
YOLOv4: Optimal Speed and Accuracy of Object Detection - groar
https://arxiv.org/abs/2004.10934
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rgovostes
The original author of YOLO stopped working on it[1]. Alexey Bochkovskiy, aka
AlexeyAB, created a fork on GitHub and wrote an extensive guide to customizing
YOLO's network architecture, added new features, and has answered zillions of
questions.

1:
[https://twitter.com/pjreddie/status/1230524770350817280](https://twitter.com/pjreddie/status/1230524770350817280)

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DagAgren
So the author goes, "wait, this actually causes more evil than good, I will
not work on it any longer", and the other guy goes "don't worry, I will keep
doing the evil for you!"

Sigh.

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deadmutex
It's tricky thing... where do you draw the line? If someone works on the linux
kernel, and someone uses the OS to do bad things.. should one stop?

Also consider that object detection has a lot of impact in positive ways as
well. It doesn't seem so black and white.

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MiroF
I agree - but I imagine even personally it might be a hard thing to hear that
something you created is being used to kill people, even with the knowledge
that it is doing a lot of good.

I'm curious if this is something that some sort of modified license could help
resolve. Do I have the option to license my software so that it can't be used
in war?

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rcw4256
Yes, but you need to be prepared to take it to court when someone uses your
software in war.

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hprotagonist
and when the answer is “hey, it’s GPL’d, here’s our source download link, fuck
off we’re exactly following the rules”?

Licenses are not a viable solution to this sort of ethical quandry.

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rcw4256
That answer should be unsatisfactory to the court, since it wasn't licensed
under the GPL. The rules, in this case, say no use in war.

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punnerud
And code on Github:
[https://github.com/AlexeyAB/darknet](https://github.com/AlexeyAB/darknet)

PyTorch version: [https://github.com/Tianxiaomo/pytorch-
YOLOv4](https://github.com/Tianxiaomo/pytorch-YOLOv4)

~~~
joshvm
It's also in Ultralytics' repo which is very frequently updated.

[https://github.com/ultralytics/yolov3](https://github.com/ultralytics/yolov3)

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gjstein
I object to the use of the word "optimal" for a task like object detection; it
feels counterproductive to claim that this is the "optimal" way of solving
such a broad and complex problem. Great results, but their language needs some
tempering.

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bawana
EVERY ‘good’ thing starts out with ‘good’ intentions. And while it is small
scale remains good. But as it scales up, it becomes evil. Even google,
remember their motto? Now harvesting data like human bodies for its matrix.
Even Facebook was a blast when it started, but now it’s a merch store. Even
the internet was beautiful when it started, now it’s a sewer. It seems the
only thing that can scale well without getting perverted is deep learning. But
as long as humans are in that loop, it will fail. Cloud computing is a
mistake. Bring back the pc, you know, ‘personal computer’

~~~
wolco
These companies were always doing those things. Google always collected and
connected information on you. Facebook was always using users content/data to
experiment with. Cloud computing was always a mistake for most (pay more, get
less control, get locked in). Deep learning opens up so many taboos our
society is not ready to deal with them. As it scales it will open up more cans
of worms.

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Reigngt09
A video on YOLOv4 - Really informative.
[https://www.youtube.com/watch?v=_JzOFWx1vZg](https://www.youtube.com/watch?v=_JzOFWx1vZg)

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mchusma
I have had a lot of fun working with YOLO v3 for robotics applications, very
excited to try these updates. Thanks to the authors for the updates and good
documentation. Good object recognition is the backbone of a huge range of
future applications, and YOLO has been a good option for a while.

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SethTro
I'm a little skeptically of the Swish implementation after looking at Table 2.

Method | Top 1 | Top 5 No-op | 78% | 94% Swish | 64.5% | 86% Mish | 79% |
94.5%

Swish is the only value that decreases performance (and by a huge magnitude)
but a very related methodology improves performance hummm...

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Reigngt09
[https://medium.com/@riteshkanjee/yolov4-superior-faster-
more...](https://medium.com/@riteshkanjee/yolov4-superior-faster-more-
accurate-object-detection-7e8194bf1872)

Article on YoloV4

