Code for "DeepMend: Learning Occupancy Functions to Represent Shape for Repair."
Published at ECCV 2022.
@inproceedings{lamb2022deepmend,
title={DeepMend: Learning Occupancy Functions to Represent Shape for Repair},
author={Lamb, Nikolas and Banerjee, Sean and Banerjee, Natasha Kholgade},
booktitle={European Conference on Computer Vision},
pages={433--450},
year={2022},
organization={Springer}
}
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Code tested using Ubutnu 18.04 and python 3.8.0. Note that you need to have the following apt dependencies installed.
sudo apt install python3.8-distutils python3.8-dev libgl1 libglew-dev freeglut3-dev
We recommend using virtualenv. The following snippet will create a new virtual environment, activate it, and install deps.
sudo apt-get install virtualenv && \
virtualenv -p python3.8 env && \
source env/bin/activate && \
pip install -r requirements.txt && \
./install.sh && \
source setup.sh
Issues with compiling pyrender are typically solved by upgrading cython: pip install --upgrade cython
.
If you want to run the fracturing and sampling code, you'll need to install pymesh dependencies:
./install_pymesh.sh
If you just want to try out inference, run the following script with the example file. This will infer a restoration and create a gif.
cd deepmend
./scripts/infer_quick.sh experiments/mugs/specs.json ../example_files/fractured_mug.obj
See fracturing/README.md
.
Navigate into the deepmend
directory.
cd deepmend
Each experiment needs a corresponding directory with a "specs.json" file. You can find an example at deepmend/experiments/mugs
.
To train, run the training python script with the path to an experiment directory.
python python/train.py -e experiments/mugs
Navigate into the deepmend
directory.
cd deepmend
Inference (and related operations) is done in four steps:
- Infer latent codes.
- Reconstruct meshes.
- Generate renders.
- Evaluate meshes.
Each experiment needs a corresponding directory with a "specs.json" file. You can find an example at deepmend/experiments/mugs
.
To infer:
./scripts/infer.sh experiments/mugs
Data is saved in the experiment directory passed to the reconstruction script, under a Reconstructions
subdirectory. For example, results for the mugs example will be stored in deepmend/experiments/mugs/Reconstructions/ours/
. Meshes are stored in the Meshes
subdirectory. A render of all the results is stored in the top-level reconstruction directory.