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Anyone know of any good reference material that teaches you how to implement and train your own Yolo object localization neural network? (Preferably for tensorflow) I'm not looking for pretrained models that you just downloaded and run, rather a tutorial that walks you step by step through the implementation of the network, the reasoning behind the architecture, and examples of the training data used for the training as well as the process of training?

I know it's a lot to ask but it's really frustrating when ever example is just "clone this repo, hit run and use the pretrained models" sure it might get you up and running quickly but it doesn't really teach you anything...

P.s. - seems like every educational post goes from super simple to super complex without any middle ground and the super complex stuff doesn't tell you why its used the way way it is.

Comments
  • 0
    I feel you, mate.
    I have been there alot of times.
    I started with that topic about 2 years ago and still do not know shit lol.
    It is so confusing. It does not matter how much dedication you have, it will not get you any further, when everything else keeps failing.
  • 0
    My first post on devRant was about that topic btw.
    You should find some good hints there.
  • 1
    I came across yolo(I believe you are referring to "You Only Look Once") last summer(i didn't use it in my project). They published a couple of papers that is open to public. Read it for better understanding and don't forget to watch the video made by siraj on YouTube.
  • 2
    @jokerreturns tbh siraj videos are bad.
  • 1
    @-ANGRY-CLIENT- yeah, his videos just skim over stuff and/or download pretrained models... Kinda useless for learning...
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