daavoo / daavoo/pyntcloud

Processing models with large number of voxels

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Feature Request
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Python
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Description

I am trying to process large models using small voxels and I usually have memory problems. I guess there are two things that can be done to improve this.

1. Using Minimum Volume Bounding Box to align the voxels model with input data, and have less empty voxels.
![model](https://user-images.githubusercontent.com/21697551/51504361-b5476b00-1e34-11e9-9711-8ee248c4f39d.png)
This will reduce to some extend the problem.

2. Create patch-based voxel system, where the model would be subdivided in many smaller same size voxel models. For example, 32x32x32 size patches which relative position are known compared to the other patches. You can store the patches in some files externally, and use them when you need. This would enable to create a lot of voxels.

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