Metadata-Version: 2.1
Name: entente
Version: 1.0.0b1
Summary: Work with polygonal meshes which have vertex-wise correspondence
Home-page: https://github.com/lace/entente
Author: Metabolize
Author-email: github@paulmelnikow.com
License: UNKNOWN
Project-URL: Issue Tracker, https://github.com/lace/entente/issues
Project-URL: Documentation, https://entente.readthedocs.io/en/stable/
Description: entente
        =======
        
        [![version](https://img.shields.io/pypi/v/entente?style=flat-square)][pypi]
        [![python version](https://img.shields.io/pypi/pyversions/entente?style=flat-square)][pypi]
        [![license](https://img.shields.io/pypi/l/entente?style=flat-square)][pypi]
        [![coverage](https://img.shields.io/badge/coverage-100%25-brightgren?style=flat-square)][coverage]
        [![build](https://img.shields.io/circleci/project/github/lace/entente/main?style=flat-square)][build]
        [![docs build](https://img.shields.io/readthedocs/entente?style=flat-square)][docs build]
        [![code style](https://img.shields.io/badge/code%20style-black-black?style=flat-square)][black]
        
        Library for working with [lacecore][]-style polygonal meshes which have
        vertex-wise correspondence.
        
        [pypi]: https://pypi.org/project/entente/
        [coverage]: https://github.com/lace/entente/blob/main/.coveragerc
        [black]: https://black.readthedocs.io/en/stable/
        [lacecore]: https://github.com/metabolize/lacecore
        [build]: https://circleci.com/gh/lace/entente/tree/main
        [docs build]: https://entente.readthedocs.io/en/latest/
        
        
        Features
        --------
        
        - Create a composite.
        - Transfer landmarks from the surface of one mesh to the surface of another.
        - Shuffle vertices.
        - Restore correspondence of vertices.
        - Spatial search, lightly wrapping [trimesh][].
        - Complete documentation: https://entente.readthedocs.io/en/stable/
        
        
        
        Installation
        ------------
        
        To use the landmark compositor, first install [libspatialindex][]:
        
        ```sh
        brew install spatialindex
        ```
        
        ```sh
        apt-get install libspatialindex-dev
        ```
        
        Then run `pip install entente[landmarker]` which installs [proximity][].
        
        [libspatialindex]: https://libspatialindex.org/
        [proximity]: https://github.com/lace/proximity
        
        
        Usage
        -----
        
        ```sh
        python -m entente.cli transfer_landmarks source.obj source.pp target1.obj target2.obj ...
        ```
        
        ```yml
        base_mesh: examples/average.obj
        landmarks:
          - knee_left
          - knee_right
        examples:
          - id: example01
            mesh: examples/example01.obj
            knee_left: [-10.0, 15.0, 4.0]
            knee_right: [10.0, 14.8, 4.1]
          - id: example02
            mesh: examples/example02.obj
            knee_left: [-11.0, 13.0, 3.5]
            knee_right: [12.0, 12.8, 3.4]
        ```
        
        ```sh
        python -m entente.cli composite_landmarks recipe.yml
        ```
        
        
        Development
        -----------
        
        ### Updating the Docker build for CircleCI
        
        1. Make sure Docker is installed and running.
        2. Build and push the images:
        
        ```sh
        ./dev.py docker-build 0.2.0  # Use the next available minor release.
        ./dev.py docker-push 0.2.0
        ```
        
        3. Update the `image:` references in `.circleci/config.yml`.
        
        
        Contribute
        ----------
        
        - Issue Tracker: https://github.com/metabolize/entente/issues
        - Source Code: https://github.com/metabolize/entente
        
        Pull requests welcome!
        
        
        Support
        -------
        
        If you are having issues, please let me know.
        
        
        License
        -------
        
        The project is licensed under the MIT license.
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Other Audience
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Artistic Software
Classifier: Topic :: Multimedia :: Graphics :: 3D Modeling
Classifier: Topic :: Scientific/Engineering :: Visualization
Description-Content-Type: text/markdown
Provides-Extra: landmarker
