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View Code? Open in Web Editor NEWA minimal re-implementation of Neural Radiance Fields (NeRF)
A minimal re-implementation of Neural Radiance Fields (NeRF)
We don't got no requirements.txt. Use this:
pip install pipreqs
pipreqs /path/to/project
I mean, how bomb would it be if I can render a new NeRF!! No Face here I come :333
From a cursory glance, it seems that an RGBA image is read as an RGB image. Seems problematic.
honestly, kind of stumped on this one, should I just plot everything using plotly?
reconstruct one image at a time and put them together to create a gif?
Not sure, but a few options I suppose
How about we implement a simple sampling scheme based on alpha values (from the original image) and use that to help training stabilize instead? Not research worthy but could be interesting enough for a class project. Then we can also do away with this stupid cropping bullshit i implemented too.
When sampling for coarse and fine network, we sample coarse_ts and fine_ts. When concatenating the two, we have to sort the ts to be in the right order so that the calculated deltas make sense. However, sorting the ts can mess with the order of the density and rgbs. What to do what to do.
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