This framework is an evolved fork of DeepDIVA: A Highly-Functional Python Framework for Reproducible Experiments.
The major differences are the full adoption of an object oriented programming design, the polishing of the workflow, the introduction of an optimized inference-use case and a better isolation between the tasks.
This work has been conducted during an internship at V7, London, UK.
Based on the "Machine Learning" category.
Alternatively, view Gale alternatives based on common mentions on social networks and blogs.
* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.
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