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Tuning YOLOv2 object detection neural networks on custom datasets

Posted 1 year ago
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Hello community, please enjoy my latest project! I hope you can find it useful, and feel free to provide some feedback. I am also quite new to organizing libraries for the Wolfram Language, so any feedback there will be greatly appreciated!

Keywords: YOLO, YOLOV2, fine tuning, pre trained, object detection, neural networks, machine learning

POSTED BY: Alec Graves
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POSTED BY: Moderation Team

Dear Alec, I am currently working on a wood defects detector for my bachelor graduation thesis, and I am trying to implement this using Yolov2.
I ran through your packages and your code you did great job writing them and I would like to mention that they are the only helpful resources i found on the internet for training an object detector on custom data using Mathematica.
However, I tried your Packages and each time I run the BuildYoloLoss package I get the following error FunctionLayer::compilerr: Cannot interpret ThreadingLayer[<>][#1, #2] & as a network. I am running Version 13.01, and since you wrote your code on earlier versions, I think there is an issue related to the syntax of the function layers specification in the GIOU Loss package. I would appreciate your help on that, and if you have other resources or insights on how to build similar loss functions and perform transfer learning on recent Yolo versions using Mathematica, as I cant find any. Thanks in advance.

POSTED BY: Bassel Harby
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