darknet VS model

This reminds me of the resume for the guy who made darknet https://pjreddie.com/darknet/

Love the darknet (also made by him) github. Like what is this?

I don’t know, the OG author seemed pretty lax on its use based on the license.

In that case you're sure to enjoy this one.

Literally the first google link dude… https://github.com/pjreddie/darknet

Election of tools: you should define if you are going to use machine/deep learning methods or classical approaches such as the Viola-Jones algorithm. I will recommend you to use ML/DL with TensorFlow (Object Detection API) or Darknet (YOLO).

https://github.com/wingman-jr-addon/model#dataset

Your response is interesting because it tells me you maybe expected it to be in a different spot - was there a specific spot you were looking at? Might help me improve the descriptions.

Thanks for the response dynamite-ready. There's a lot in here, but I'll try to comment on a couple items. Some of your suggestions I've actually thought about extensively, so perhaps you'll find the reasoning interesting?

Regarding the current state of tech: I agree the tech still has quite a ways to go. I think one of the most interesting aspects here is how e.g. NSFW.js can get extremely high accuracy - but not necessarily perform better in the real world. I think it speaks in part to the nature of how CNN's work, the nature of the data, and the difficulty of the problem. Still, having seen how incredibly good "AI" has gotten in the last decade, I have quite a bit of hope here.

Regarding putting it on a server: that is indeed a fair question, but my desire is to keep the scanning on the client side for the user. In fact, it was actually the confluence of Firefox's webRequest response filtering (which is why I didn't make a Chrome version) and Tensorflow.js that allowed me to move from dream to reality as I had been waiting prior to that time. I can't afford server infrastructure if the user base grows, and people don't want to route all their pictures to me. So I guess I see the current way it works as a bonus, not a flaw - but it DOES impact performance, certainly.

Regarding data collection with respect to server - yes, this is something I've contemplated (there's a GitHub issue if you're curious). There are, however, two things that I've long mulled over: privacy and dark psychological patterns. Let me explain a bit. On the privacy front - it is not likely legal for a user to share the image data directly due to copyright, so they need to share by URL. This can have many issues when considering e.g. authenticated services, but one big one also is that the URL may have relatively sensitive user-identifying information buried in its path. I can try to be careful here but this absolutely precludes sharing this type of URL data as an open dataset. On the psychological dark patterns front - while I'm fine with folks wanting to submit false positives, I think there's a very real chance some will want to go flag all the images they can find that are false negatives (e.g. porn). I don't think that type of submission is particularly good for their mental health or mine. So, in general, I think user image feedback is something that would be quite powerful but needs a lot of care in how it would be approached.

Regarding the UX - thanks! And you're welcome to try the model as well - I've tried to include enough detail and data to allow others to integrate as they wish: https://github.com/wingman-jr-addon/model/tree/master/sqrxr_... Also, let us know how things go if you try out Darknet.

Good luck!

Y'all were kind enough to help me get up and running with a Supermicro GPU server. I use it to cook up the machine learning model for a Firefox addon that blocks NSFW images client-side, Wingman Jr. Filter. Your help made a big difference in me being able to get the right box at the right price - so thanks!