issue at raymarching about nerfacc HOT 7 CLOSED

the above issue is resolved, It's working now,

Just one more thing -

the aabb argument that has to be specified in OccupancyGrid(roi_aabb = aabb) is the same as that in ray_marching(scene_aabb=aabb) ?

from nerfacc.

They can be the same but not necessary to be.

If you have a scene bounded by a bbox, it is recommended to set them to the same.

If you want to use the contraction for the occupancy grid to cover an infinity space, e.g., OccupancyGrid(..., contraction_type=ContractionType.UN_BOUNDED_SPHERE), then the roi_aabb is the region of interest in the infinity space. In this case you shouldn't set the scene_aabb to ray_marching, as it will only march inside this bounding box

from nerfacc.

Understood thank you !

I just wanted to know , when performing testing , I wonder how the python api commands provided are to be used .

Because in the training part I use occupancy grid in the raymarching() function . And since it gets updated every time, so I am a bit confused about how to test the model once I have save the weights ?

from nerfacc.

Same way as you do the training — use the occupancy grid as well.

That means you would want to save both your network and the occupancy grid, and reload them when testing

from nerfacc.

Oh okay , I did get your point.
Saving occupancy grid using torch.save() .?

from nerfacc.

yeah the occupancy grid is a torch.nn.Module so you can save it in the same way you do with network.

from nerfacc.

Closed as the problems seem to be all resolved. Feel free to reopen it if not.

from nerfacc.