You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
In the function get_generator() in file src/conv_onet/config.py, the parameters are initialized as: recep_field=2**(cfg['model']['encoder_kwargs']['unet3d_kwargs']['num_levels'] + 2), grid_reso = 25 + recep_field - 1, query_vol_size = 25 * unit_size.
Why the reception field is calculated like this? Where does the 25 comes from? In my understanding, query_vol_size and input_vol_size define the size of space that each prediction will be operated in but their relationship with the reception field and 25 is unclear.
Also, is unit_size's physical meaning removed since the queried result points are sampled on a 3D grid with interval (query_crop_size/nx<--25*unit_size/self.resolution0)? (in config/pointcloud_crop/demo_matterport.yaml, a comment says that unit_size define the size of a voxel, in meter)