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PyTorch's implementation of the paper "End to End Learning for Self-Driving Cars"

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PyTorch's implementation of the paper "End to End Learning for Self-Driving Cars"

Introduction

This is the PyTorch implementation of the paper "End to End Learning for Self-Driving Cars" by NVIDIA. The paper can be found here.

This code is based on the original implementation by Pankaj Karki. The original implementation is in TensorFlow.

Conda requirements

To install the conda environment, run the following command: conda install pytorch torchvision torchaudio -c pytorch.

Dataset

The dataset used in this project is the Dataset from Sully Chen. It has a size of 2.3GB approximately.

Training

To train the model, run the following command: python train.py.

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PyTorch's implementation of the paper "End to End Learning for Self-Driving Cars"

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