Training data preparation not working

[blacktime14]

Hi, I have an issue regarding data preparation.
As you mentioned in Readme, I tried to prepare ShapeNetv2 dataset for training by using mesh_to_sdf.
I used get_surface_point_cloud and sample_sdf_near_surface function (like the captured image below), but the result was really different from your uploaded eval dataset.

Do I need to change detailed arguments for both functions to get the same results?

This is the given data from eval dataset, and

This is our failure version.

Thanks in advance.

[YuDeng]

Hi, sorry that the description of the data preparation part is not that clear.

We actually modified the original mesh_to_sdf library to get the data as in the eval dataset:

1. We normalized the object within a sphere with a radius of 1/1.03 instead of 1 as in the original mesh_to_sdf.
2. We directly sampled 500k points on the object surface as well as their normals instead of sampling points "near the surface".
3. We uniformly sampled 500k points within the cube of [-1,1]^3 instead of in the unit spherical space.
4. For all sampling points, we compute their sdf using the "scan" and "depth" method in the mesh_to_sdf library.

For more details, you can check the supplementary materials of our original paper. Hope it answers your question.