onnx-Ultra-Fast-Lane-Detection-Inference

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

Pytorch inference

For performing the inference in Pytorch, check my other repository Ultrafast Lane Detection Inference Pytorch.

Requirements

  • OpenCV, scipy, onnx and onnxruntime. pafy and youtube-dl are required for youtube video inference.

Installation

pip install -r requirements.txt
pip install pafy youtube-dl

ONNX model

The original model was converted to different formats (including .onnx) by PINTO0309, download the models from his repository and save it into the models folder.

ONNX Conversion script: https://github.com/cfzd/Ultra-Fast-Lane-Detection/issues/218

Original Pytorch model

The pretrained Pytorch model was taken from the original repository.

Model info (link)

  • Input: RGB image of size 800 x 200 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)

GitHub

https://github.com/ibaiGorordo/onnx-Ultra-Fast-Lane-Detection-Inference