ROS-based code to control a real Self-Driving Car. Final project in Udacity's Self-Driving Car Engineer Nanodegree.
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Updated
Dec 31, 2017 - Python
ROS-based code to control a real Self-Driving Car. Final project in Udacity's Self-Driving Car Engineer Nanodegree.
Final project of the Udacity Self-Driving Car Nanodegree
A detailed tutorial on how to build a traffic light classifier with TensorFlow for the capstone project of Udacity's Self-Driving Car Engineer Nanodegree Program.
SURVIVE is a system that deters and helps punish red light violations. This is the software part of our prototype (hardware-sensors) as long as some algorithms to detect cars using only CV (Computer Vision)
Lane detection and Traffic light detection, for Ohio University PAVE student organization
Entire Self-Driving Car Software Stack Tested on Real Vehicle
Self driving car capstone project based on ROS and light-weight traffic light detection CNN model
This is the final project in Udacity's Self-Driving Car Engineer Nanodegree where we will implement ROS nodes to control Carla - Udacity's self-driving car.
Traffic Light Detection using the tensorflow object detection API
Traffic light detection
Detect traffic lights and classify the state of them, then give the commands "go" or "stop".
Detect traffic lights and their locations from images using computer vision
Traffic light detection using deep learning with the YOLOv3 framework. PyTorch => YOLOv3
Capstone Project : In this project, we implement a Real Self Driving Car in python to maneuver the vehicle around the track while following the traffic rules.
Final Project of the Udacity Self-Driving Car Engineer Nanodegree with the goal to develop a an architecture and its underlying components to steer a vehicle autonomously through a full physics simulation environment.
Here a transfer learning solution for traffic light detection is presented. It uses Mask Region-Based Convolutional Neural Network as it base.
Program a real Self-Driving Car by writing ROS nodes to implement core functionality of the autonomous vehicle system.
traffic light recognition system for ADAS
A self-driving car prototype built using a Raspberry Pi and remote-control car with end-to-end steering prediction, traffic light detection, and obstacle avoidance.
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