Lane Detection

This is a project for detecting lane in a road.

Read this before you start

This repo does not contains training, as it only used for testing with pretrained model.

Please refer to the original library for the training, and use this library next for your testing in your real world application.

Supported

These are the supported model for lane detection.

• SCNN Lane Detection from Harry Han project.

How to install

1. Install the Library from here

   pip install laneDetection

2. Install the requirement for the library

   Refer to the latest requirements.txt

   pip install -r requirements.txt

Sample Code (Demo)

To see if the library loaded successful.

import SCNN_Lane_Detection as scnn_lane_detection
import cv2

Initialize SCNN pretrained weight which can be find here

scnn_lane_detection.init('.../vgg_SCNN_DULR_w9.pth')

Find road lane image and get the url. You can try this

url = 'https://i.ytimg.com/vi/szhG6iPJmE4/maxresdefault.jpg'
scnn_lane_detection.predictThreshold(0.05)
img, lane_img = scnn_lane_detection.demo(url)

Here you can see the lane_img with

cv2.imshow("Lane Image", lane_img)
cv2.waitKey(0)

This is the Lane showed in different color which is shown below.

But if we need to combine them with our original picture to see if it fits can be done with

res = scnn_lane_detection.getAddWeight(img, lane_img)
cv2.imshow("Final Result", res)
cv2.waitKey(0)

Which can be seen here