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drprojects avatar drprojects commented on June 12, 2024

The configs system is built so that hydra dynamically parses the configs and adapts the model input size according to the chosen features. Besides, it is also possible to pick from a list of supported features to be used for superpoint partition or as input pointwise features at training time.

In invite you to have a look at the configs for the different provided datasets, some have RGB, some have lidar intensity. Besides, you want to have a close look at how the partition_hf and point_hf are used in the configs and in the project, to understand the data pipeline.

If you want to create new point-wise attributes beyond the ones we support with configs/datamodule/semantic/_features.yaml, you can. To this end, you will specify the name and dimensions of these new point attributes in this file. And if they need som careful preprocessing, you may need to build dedicated Transform operations. You will need to dive deeper into the transforms of the existing datasets to see if what you need is not already here. But everything is thoroughly commented across the project, so you should be able to read though the code.

from superpoint_transformer.

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