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Installation

The code was tested on Ubuntu 22.04 with CUDA 11.6 and Python 3.9.

1. Clone the repo

git clone https://github.com/markomih/ResFields.git
cd ResFields

2. Install necessary dependencies

Create a new conda environment with all dependencies:

conda create -n ResFields python=3.9 -y
conda activate ResFields
conda install cudatoolkit=11.6  -y
pip install torch==1.13.1+cu116 torchvision==0.14.1+cu116 torchaudio==0.13.1 --extra-index-url https://download.pytorch.org/whl/cu116
pip install tqdm scikit-image opencv-python configargparse lpips imageio-ffmpeg lpips tensorboard numpy==1.22.4 sk-video trimesh wandb omegaconf pysdf pymcubes matplotlib pytorch-lightning==1.6.5 gdown

Now you can verify that the environment is set up correctly by running a simple experiment of learning a 2D video via a Siren+ResField MLP:

cd dyrecon
python launch.py --config ./configs/video/base.yaml --train --predict model.resfield_layers=[1,2,3] model.composition_rank=10 tag=ResFields

# or the following command for the vanilla Siren
python launch.py --config ./configs/video/base.yaml --train --predict tag=vanilla

3. [Optional] Download the data data

See data preparation to set up the datasets