DevMesh

Self Driving Car Algorithm

kazi haque

kazi haque

Kolkata, West Bengal

1 0
  • 0 Collaborators

This code helps in getting the steering angle of self driving car. The inspiraion is taken from [Udacity Self driving car](https://github.com/udacity/CarND-Behavioral-Cloning-P3) module as well [End to End Learning for Self-Driving Cars](https://devblogs.nvidia.com/deep-learning-self-driving-cars/) module from NVIDIA ...learn more

Project status: Concept

Robotics, Internet of Things, Artificial Intelligence

Intel Technologies
Intel Opt ML/DL Framework, Intel Python

Code Samples [1]

Overview / Usage

his 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

Code Requirements

You can install Conda for python which resolves all the dependencies for machine learning.

pip install requirements.txt Description

An autonomous car (also known as a driverless car, self-driving car, and robotic car) is a vehicle that is capable of sensing its environment and navigating without human input. Autonomous cars combine a variety of techniques to perceive their surroundings, including radar, laser light, GPS, odometry, and computer vision. Advanced control systems interpret sensory information to identify appropriate navigation paths, as well as obstacles and relevant signage

SDCA V2 (NVIDIA Dataset based on real world) Dataset

Download the dataset at here and extract into the repository folder

Python Implementation
  1. Network Used- Convolutional Network
  2. Inspiration - End to End Learning for Self-Driving Cars by Nvidia

If you face any problem, kindly raise an issue

Procedure
  1. First, run LoadData_V2.py which will get dataset from folder and store it in a pickle file after preprocessing.
  2. Now you need to have the data, run Train_pilot.py which will load data from pickle. After this, the training process begins.
  3. For testing it on the video, run SDCA.py

Methodology / Approach

his 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

Code Requirements

You can install Conda for python which resolves all the dependencies for machine learning.

pip install requirements.txt Description

An autonomous car (also known as a driverless car, self-driving car, and robotic car) is a vehicle that is capable of sensing its environment and navigating without human input. Autonomous cars combine a variety of techniques to perceive their surroundings, including radar, laser light, GPS, odometry, and computer vision. Advanced control systems interpret sensory information to identify appropriate navigation paths, as well as obstacles and relevant signage

SDCA V2 (NVIDIA Dataset based on real world) Dataset

Download the dataset at here and extract into the repository folder

Python Implementation
  1. Network Used- Convolutional Network
  2. Inspiration - End to End Learning for Self-Driving Cars by Nvidia

If you face any problem, kindly raise an issue

Procedure
  1. First, run LoadData_V2.py which will get dataset from folder and store it in a pickle file after preprocessing.
  2. Now you need to have the data, run Train_pilot.py which will load data from pickle. After this, the training process begins.
  3. For testing it on the video, run SDCA.py

Technologies Used

Intel Optimized python
numpy
matplotlib
cv2
keras
h5py
scipy
tensorflow

Repository

https://github.com/kazi92/SelfDrivingCarAlgorithm

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