D. Ring, J. Barbier, Guillaume Gales, Ben Kent, Sebastian Lutz
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Jumping in at the deep end: how to experiment with machine learning in post-production software
Recent years has seen an explosion in Machine Learning (ML) research. The challenge is now to transfer these new algorithms into the hands of artists and TD's in visual effects and animation studios, so that they can start experimenting with ML within their existing pipelines. This paper presents some of the current challenges to experimentation and deployment of ML frameworks in the post-production industry. It introduces our open-source "ML-Server" client / server system as an answer to enabling rapid prototyping, experimentation and development of ML models in post-production software. Data, code and examples for the system can be found on the GitHub repository page: https://github.com/TheFoundryVisionmongers/nuke-ML-server