Curb Detection Using Hough Transform on Lidar Data
I've included sample data in /sample. I've not been able to include Lidar data
because of the Lidar file size/Github file size limit. See the section below Data to
see how to gather Lidar data.
-
Register and make account here: http://pugetsoundlidar.ess.washington.edu/lidardata/account.php
-
Data is here: download any one of the *.laz files http://pugetsoundlidar.ess.washington.edu/lidardata/restricted/las/pslc2016/KingCounty_Delivery_1/
.laz is compressed version of .las. You usually work with .las. Here’s how to go from .laz to .las:
-
Download this: https://rapidlasso.com/LAStools/
-
Go into that folder, then from there, in terminal, run ‘make’.
-
Then, go into /bin, then run the executable
laszip. It should open up a terminal: you can input a file path, and an output file path (.laz to .las) -
To visualize, here is a site that’s simple: http://lidarview.com/
- Clone the repo
$ git clone https://github.com/michaely1113/LidarCurbDetection.git
$ cd LidarCurbDetection
- Initialize and activate a virtualenv:
$ virtualenv -p python3 env
$ source env/bin/activate
- Install the dependencies:
$ pip install -r requirements.txt
- Run the main code:
$ python main.py
After the .jpg files are generated, you may need to manually crop them to remove the white space in order for the hough transform algorithms to work accurately.