Modular autonomous driving platform running on the CARLA simulator and real-world vehicles.
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Updated
Mar 24, 2023 - Python
Modular autonomous driving platform running on the CARLA simulator and real-world vehicles.
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.
Detect traffic lights and classify the state of them, then give the commands "go" or "stop".
Traffic light detection using deep learning with the YOLOv3 framework. PyTorch => YOLOv3
Entire Self-Driving Car Software Stack Tested on Real Vehicle
Module for detecting traffic lights in the CARLA autonomous driving simulator. Based on the YOLO v2 deep learning object detection model and implemented in keras, using the tensorflow backend.
traffic light recognition system for ADAS
Machine Learning Based Real-Time Traffic Light Alert on Your Car with Raspberrypi
Traffic Light Detection using the tensorflow object detection API
Autonomous Self-Driving Car Prototype - with automatic steering control, traffic sign recognition, traffic light detection and other object detection features.
A simple yet effective repo for object detection based on the FCOS architecture.
Traffic light detection
ROS-based code to control a real Self-Driving Car. Final project in Udacity's Self-Driving Car Engineer Nanodegree.
traffic-lights-detection-and-color-recognition-using-yolov8
Self driving car capstone project based on ROS and light-weight traffic light detection CNN model
Program a real Self-Driving Car by writing ROS nodes to implement core functionality of the autonomous vehicle system.
Detect traffic lights and classify the state of them, then give the commands "go" or "stop".
Here a transfer learning solution for traffic light detection is presented. It uses Mask Region-Based Convolutional Neural Network as it base.
Detect traffic lights and their locations from images using computer vision
OpenLendaのPythonでのONNX推論サンプル
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