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Lane Detection for CCTV-cameras using CLRNet: Cross Layer Refinement Network

License: Apache License 2.0

C++ 0.86% Python 96.75% Cuda 2.39%

etss-03-lanedet's Introduction

Automation Lab, Sungkyunkwan University

Lane Detection for CCTV-cameras using CLRNet: Cross-Layer Refinement Network

Prepare for an updated version, include:

Background subtraction module
Segment Anything module -> Generate Lane segments
Yolov8 model -> detect vehicles
Overall Process

Introduction

~~- Lane Detection method for CCTV-cameras using Yolov8 + SegmentAnything + ByteTrack~~

Lane Detection method for CCTV-cameras using RTM + Norfair + SegmentAnything + Adaptive HoughR

Installation

Update soon

Getting Started

Results

Reproduce results using F1 score metric.

Backbone	CULane	Tusimple
CLRNet-Resnet18 / CLRNet-Resnet18*	79.58 / 79.49	97.89 / 97.82
CLRNet-Resnet34 / CLRNet-Resnet34*	79.73 / 79.44	97.82 / 97.97
CLRNet-Resnet101 / CLRNet-Resnet101*	80.13 / 79.92	97.62 / 97.71
'*' method is the reproduced results.

'F1@50' refers to the official metric, i.e., F1 score when IoU threshold is 0.5 between the gt and prediction. 'F1@75' is the F1 score when IoU threshold is 0.75.

CCTV-Camera Visualization

Acknowledgement

etss-03-lanedet's People

Contributors

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