Expresso : A user-friendly GUI for Designing, Training and Exploring Convolutional Neural Networks

TL;DR

Expresso is a user-friendly Python-based GUI tool built on Caffe, designed to simplify the process of designing, training, and analyzing convolutional neural networks for both beginners and experienced researchers.

Contribution

It introduces an extensible, multi-threaded graphical interface that streamlines deep learning workflows and experiment management.

Findings

Facilitates easier network design and training

Enables concurrent execution of tasks

Provides visualization and analysis tools

Abstract

With a view to provide a user-friendly interface for designing, training and developing deep learning frameworks, we have developed Expresso, a GUI tool written in Python. Expresso is built atop Caffe, the open-source, prize-winning framework popularly used to develop Convolutional Neural Networks. Expresso provides a convenient wizard-like graphical interface which guides the user through various common scenarios -- data import, construction and training of deep networks, performing various experiments, analyzing and visualizing the results of these experiments. The multi-threaded nature of Expresso enables concurrent execution and notification of events related to the aforementioned scenarios. The GUI sub-components and inter-component interfaces in Expresso have been designed with extensibility in mind. We believe Expresso's flexibility and ease of use will come in handy to researchers, newcomers and seasoned alike, in their explorations related to deep learning.