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Creating a YOLO Core ML Object Detector with Decoding Logic

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25 Nov 2020CPOL
In this article we are ready to include detection decoding directly in the Core ML model.
In this article, we’ll include the decoding of YOLO v2 results into the Core ML model.

Revisions


  

Compare Revision Minor Date Status Editor
6 - publicly available Yes 25-Feb-21 5:08 Available Sean Ewington
Updates in content.
5 No 26-Nov-20 4:23 Available Sean Ewington
Updates in content. Changes: 91

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This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)

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About the Author

Jarek Szczegielniak
Architect Objectivity
Poland Poland
Jarek has two decades of professional experience in various areas, including machine learning, software design, development and testing, business and system analysis, project and team management, logistics and business process optimization.
He is passionate about creating service-oriented software solutions with complex logic, especially with the application of AI.
Jarek currently works as a Machine Learning Engineer and Technical Architect at Objectivity (https://www.objectivity.co.uk).

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