LIU42/LaneDetection

基于网格级图像分割的车道线检测模型。

26
/ 100
Experimental

This project helps self-driving car developers and researchers create or improve systems that can accurately identify lane lines from camera images. It takes raw road images as input and outputs a grid-level prediction of where lane lines are, simplifying the visual information for navigation systems. This tool is for engineers building autonomous vehicle perception systems or related intelligent transportation solutions.

No commits in the last 6 months.

Use this if you need a lane detection model that balances accuracy with reduced computational load, particularly for integrating into an autonomous driving system.

Not ideal if you need a general-purpose image segmentation model for non-road-related tasks or require extremely high pixel-level precision beyond grid-level predictions.

autonomous-driving computer-vision vehicle-perception intelligent-transportation road-safety
No License Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 5 / 25
Maturity 8 / 25
Community 11 / 25

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Stars

13

Forks

2

Language

Python

License

Last pushed

Aug 27, 2025

Commits (30d)

0

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