DeepDIVA: A Highly-Functional Python Framework for Reproducible Experiments

DeepDIVA is an infrastructure designed to enable quick and intuitive setup of reproducible experiments with a large range of useful analysis functionality. Reproducing scientific results can be a frustrating experience, not only in document image analysis but in machine learning in general. Using DeepDIVA a researcher can either reproduce a given experiment with a very limited amount of information or share their own experiments with others. Moreover, the framework offers a large range of functions, such as boilerplate code, keeping track of experiments, hyper-parameter optimization, and visualization of data and results. DeepDIVA is implemented in Python and uses the deep learning framework PyTorch. It is completely open source and accessible as Web Service through DIVAServices.

Additional resources

• DeepDIVA Homepage
• Tutorials
• Paper on arXiv