u/Suitable-Name

Hey everyone,

I just had some corundum casually flying through my room. Wasn't even too bad regarding the stone. Just some cheap training material. Nothing that hurts.

But that piece almost hit my OLED TV🤬

That made me think... sure, would've sucked. But I'm also sure there are people here that had more tragic accidents than me I almost had.

With or without the involvement of other things that might got hit. What was your most expensive mistake / accident / whatever while faceting?

Hi zusammen, die Tatsache, dass ich diesen Post erstelle, macht es für die, die sich auskennen wahrscheinlich offensichtlich, dass ich keine Ahnung habe. Also prinzipiell weiß ich schon, was ich will, nur nicht, nach was ich auf z.B. Google Maps suchen muss.

Ich habe eine Metallplatte, die optimalerweise im Mikrometerbereich geglättet werden müsste. Hat mir da jemand eine Empfehlung oder einen Tip nach was ich suchen muss um einen Anbieter zu finden der mir helfen kann?

Vielen Dank für euren Input!

Instead of digging around your phone's charging port with a toothpick, just gently press a tiny piece of poster putty into it and pull it out. It grabs all the compacted pocket lint mostly in one go without risking damage to the pins.

Also works for all other small openings that collect dust.

Hey everyone,

I read every now and then that heating possibly enhances color in sapphires and also makes them clearer.

I just wonder, what are the limits here? Does anyone have a before / after picture of some (maybe even strong) included that became clearer after heating or where it didn't work out and the stone didn't clear up?

Here are two stones that made me wonder if they'd probably clear up when getting heated.

Thanks for sharing your experiences!

https://preview.redd.it/n7gy3y4ijreh1.png?width=4000&format=png&auto=webp&s=c6f25756bed84836e2516a61efbb4ec30302e363

https://preview.redd.it/ycnfeovjjreh1.png?width=4000&format=png&auto=webp&s=570e0f154e31a4d77a357c4211da4403fa3cdba3

https://preview.redd.it/35u6oj6ljreh1.png?width=4000&format=png&auto=webp&s=9750a37130c7f12ffb0cce6af1f852d09cca5d05

https://preview.redd.it/85tr9l0mjreh1.png?width=4000&format=png&auto=webp&s=59d26891903654f1793bb93afaa0009d22cd8491

Hey everyone,

I've been working on and off on several projects, mostly for myself. This here began with a simple "how hard can it be to merge some pictures with shifting focus?". I guess, I underestimated it "a bit". But looking at what's available, I thought this one would be great to add some features people probably would miss otherwise, give it a polish and release it. Even though I'm basically writing code for more than half of my life now, I didn't publish much yet. This is definitely the biggest project so far I'm releasing to public myself and I hope you'll like the software!

So, I just finished the final polish of what I call z-stackr. It's a focus stacking tool to create a single merged picture out of multiple pictures with shifting focus.

I could give you an AI wall of text now, but you'll have that, when you visit the repository and have a look at the README files. So, I'm trying to keep it short and since everything is explained in greater detail in the READMEs. Here is a overview of the most important currently implemented features:

• Usable as GUI (Slint), CLI or library and Python
• Support for JPEG, TIFF, PNG and several RAW formats (RAW formats mostly untested)
• Two different alignment algorithm implementations; optionally AKAZE + RANSAC for preprocessing
• Three different merge algorithms
• Optional sorting of frames and configurable threshold for culling of frames that don't contribute enough to the final result
• Monitor mode for live-stacking as soon as new pictures get added to a folder getting watched
• Neural network support with traits for easy replacement of the model implementation (Models not trained yet)
• Python scripts to create synthetic training data from normal images using DepthAnywhereV3 + Blender
• AKAZE, Python, AI features and GPU support are behind optional feature flags. The GUI adopts to what actually was compiled, AKAZE is the only default feature

Other things to add, that came into my mind so far are, for example, a WASM build or some color management options besides the auto correction.

Now, probably one of the most important question for many... How much is "slop"? Well, From a percentual point of view, quite a lot:

• All docs / comments / README files
• Explicit SIMD code
• NN implementation
• Boilerplate (discussing file/folder layout with AI and have it create a setup.sh which creates the initial layout)
• Error Analysis from time to time
• General review and evaluation of some benchmarks used during development
• Suggesting / Explaining the used algorithms for implementation

Regarding the neural networks and loss functions, they're designed by Fable 5 and dispatched for implementation to Sonnet 5. In the best case, they'll do what they're designed to, in the worst case they're just a sample implementation for the traits. I decided to publish V1 without the weights, since the rest of the features is working pretty good, in my opinion and training will, of course, also need time.

I'm going to train the models on a single A100-80G over the next days / weeks. If someone can or wants to support with this, help is always welcome. Real stacking datasets would absolutely help, if someone is willing to share them. Due to the lack of enough real stacking frame sources, my plan was to pre-train using synthetic data (extracting depth info from normal pictures, shifting focus using blender, simulating alignment issues). When this is done, I'll also publish the weights, but I don't expect it to be too good, until there is a fine-tuning with real source and target frames. Performance and so on? I have no idea, but I was curious how good this would work, so I guess, I'll find it out. Don't worry, I said Claude not to make any mistakes and create an expert-style model and loss function! ;)

Also, cases that work in other stacking software but not in this one would be interesting, of course, if someone is willing to share them.

I have quite some years development experience, so when using AI, I mostly still know what I'm doing and don't trust it blindly. Mostly? My in-depth knowledge of neural networks isn't the strongest and the SIMD code was also something where I actually trust the AI more then myself. Of course, this doesn't mean that I expect the rest of the project to be flawless.

"Oh my god, all in one commit!"... Yep, I explained it in comments before, but surely most of them have never seen them. I'm developing against my own git server and only push the final state to GitHub if I decide to publish something. That's enough food for the GitHub AI. I'll see how I handle future changes on the project regarding this.

For anyone who wants to give it a try but is lacking images to stack, there are some frames in the sample folder, including a reference result to show what the result should look like using Apex.

I'd be happy to see some feedback on the app and hope some people will have their fun with it. Also, feel free to contribute if you like the project, but feel like something is missing or could be done better.

GitHub: https://github.com/suitable-name/z-stackr  
crates.io: https://docs.rs/z-stackr-core / align / algo / pipeline / nn / python / gui / cli  
docs.rs: https://docs.rs/z-stackr-core / align / algo / pipeline / nn / python / gui / cli  
pypi: https://pypi.org/project/z-stackr

Have a nice day!

https://preview.redd.it/djiy0i6gn0ch1.png?width=2954&format=png&auto=webp&s=8489e55bd8a2f1fe07e251252db68cd0c92924a8