HyperParams fine tuning value

[abhigoku10]

@brian-h-wang hi i have few queries regarding the few hyperparams used Q1. for kitti dataset you have used calibrations matrix for projection of points , if for custom data i have no calibration file is there any way i can modify the modules Q2 To connect 3D points you use K-means which for kitti is 10 how did you come up with this param , did you use same value for both velodyne-64 and velodyne-16 Q3 To perform label diffusion you use either convergence or max iterations how to come up with this value Q4. Besides semi supervised graphnn did u try some other methods like dbscan, ecludiean clustering if so can you share that Q5 you had cited "“Fusion of images and point clouds for the semantic segmentation of large-scale 3D scenes based on deep learning,”" did you the refined segmentation mentioned

THanks a lot in advance