/Ultrafast-Lane-Detection-Inference-Pytorch-

Example scripts for the detection of lanes using the ultra fast lane detection model in Pytorch.

Primary LanguagePythonMIT LicenseMIT

Ultrafast Lane Detection Inference Pytorch

Example scripts for the detection of lanes using the ultra fast lane detection model in Pytorch.

!Ultra fast lane detection Source: https://www.flickr.com/photos/32413914@N00/1475776461/

Requirements

  • OpenCV, Scikit-learn and pytorch. pafy and youtube-dl are required for youtube video inference.

Installation

pip install -r requirements
pip install pafy youtube-dl

Pytorch: Check the Pytorch website to find the best method to install Pytorch in your computer.

Pretrained model

Download the pretrained model from the original repository and save it into the models folder.

Ultra fast lane detection - TuSimple(link)

  • Input: RGB image of size 1280 x 720 pixels.
  • Output: Keypoints for a maximum of 4 lanes (left-most lane, left lane, right lane, and right-most lane).

Examples

  • Image inference:
python imageLaneDetection.py
  • Webcam inference:
python webcamLaneDetection.py
  • Video inference:
python videoLaneDetection.py

Inference video Example

!Ultrafast lane detection on video

Original video: https://youtu.be/2CIxM7x-Clc (by Yunfei Guo)