
Responding to the Controversy about YOLOv5 - rocauc
https://blog.roboflow.ai/yolov4-versus-yolov5/
======
bArray
With regards to my comment in a thread that got some notice [1]:

I incorrectly assumed some relationship between @rocauc and the guys behind
YOLOv5 due to some shared language and diagrams, sometimes our brains jump to
conclusions - sorry. Unfortunately the edit timed out before I could do much
about it.

I really appreciate the follow up and the hard work that has gone in since by
RoboFlow. This controversy isn't their fault and they really shouldn't get a
bad rep for it - in fact their handling of the situation has been good. Maybe
some more due diligence, but we're all guilty sometimes. These are the sorts
of actions that earn my respect in terms of being an authoritative source.

My original comment was quite reactionary, the YOLOv5 guys have done some
interesting work. We now have two new interesting approaches based on YOLOv3,
I look forward to reading more about the YOLOv5 internals in the future. There
was some strangeness around comments being deleted from their GitHub issues
once they started getting noticed, but I'll give them the benefit of the
doubt.

With regards to naming, I really think there needs to be some clear change.
YOLOv5 does not build on top of YOLOv4 in any way. I appreciate that the team
was "scooped" on the name, but I don't think bumping the version number was
the correct approach. It's extremely weird to people coming across this for
the first time that YOLOv4 can outperform YOLOv5.

There are still some open issues to be addressed with regards to which network
performs better and in which use cases, hopefully in the coming weeks it can
be worked out.

[1]
[https://news.ycombinator.com/item?id=23480884](https://news.ycombinator.com/item?id=23480884)

~~~
rocauc
Thanks for your followup thoughts. Pleased the conversation has evolved to
focus on architecture and performance rather than naming alone.

re: GitHub comment deletion - We determined we should engage when we have
easier to reproduce results, so we moved quickly to share them. That's what
this post and diligence is, and I've re-engaged on the issues thread in
question [1] with fuller remarks + reproducible Colab notebooks.

[1]
[https://github.com/AlexeyAB/darknet/issues/5920#issuecomment...](https://github.com/AlexeyAB/darknet/issues/5920#issuecomment-643287337)

~~~
bArray
> Thanks for your followup thoughts. Pleased the

> conversation has evolved to focus on architecture and

> performance rather than naming alone.

Agreed. Maybe it wasn't so clear originally, but part of the naming issue came
from the point that a fair comparison hadn't been made with the "previous"
model.

> re: GitHub comment deletion

This was referring to the comments in the GitHub issues of Ultralytics. But in
any case, benefit of the doubt is given. Some people doubted their association
with the project and the comments are now gone - so let's see.

------
yeldarb
This post is in response to the discussion[1] on Hacker News this week on the
post "YOLOv5: State-of-the-art object detection at 140 FPS" and the objections
raised by AlexeyAB on Github[2].

The controversy surrounded around two points:

• Should the model truly be named YOLOv5?

• Are the initial benchmarks Roboflow published accurate and reproducible?

We have published more details surrounding our methodology, clear steps and
notebooks for reproducing our results, a correction of an unfair comparison we
made (re relative inference speed and batch sizes), how we think about the
naming controversy and a request for the community to weigh in.

[1]
[https://news.ycombinator.com/item?id=23478151](https://news.ycombinator.com/item?id=23478151)

[2]
[https://github.com/AlexeyAB/darknet/issues/5920#issuecomment...](https://github.com/AlexeyAB/darknet/issues/5920#issuecomment-642812152)

