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elchun / lndf_robot

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Occupancy ground truth data generation - question #1

Closed aprath1 closed 1 year ago

aprath1 commented 1 year ago

Could you please share how you are generating occupancy ground truths for the point cloud data generated with the 'shapenet_pcd_gen.py' ? The file only generates point cloud using pybullet simulation and I was wondering for these point clouds, how you have generated the occupancy ground truths. Is it possible to integrate it in the same (shapenet_pcd_gen) pipeline?

Thanks

elchun commented 1 year ago

Hi @aprath1, Thanks for the question. Please see this issue from the Neural Descriptor Fields repo: https://github.com/anthonysimeonov/ndf_robot/issues/10. This portion of the codebase is very similar to ours. I believe you can voxelize the meshes and sample within the bounding box of the objects. Then use importance sampling to balance the number of positive and negative samples.

aprath1 commented 1 year ago

Ok, Thank you for your response, will try it out.