Open Source Unix Shell Frameworks

Gin Config is a lightweight and flexible configuration framework for Python built around dependency injection. It enables developers to manage complex parameter hierarchies—particularly common in machine learning experiments—without relying on boilerplate configuration classes or protos. By decorating functions and classes with @gin.configurable, Gin allows their parameters to be overridden using simple configuration files (.gin) or command-line bindings. Users can define default parameter values, scoped configurations, and modular references to functions, classes, or instances, resulting in highly composable and dynamic experiment setups. Gin is particularly popular in TensorFlow and PyTorch projects, where researchers and developers need to tune numerous interdependent parameters across models, datasets, optimizers, and training pipelines.

Clairv is a Java framework based on Apache Lucene that adds search capability to your applications. Distributed indices over different machines are supported. A web front end will also be provided.

PROTON is a high-level Python framework that facilitates rapid server-side development with clean & pragmatic design. Thanks for checking it out! PROTON aims at easing server-side development for all Python enthusiasts. Essentially, by running a shell command, developer will auto generate necessary Model, Controller and APIs! All of this with connectivity to Transactional Databases (PROTON supports Postgresql, MySQL & SQL Server),caching (Redis middleware), Auto generated OpenAPI specs & descriptive logging! One command, to get a production ready server-side stack!

RefineNet is a MATLAB-based framework for semantic image segmentation and general dense prediction tasks. It implements the architecture presented in the CVPR 2017 paper RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation and its extended version published in TPAMI 2019. The framework uses multi-path refinement and improved residual pooling to achieve high-quality segmentation results across multiple benchmark datasets. It provides trained models for datasets such as PASCAL VOC 2012, Cityscapes, NYUDv2, Person_Parts, PASCAL_Context, SUNRGBD, and ADE20k, with versions based on ResNet-101 and ResNet-152 backbones. The repository supports both single-scale and multi-scale prediction, with scripts for training, testing, and evaluating segmentation performance. While this codebase is specific to MATLAB and MatConvNet, a PyTorch implementation and lighter-weight variants are also available from the community.

Strasheela is a constraint-based music composition system. The user defines music theories by sets of compositional rules and the system creates music which complies with these theories. User-interface is the programming language Oz.

"Yet Another Do-It-Yourself (Test) Automation Framework" specification. Use or modify one of the existing software implementations (hosted/referenced here), or implement the framework yourself. Download and read the spec for more details.

Agglo is a CASE (Computer Aided Software Engineering) or AGL (Atelier Génie Logiciel), whose aim is to facilitate installation ans use of various tools (either existing opensource tools, or agglo tools), in several facets of project development: - requirements management - unit tests - automated integration tests - toolkit for various languages (cpp, c, python, shell, xsl) other facets are to come ultimately: - coverage tests - planification - integration with hudson - code quality analysis - indicator production

The dotCODES Source Control Maintenance Mainframe for Visual Studio is an administrator console application for developing dotCODES components. Built upon a Python foundation, the program is used to create data center routines (Unix packages) and maintain enterprise cloud services (CGI scripts/Apache) by means of building dotCODES runtimes and deploying them to and from the client server.