onnx-Ultra-Fast-Lane-Detection-Inference

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

Source: https://www.flickr.com/photos/[email protected]/1475776461/

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

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