compoelem
Library for generating and comparing compositional elements from art historic images.
colabs to this project
https://drive.google.com/drive/folders/1ajWBqMry1zhEYhIC5dhzpnReOHeEJVuq?usp=sharing
Dataset
The dataset we used for the evaluation of our method can be found here: https://drive.google.com/file/d/1-lSW62XNsjwgeSSTtdlpMtAU9RjEqugD/view
Build and Setup:
git clone https://github.com/tilman/compoelem
cd compoelem
git submodule update --init --recursive
git submodule update --recursive
Build and Setup Openpose
Installation routine could change with an update of the git submodule. Tested with git commit b3e8abf from 20 Dec 2019. For an up to date installation procedure visit: https://github.com/tensorboy/pytorch_Realtime_Multi-Person_Pose_Estimation
Depends on swig therfore run apt install swig
or conda install swig
for ubuntu or brew install swig
for Mac OSX.
Also make sure to download the model and place it under compoelem/compoelem/detect/openpose/pose_model.pth
conda install swig
cd compoelem/detect/openpose
pip install -r requirements.txt
cd lib/pafprocess; sh make.sh
Installation of the library:
python setup.py clean --all
python setup.py bdist_wheel
pip install dist/compoelem-0.1.0-py3-none-any.whl
or
python setup.py clean --all
python setup.py install
Usage:
See docs and tests for example usage.
Run Test Suite:
python setup.py pytest
Build the documentation:
first built the project and then run:
pip install pdoc3
rm -rf docs && python setup.py clean --all && python setup.py install && pdoc --html --output-dir docs compoelem
Development: bump version and install locally
./release.sh major|minor|patch