Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Decimating pointcloud to 8192 points #11

Open
sitagy opened this issue May 19, 2019 · 0 comments
Open

Decimating pointcloud to 8192 points #11

sitagy opened this issue May 19, 2019 · 0 comments

Comments

@sitagy
Copy link

sitagy commented May 19, 2019

Hello,
I have a pointcloud which about 40,000 points. Since I don't have labels in my data set. I am directly feeding my data to the model in predict.py.
pred_labels = predict_one_input(sess, ops, myData)
I am decimating the pointcloud randomly using tools like cloud compare. Because of random decimation, sometimes the segmentation works and some times it doesn't. Is there a better way to correctly pick points so that segmentation always works?

Thanks in advance

@sitagy sitagy changed the title All objects are recognized as wall! Decimating pointcloud to 8192 points May 21, 2019
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant