davidbrai/deep-learning-traffic-lights
Code and files of the deep learning model used to win the Nexar Traffic Light Recognition challenge
This project helps self-driving car engineers and researchers accurately identify the state of traffic lights from dashcam images. It takes raw image data as input and outputs a classification of the traffic light's state (e.g., red, yellow, green), enabling reliable decision-making for autonomous vehicles. The primary users are those developing or testing autonomous driving systems.
483 stars. No commits in the last 6 months.
Use this if you need a robust deep learning model to classify traffic light states from vehicle camera feeds for autonomous driving applications.
Not ideal if you are looking for a general object detection model or if you don't have access to the Caffe deep learning framework.
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483
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160
Language
Jupyter Notebook
License
BSD-2-Clause
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Last pushed
Apr 19, 2017
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