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[deleted] OP t1_j8wddyy wrote

Reply to comment by PaleontologistDue620 in My Neural Net is stuck, I've run out of ideas by [deleted]

It is interesting you commented this. I have spent a day yesterday trying to train some Yolo in python, but all the implementations on github are quite obsolete, apart from Yolov7.

Unless you refer to ultralytics only?

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PaleontologistDue620 t1_j8wuk9b wrote

go for YOLO v3 or YOLO v4. i promise they'll be good enough for you, don't be bothered with version numbers . (if you need lighter models go for tiny versions of v3 and v4).

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[deleted] OP t1_j8x413i wrote

I did it with tiny yolo v7, using google colab. My point is that there are barely any projects that are usable, unless you found some?

Yes the results were great, I am thinking of writing a little blogpost for others, it is actually quite simple because I found a tutorial in roboflow this time around.

Thanks for your support !

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[deleted] OP t1_j90ysce wrote

Sorry to be annoying but I thought it was nice to give you some news as well. I was confused as to why there isnt yolo in pytorch, here it is why https://github.com/pytorch/vision/issues/6341

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PaleontologistDue620 t1_j90z1yo wrote

no you're not annoying at all, thanks for the update :)

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[deleted] OP t1_ja32trh wrote

Another update, I am reading the first yolo paper:

>We also train YOLO using VGG-16. This model is more accurate but also significantly slower than YOLO. It is useful for comparison to other detection systems that rely on VGG-16 but since it is slower than real-time the rest of the paper focuses on our faster models.

Which also explains that my main error was to use VGG16 without a good idea of how to make it understand where the objects are, which is what they did..

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[deleted] OP t1_j8zb580 wrote

I have found out that VGG can indeed be used with SSD for the same task. Idk exactly what is the general idea but mostly you can combine CNNs with something else and get the bouding box. Pytorch has a SSD-VGG model.

I wonder why pytorch has no yolo implemented that we can just use..

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