[Machine vision to sort by headstamp]

3 hours ago, StandardError said:

 

 

This is pretty neat and probably what I would have done. I'm going to assume that the .hdf5 is the model weights?

 

If I can ask, what was the ROC-AUC for your model? Don't get me wrong. It's very impressive, but I had been debating about how much any model's robustness would be impacted by the quality of imaging and such.

 

Also, getting it on an RPi3 is pretty nice. I was tempted to use one of the intel compute chips but suspected that'd be overkill

 

I've just been sidelined with thesis revisions and haven't been able to really go at it but this is pretty cool.

 

 

 

Correct, the hdf5 file is where the model weights are stored.

 

Check out the images I posted and the results. In my opinion, the model is more accurate with low quality images than a person would be.

 

For training, you certainly want a little more horsepower than an RPi, but for classification, it's plenty fast enough. The model is small, and the classification time is quicker than a brass feeder.

 

37 minutes ago, Yondering said:

 

This is very cool, and I'd be willing to contribute on the hardware side. I don't have the free time right now to commit to building a complete system, but I can help out with machining on various parts and some design input. 

 

One thought & question on the software side - could this be used to separate between crimped and uncrimped or processed brass? I'm guessing so, it would just need to look at the primer pocket crimp instead of (or along with?) the headstamp. I'd love to have an easy way to sort out crimped primer pocket 9mm brass; that stuff has been a plague on my reloading process lately.

 

You absolutely could separate based on crimped primer pockets. You can basically sort by any criteria that a person would be able to visually recognize, assuming the fidelity of the image is good enough. Processed brass may be more difficult, because there's not a very obvious visual indicator that it's already been processed.

[Machine vision to sort by headstamp]

On 2/26/2019 at 6:07 PM, jmorris said:

 

Figure out the computation part and I’ll knock out the physical part.

 

I did get a little further on my sort by weight project but it’s still not much more than proof of concept at this point.

 

https://www.youtube.com/watch?v=1V_Hm3oqlO4

 

I actually registered just to respond to this post. I'm a software engineer with experience in backend web development (mostly Python, including Django, Flask, etc.), embedded software, Linux, and more recently, machine vision. I wrote and trained an ML model last year to sort 5.56 brass by headstamp, and it does so with 100% accuracy based on my validation data.

 

Here are some samples that were all correctly classified. https://imgur.com/a/90eSE

 

The code is open source, and freely available here: https://github.com/jakogut/brass-sorter

 

It was actually rather easy, and it's quite quick, even on an RPi 3 (even faster on many other inexpensive SBCs out there). If memory serves, it takes about a tenth of a second to classify each piece of brass, but don't quote me on that.

 

I haven't spent much time or effort on the mechanical side of this, because it's not my strong suite, but if somebody could build a machine that could be controlled by an RPi, I could write all the software to make it happen. It would be really neat if the parts could be 3D printed, and the machine could be built for a couple hundred bucks. I'm also very experienced with (and an active contributor to) Buildroot, and I could make a set of scripts to build a firmware image automatically that would be easy for DIYers to install.

 

I'd be willing to do this work and open source it, if some of you want to work on the hardware side of things.