Self-Supervised Neural Implicit Isotropic Volume Reconstruction
Project description
Neural Implicit Isotropic Volume Reconstruction
Getting Started
conda create -n niv python=3.9
conda activate niv
conda install pytorch==1.13.1 torchvision==0.14.1 torchaudio==0.13.1 pytorch-cuda=11.7 -c pytorch -c nvidia
pip install igneous-pipeline pytorch-ignite tqdm wandb
Start and Reconnect to Training Job using tmux
tmux new -s my_training_session
python train.py -opt options/train/train_iso_em.yml
Detach from the session using Ctrl+B D
.
Reconnect to the session using
tmux attach -t my_training_session
List existing tmux sessions
tmux list-sessions
Delete tmux session
tmux kill-session -t session-name
Data Access
Requires gsutil
command-line utility installed. See instructions here.
Download public training data from GCS
cd neural-volumes
gsutil cp gs://neural-implicit-volumes/datasets/hemibrain-volume-denoised-large.zip ./data
cd data
unzip hemibrain-volume-denoised-large.zip
Convert reconstructed volume to NG precomputed and upload to GCS
igneous image create ./DATA.npy ./PRECOMPUTED_FOLDER --compress none
gsutil -m cp -r ./PRECOMPUTED_FOLDER/ gs://neural-implicit-volumes/NAME/
References
We used the code from following repositories: NVP, LIIF, VINR.
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