drprojects / superpoint_transformer

Official PyTorch implementation of Superpoint Transformer introduced in [ICCV'23] "Efficient 3D Semantic Segmentation with Superpoint Transformer" and SuperCluster introduced in [3DV'24 Oral] "Scalable 3D Panoptic Segmentation As Superpoint Graph Clustering"
MIT License
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Inference on a single unlabeled .ply file #93

Closed faridht closed 3 months ago

faridht commented 3 months ago

Hello! Thank you so much for this project!

I managed to go through the model retraining and evaluation (using the notebook demo). Presently however, I am trying to see the output of inference on a single unlabeled .ply file.

May you kindly advise on how this can be achieved? I tried to look into the docs and some issues, and it seems to me that the only way is through creating custom dataset files (Maybe I am misunderstanding or missing something).

Thank you very much in advance!

drprojects commented 3 months ago

Hello @faridht,

Normally you should be able to find what you need for running the inference on a cloud in notebooks/demo.ipynb. This notebook shows how to run a forward pass on a NAG and visualize it with our tool.

Yet, since preparing a NAG for inference requires some preprocessing, you indeed should implement dedicated classes inheriting from BaseDataset and BaseDatamodule for your new data. If you have only one cloud tile in your dataset, this may sound overkill, but this is the cleanest, foolproof way of accessing all the features of this codebase.

A workaround would be that you manually instantiate and run the series of Transform for processing your raw data into a proper NAG for inference, and then run a forward pass on the model. These would be the ones you would otherwise find in your dataset's config file: