nmhaddad/semantic-segmentation
Off-Road Perception with DeepLabV3+
This project helps autonomous off-road vehicles like rovers or drones understand their surroundings by identifying different elements in images and videos. It takes raw off-road footage as input and outputs segmented images where each pixel is labeled, distinguishing elements like terrain, obstacles, or vegetation. This is for engineers and researchers developing perception systems for robotics in challenging outdoor environments.
No commits in the last 6 months.
Use this if you need to accurately identify and classify objects within images or videos captured in rugged, off-road settings for autonomous navigation or environmental analysis.
Not ideal if your primary use case involves urban environments, standard road scenes, or if you need object detection with bounding boxes rather than pixel-level segmentation.
Stars
37
Forks
7
Language
Python
License
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Category
Last pushed
Jul 22, 2025
Commits (30d)
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