bmild / nerf

Code release for NeRF (Neural Radiance Fields)
http://tancik.com/nerf
MIT License
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Depth GT #107

Closed BingCS closed 3 years ago

BingCS commented 3 years ago

Hi, I just want to confirm that the depth images in the testing dataset of nerf_synthetic are the ground truth or not?

If they are ground truth, could you please also release the depth images for the training and validation datasets?

Many Thanks!

tancik commented 3 years ago

The depth images were rendered from blender. We never used them in the project so I can't vouch for their correctness (in fact they were included in the folder by mistake but we decided to keep them incase someone found them useful). We have no plans on rendering depth images for the training and validation datasets.

BingCS commented 3 years ago

Thanks for your kind reply. Which version of the Blender do you use? @tancik

tancik commented 3 years ago

I believe I was using 2.82 at the time.

BingCS commented 3 years ago

Great thanks!

ray8828 commented 1 year ago

FYI: you could check the blender file bpy script to find the depth mapping, unfortunately, the lego far value here is not 6.0, but 8.0 as suggested in the blender file, this will align the 8bit depth

image
Szy-Young commented 1 year ago

FYI: you could check the blender file bpy script to find the depth mapping, unfortunately, the lego far value here is not 6.0, but 8.0 as suggested in the blender file, this will align the 8bit depth image

Hi @ray8828 , your visualization looks great! Could you plz help me take a look if my parsing for depth map in "Lego" is correct? Thanks!

import cv2
import numpy as np

depth_file = ....
depth = cv2.imread(depth_file, 0)
near = 2.
far = 8.
depths = near + (far - near) * (1. - (depth / 255.).astype(np.float32))
Jiahao-Ma commented 1 year ago

@ray8828 Could you please provide some details about how to generate points cloud using the depth map you mention? I have tried lots methods, but still fail to reconstruct the point clouds.