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This is a major project that was completed under the course Deep Learning(CSE674) at University at Buffalo.

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Self-Driving-Car

DISCLAIMER

This project is purely for knowledge purpose. It should not be used for any real-life training model for autonomous vehicles.

Description

It is a supervised regression problem between the steering angles and the road images in front of a car. The network is based on The NVIDIA model.

Files Included

  • IMG folder - Training and testing data set images
  • drivinglog.csv - comma seperated values of the dataset
  • train_model.ipynb - Model build to train the the car referencing NVIDIA model
  • test.py - test the model ona new environment using Anaconda and Unity.
  • model.h5 - saved trained model
  • environment.yml - Specifying all the requirements
  • Final Report

How to run the model

You will need anaconda to run the model.

Creating an environment in Anaconda

conda env create -f environment.yml

running the pre-trained model

python test.py model.h5

To train the model

python train_model.ipynb

To understand the the model architecture in detail go through the Final-Report

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This is a major project that was completed under the course Deep Learning(CSE674) at University at Buffalo.

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