Machine Learning - Part 8 - Serialization, Caching & Archiving - Flame 2021.2 @Autodesk_Flame
Machine Learning - Part 8 - Serialization, Caching & Archiving - Flame 2021.2  @Autodesk_Flame
Uploaded October 2020 | Updated September 2026, 11 minutes ago
Level: Intermediate
Recorded in: Autodesk Flame 2021.2


In part 8 of the Machine Learning series, we examine a series of performance enhancements for Machine Learning and internally generated Motion Vectors in the Timeline in the Flame 2021.2 Update.

When using Machine Learning Models and generated Motion Vectors Maps, Flame will now cache the frames to disk to enhanced performance. This removes the need to recalculate the data analysis each time you visit the TimelineFX.

Since this type of caching is now part of the project, it can now be managed as well as archived with the Flame project!

There is also a new notification when Machine Learning models are initialising to let you know what Flame is doing.

And finally, as a new CentOS only feature, the machine learning models are serialised or written to your system disk in order to load faster when you need them. To be clear, this affects the loading times for the machine learning algorithm and not the computations when analysing the footage with a machine learning model.


If you wish to follow along, you can download the 30-day Flame trial at autodesk.com/products/flame/free-trial

or if you are in education, you can sign up for a free 3-year license at autodesk.com/education/free-software/flame


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00:00 - Introduction
00:45 - Notifications
01:29 - Serialization
02:30 - Managing your Cache!
04:33 - Archiving
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Machine Learning - Part 8 - Serialization, Caching & Archiving - Flame 2021.2

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