Closed jdiazram closed 2 years ago
Thanks for the kind words. I have a notebook here demonstrating how to use my code to train a tiny NeRF model on the tiny_nerf_data.npz
file used by the original NeRF authors in their notebook here. The only differences from my run_tiny_nerf.ipynb
notebook are that:
1) I do not divide data["images"]
by 255 because the images have already been normalized to be between zero and one.
2) I calculate camera_distance
from the pose array, i.e., camera_distance = float(np.linalg.norm(data["poses"][0, :3, -1]))
.
3) I set t_n
, t_f
, and N_c
to 2.0, 6.0, and 64, respectively, to follow the choices used in the original NeRF authors' notebook above.
For the following test view from the original NeRF authors' notebook:
my notebook generated the following after 14,900 iterations (~45 minutes on a P100 GPU):
Hi, excellent work with this code of NeRF. I have a question, can I use the original dataset of NeRF or my own dataset using generate_nerf_dataset.py to create them?
thx