Self Driving Car Algorithm
kazi haque
Kolkata, West Bengal
- 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
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 RequirementsYou can install Conda for python which resolves all the dependencies for machine learning.
pip install requirements.txt DescriptionAn 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) DatasetDownload the dataset at here and extract into the repository folder
Python Implementation- Network Used- Convolutional Network
- Inspiration - End to End Learning for Self-Driving Cars by Nvidia
If you face any problem, kindly raise an issue
Procedure- First, run
LoadData_V2.py
which will get dataset from folder and store it in a pickle file after preprocessing. - Now you need to have the data, run
Train_pilot.py
which will load data from pickle. After this, the training process begins. - 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 RequirementsYou can install Conda for python which resolves all the dependencies for machine learning.
pip install requirements.txt DescriptionAn 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) DatasetDownload the dataset at here and extract into the repository folder
Python Implementation- Network Used- Convolutional Network
- Inspiration - End to End Learning for Self-Driving Cars by Nvidia
If you face any problem, kindly raise an issue
Procedure- First, run
LoadData_V2.py
which will get dataset from folder and store it in a pickle file after preprocessing. - Now you need to have the data, run
Train_pilot.py
which will load data from pickle. After this, the training process begins. - For testing it on the video, run
SDCA.py
Technologies Used
Intel Optimized python
numpy
matplotlib
cv2
keras
h5py
scipy
tensorflow