How to run on custom datasets?
Hi, I am trying to run NMF on my own datasets. My dataset format is dtu or neus, for which I write a new dataloader. But I notice the rendered results except the images of the last index are just blank with vis_every=500. I tried to tune the near_far but did not work.
Are any advice for custom datasets? For example, the scale of the scene? the size of the bounding box of the poses?
I have a similar issue with my real segmented datasets. I first convert the datasets from LLFF to blender format scripts/llff2nerf.py and then train them as with other blender datasets but the metrics and reconstruction are really bad. I still haven't figured out what goes wrong.
Try tuning the starting density. Is the PSNR going up?
Try tuning the starting density. Is the PSNR going up?
Hi, thanks for your advice. Which yaml file should I use for tuning the starting density? Multiple yaml files have density setting.
This one. The one shown in the readme. https://github.com/half-potato/nmf/blob/main/configs/model/microfacet_tensorf2.yaml