EPFL-LGG / UmbrellaMesh_release_v1

Umbrella Meshes: Elastic Mechanisms for Freeform Shape Deployment

ACM Transactions on Graphics (Proceedings of SIGGRAPH), July 2022.
Yingying Ren* · Uday Kusupati* · Julian Panetta · Florin Isvoranu · Davide Pellis · Tian Chen · Mark Pauly
*joint first author (order determined by coin toss)

About

This repository contains the source code and data for the paper Umbrella Meshes: Elastic Mechanisms for Freeform Shape Deployment, published at SIGGRAPH 2022.

Note: major refactoring is in progress! Please stay tuned for updated versions in Fall 2022!

Getting Started

C++ Code Dependencies

The C++ code relies on boost and cholmod/umfpack. The design optimization part of the code also depend on the commercial optimization package knitro; these will be omitted from the build if knitro is not found.

macOS

You can install all the necessary dependencies except knitro on macOS with MacPorts:

# Build/version control tools, C++ code dependencies
sudo port install cmake boost suitesparse ninja glew
# Dependencies for jupyterlab/notebooks
sudo port install npm6
conda install python

Ubuntu 19.04

A few more packages need to be installed on a fresh Ubuntu 19.04 install:

# Build/version control tools
sudo apt install git cmake ninja-build
# Dependencies for C++ code
sudo apt install libboost-filesystem-dev libboost-system-dev libboost-program-options-dev libsuitesparse-dev
# LibIGL/GLFW dependencies
sudo apt install libgl1-mesa-dev libxrandr-dev libxinerama-dev libxcursor-dev libxi-dev
# Offscreen render dependencies
sudo apt install libglew-dev libpng-dev
# Dependencies (pybind11, jupyterlab/notebooks)
sudo apt install python3-pip npm
# Ubuntu 19.04 packages an older version of npm that is incompatible with its nodejs version...
sudo npm install npm@latest -g

Obtaining and Building

Clone this repository recursively so that its submodules are also downloaded:

git clone --recursive https://github.com/EPFL-LGG/UmbrellaMesh

Build the C++ code and its Python bindings using cmake and your favorite build system. For example, with ninja:

cd UmbrellaMesh
mkdir build && cd build
cmake .. -GNinja
ninja

Running the Jupyter Notebooks

The preferred way to interact with the code is in a Jupyter notebook, using the Python bindings. We highly recommend that you install the Python dependencies and JupyterLab itself in a virtual environment (e.g., with venv).

pip3 install wheel # Needed if installing in a virtual environment
pip3 install jupyterlab==3.3.4 ipykernel==5.5.5 ipywidgets==7.7.2 jupyterlab-widgets==1.1.1 # Use a slightly older version of ipykernel to avoid cluttering notebook with stdout content.
# If necessary, follow the instructions in the warnings to add the Python user
# bin directory (containing the 'jupyter' binary) to your PATH...

git clone https://github.com/jpanetta/pythreejs
cd pythreejs
pip3 install -e .
cd js
jupyter labextension install .

pip3 install matplotlib numpy scipy pytest

Launch Jupyter lab from the root python directory:

cd python
jupyter lab

There are four demos in python/live_demos. Try them out!

Citation

If you use parts of this code for your own research, please consider citing our paper:

@article{RKP2022umbrellameshes,
	author = {Ren, Yingying and Kusupati, Uday and Panetta, Julian and Isvoranu, Florin and Pellis, Davide and Chen, Tian and Pauly, Mark},
	title = {Umbrella Meshes: Elastic Mechanisms for Freeform Shape Deployment},
	year = {2022},
	issue_date = {July 2022},
	publisher = {Association for Computing Machinery},
	address = {New York, NY, USA},
	volume = {41},
	number = {4},
	issn = {0730-0301},
	url = {https://doi.org/10.1145/3528223.3530089},
	doi = {10.1145/3528223.3530089},
    journal = {Transactions on Graphics (Proceedings of SIGGRAPH)},
	month = {jul},
	articleno = {152},
	numpages = {15},
	keywords = {deployable structure, computational design, numerical optimization, fabrication, physics-based simulation}
}