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README.md
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@@ -19,7 +19,6 @@ The models are all scaled to a unit sphere scale which is a normalised cubic sca
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The benefits to doing this is reduced file size and memory usage. Can be used to teach netural networks the shapes of objects to then be fed into a re-coloring network.
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**This is work-in-progress (WIP)** and I might not even finish it because the process is a little slow, the script I am using to convert the GLB files is a Blender script in Python that seems to leak memory in the second phase for some reason, you can check it out here: https://github.com/lzardy/glb_processing/blob/main/glb_to_ply.py
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Even if it didn't leak... It's really really slow.
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Refer to the original [AllenAI Objverse 1.0 dataset here](https://huggingface.co/datasets/allenai/objaverse) for the meta-data etc.
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The benefits to doing this is reduced file size and memory usage. Can be used to teach netural networks the shapes of objects to then be fed into a re-coloring network.
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**This is work-in-progress (WIP)** and I might not even finish it because the process is a little slow, the script I am using to convert the GLB files is a Blender script in Python that seems to leak memory in the second phase for some reason, you can check it out here: https://github.com/lzardy/glb_processing/blob/main/glb_to_ply.py
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_Even if it didn't leak... It's still really really slow._
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Refer to the original [AllenAI Objverse 1.0 dataset here](https://huggingface.co/datasets/allenai/objaverse) for the meta-data etc.
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