Meshes4Mic

A Python package for efficient 3D mesh processing and visualization tailored to microscopy image analysis, bridging the gap between volumetric data and surface representation for biological research. This package will be the backbone of a Blender addon and a Napari plugin.

Mask/labeled-map ↦ meshes

Allows to transform a binary mask or a labeled-map into a set of meshes.

• Images are read thourgh Dask, so they can be of any arbitrary size.
• Works whether images are isotropic or not.
• In the case of a labels-map, each individual label has its own buffer and so, their own mesh. Otherwise, everything is connected. The OME-TIF and OME-ZAR file formats are the only supported formats.
• Multi-channels and multi-timepoints stacks are handled.
• The output is an Alembic (.abc) file.
• Meshes can be optimized given their local curvature to minimize the number of vertices.

How to build the project...

...for production

• We will need a Python environment with the pybind11 module available.
• Navigate to the project's root directory (the one containing setup.py).
• In there, create a folder named build.
• Run the command python setup.py build_ext --inplace.
• Run the command pip install -e ..
• You can now use the module in this Python environment.

...for C++ unit-tests

• You will need to have CMake installed.
• Navigate to the project's root directory (the one containing setup.py).
• In there, create a folder named tests-build and jump into it.
• From this folder, run the command: cmake ...
• Still in this folder, you can now run: make, which will result in the creation of the M4M executable.
• Run ./M4M to launch the testing session.

...for Python unit-tests

• You will need the pytest module.
• To do that, you first need to build the project with the "For production" instructions.
• Then, you can navigate to the meshes4mic/src/meshes4mic/tests folder.
• From there, you can simply run pytest . to launch the testing session.