Closed ziangdi123 closed 6 months ago
Hi, thanks for your interest. Yes, you can use run_network
to get CT volume. Please have a look at line 68 in `train.py'. Simply insert voxel coordinates and you can get the densities.
In terms of network, we set the range of output values to [0,+inf] with ReLU. As for the dataset, we normalize values to [0, 1] for simplicity. The bound is for the hash encoder rather than the network output. It defines the space that the hash encoder covers. Hope this helps.
Thank you for your reply!
Hi,
I have read the code in
src/render/render.py
.I noticed that you obtain the values of sampled points along a set of rays by sending their coordinates into the MLP network. So is it possible to get the values of a CT volume from the trained network just by calling the
run_network()
function?And also, what is the range of the output values of the network? And why do you apply a bound to them?
Thank you for your time!