NikolasEnt/Road-Semantic-Segmentation
Udacity Self-Driving Car Engineer Nanodegree. Project: Road Semantic Segmentation
This project helps self-driving car engineers and researchers train artificial intelligence to precisely identify road surfaces and other vehicle types from front-facing camera videos. It takes raw video frames as input and produces an output where each pixel is labeled as either road, background, or other vehicle classes, enabling autonomous navigation systems to understand their environment. This tool is for engineers building and testing self-driving car perception systems.
No commits in the last 6 months.
Use this if you need to train a semantic segmentation model for self-driving cars to accurately detect roads and vehicles in diverse lighting conditions.
Not ideal if you're looking for a pre-trained model ready for immediate deployment without additional training or dataset preparation.
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Last pushed
Dec 28, 2017
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