MarcelleA Toolkit for Composing Interactive Machine Learning Workflows and Interfaces

WARNING

This website document the next big update to Marcelle. It is unstable and breaking changes are expected. The current stable version is documented at https://marcelle.dev/

Marcelle is a modular open source toolkit for programming interactive machine learning applications. Marcelle is built around components embedding computation and interaction that can be composed to form reactive machine learning pipelines and custom user interfaces. This architecture enables rapid prototyping and extension. Marcelle can be used to build interfaces to Python scripts, and it provides flexible data stores to facilitate collaboration between machine learning experts, designers and end users.

Design Human-AI interactions in minutes.
Marcelle provides a high-level API enabling rapid prototyping of applications where human directly interact with machine learning systems.

GIF Webcam recognition

Features

Modular
Marcelle is built around various components providing a graphical user interface that can be displayed on demand. Components can typically be data sources (for instance a webcam capturing images), data structures (such as datasets), models, or visualization.

Component-based architecture Animation

Composable
Marcelle provides two layout mechanisms for user interface composition: dashboards and wizards.

Composable Interfaces Animation

Interaction-Driven
Marcelle emphasizes machine learning pipelines driven by user interactions, through reactive programming.

Interaction-driven pipelines Animation

Designed for collaboration
Marcelle's data stores enable sharing data and models among stakeholders

Collaboration