Python

"An open source machine learning framework for everyone "

TensorFlow™ is an open source software library for high performance numerical computation. Its flexible architecture allows easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices. Originally developed by researchers and engineers from the Google Brain team within Google’s AI organization, it comes with strong support for machine learning and deep learning and the flexible numerical computation core is used across many other scientific domains.

Super-resolve anisotropic EM data along low-res axis with deep learning.

Multicut workflow for large connectomics data. Using luigi for pipelining and caching processing steps. Most of the computations are done out-of-core using hdf5 as backend and implementations from nifty

Luigi is a Python module that helps you build complex pipelines of batch jobs. It handles dependency resolution, workflow management, visualization etc. It also comes with Hadoop support built in.

The purpose of Luigi is to address all the plumbing typically associated with long-running batch processes. You want to chain many tasks, automate them, and failures will happen. These tasks can be anything, but are typically long running things like Hadoop jobs, dumping data to/from databases, running machine learning algorithms, or anything else.

vmtk is a collection of libraries and tools for 3D reconstruction, geometric analysis, mesh generation and surface data analysis for image-based modeling of blood vessels.

vmtk is composed of

• C++ classes (VTK and ITK -based algorithms)
• Python classes (high-level functionality - each class is a script)
• PypeS - Python pipeable scripts, a framework which enables vmtk scripts to interact with each other