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1.4 KiB
1.4 KiB
MattPort
Setup the environment
# Clone the repo
git clone --recurse-submodules git@github.com:ethanweber/mattport.git
# Create the python environment
conda create --name mattport python=3.8.13
conda activate mattport
pip install -r environment/requirements.txt
# Install mattport as a library
python setup.py develop
# Running the test cases
pytest tests
Getting the data
Download the original NeRF dataset and put it in the following format.
- data/
- blender/
- fern/
- lego/
Training a model
# Run with the default config
python scripts/run_train.py
# Run with config changes
python scripts/run_train.py machine_config.num_gpus=1
Setting up Jupyter
python -m jupyter lab build
bash environments/run_jupyter.sh
Tooling
We use autoenv to make setting up the environment and environment variables easier. This will run the .envrc file upon entering the /path/to/mattport folder. It will also remove the set environment parameters upon leaving.
# Install direnv.
sudo apt install direnv
# Add the following line to the bottom of your ~/.bashrc file.
eval "$(direnv hook bash)"
# Populate your .envrc with commands you want to run. Then, run the following to allow updates.
cd /path/to/mattport
direnv allow .