I am trying the point cloud simplifier on a point cloud with 11 million points, but it is taking a very long time . It hasn't finished yet and it looks like it could take days to finish. Is it possible to speed up the transformer based on the parameter values?
Question
Is there a way to speed up the point cloud simplifier?
This post is closed to further activity.
It may be an old question, an answered question, an implemented idea, or a notification-only post.
Please check post dates before relying on any information in a question or answer.
For follow-up or related questions, please post a new question or idea.
If there is a genuine update to be made, please contact us and request that the post is reopened.
It may be an old question, an answered question, an implemented idea, or a notification-only post.
Please check post dates before relying on any information in a question or answer.
For follow-up or related questions, please post a new question or idea.
If there is a genuine update to be made, please contact us and request that the post is reopened.
+62- Celebrity
Whether it would actually speed up processing is hard to say but the filter ratio is one likely suspect to play with.
Depending on how accurate you want the result to be you could also try the PointCloudThinner, that will simply filter the point cloud without trying to preserve the shape. The downside of that is that you are of course introducing small errors in your data.
Thanks for the suggestion, but I had tried that already and it didn't seem to make a difference. I'm reverting back to the PointCloudSurfaceGeneralizer for the moment to do simplification.
+62- Celebrity
I just tried wrapping it in a custom transformer so it can do Parallel Processing, there is a few % performance gain that way (which might be higher if done on a machine with more cores, mine only has 4).
In order to make that work I used a Tiler to cut the point cloud into 4 parts.
One thing to keep in mind is that this may result in visible seams being introduced in your final result because each part is processed completely seperate from the others.