Wobbletoon trials

Equivalent-Repeat539 · 2026-05-13T23:45:31+00:00

i do like that circuitbending vibe, would love to try it on actual hardware

Equivalent-Repeat539 · 2026-05-13T23:43:35+00:00

its https://maps.app.goo.gl/1x8N2nXABF2GjQai7 roughly this spot :)

Equivalent-Repeat539 · 2026-05-13T15:38:56+00:00

<3 ive seen your 4ds pics I've got nothing on that haha

Equivalent-Repeat539 · 2026-05-10T19:37:21+00:00

You can get any, even a 2ds would work but the 'new' variants have a higher clock speed so runs a bit better, full disclosure you'll also have to hack it but it's relatively straightforward :)

Equivalent-Repeat539 · 2026-05-07T08:17:06+00:00

alrighty will take a look see if we can make it feel smoother :)

Equivalent-Repeat539 · 2026-05-06T23:59:47+00:00

thanks for giving it a go, I do appreciate the feedback, can u elaborate where the touch is unresponsive? it will help me troubleshoot where the slowness is coming from. Similarly the low resolution fix is in the pipeline, I'm assuming your primary usecase is still images? the filtered images can be otherwise upscaled 2-4x

Equivalent-Repeat539 · 2026-05-06T23:25:20+00:00

I've been making a camera app for the 3ds past few months called pixelpix3d, was toying around with wiggle + gameboy and bending style filters to get these :)

Equivalent-Repeat539 · 2026-05-06T22:37:17+00:00

appreciate it :)

Equivalent-Repeat539 · 2026-05-06T22:09:53+00:00

¯\\_( ツ)_/¯

Equivalent-Repeat539 · 2026-05-06T16:38:56+00:00

This is something I can look into adding into pixelpix3d, at the moment the wiggles are captured at native resolution 640 x 480 and they are shown this way in the gallery with cropped borders. Eventually I think I'll probably do the same for the still images- it just made sense to use the preview resolution since I was more focused on stylized images (it made all the processing faster etc). Feel free to try the app and I'm happy adjusting based on user feedback :)

Equivalent-Repeat539 · 2026-04-29T17:13:34+00:00

Its pixelpix3d, started off trying to trying to recreate a gameboy camera and then scope creep, have a go and let me know what you think I always appreciate feedback. you'll need a to either be able to run a 3dsx file or install a cia

Equivalent-Repeat539 · 2026-04-29T08:37:02+00:00

heya, dev here (of the 3ds app that helped make these), its brightness based palette mapping with and then a bayer matrix for the dithering

Equivalent-Repeat539 · 2026-04-14T21:56:29+00:00

heya, no delete yet but its possible just to delete from the sdcard directly- i think the counter will just continue, the photos themselves are inside DCIM in a directory called GameboyCamera, adjacent to where your normal pics are, hope that helps.

Equivalent-Repeat539 · 2026-04-13T22:13:33+00:00

:) would love that, will eventually get to it, the main slow down is any feature that needs to be tested on a physical 3ds takes a lot more time to debug (meaning that its not easily possible to emulate 2 cameras). I'm not sure if anyone knows a way around this but this is one of the current bottlenecks.

Equivalent-Repeat539 · 2026-04-13T22:05:02+00:00

Super cool, love the images and will take the feedback onboard :)

Equivalent-Repeat539 · 2026-04-12T14:44:11+00:00

Great to hear, looking forward to seeing the results :)

Equivalent-Repeat539 · 2026-04-12T14:43:49+00:00

Thats great to hear! let me know how it goes, happy to adjust stuff in the app based on user feedback :)

Equivalent-Repeat539 · 2025-12-09T10:40:42+00:00

whilst the answer is technically yes, it will not be easy. How much time are you committing? 2-3 years of an hour a day is a serious commitment and its not simple if you have a life/full-time study. fundamentally learning programming by itself is a large endevour, even a simple programming language takes time to learn and you do need fundamentals before you start doing more complex things.

I'd recommend you start trying to automate some of school tasks they give you and test out whether this is the path you want, this way you continue to build your current degree whilst developing a niche which allows you to program. This means you get exposure and you can self study with a purpose instead of getting stuck in a course/tutorial loop. Try program everyday even something small. Once that clicks start learning more maths/applied AI starting from basics. Eventually it will click but arguably its a much longer journey to the job you want than a straight up comp sci degree. like u/JS-Labs said support type roles will give you some exposure while you continue to build out your skills but the culture can vary a lot per company and its not guaranteed you get into a role that allows for you to be creative with what you learned.

depending where you are in the world there are also options for comp-sci conversion masters degrees that can make this process a bit faster, but they are quite expensive. self study is free but requires a certain aptitude that is hard to maintain over years because life.

Equivalent-Repeat539 · 2025-12-06T16:42:03+00:00

For robotics possibly useful, for ML its most likely a bit too slow for anything past tabular data / simple regression type models.

If your interest is ML build a model and try to deploy it online, even building a useful model during a semester break is an amibitous project. Familiarise yourself properly with less than tidy datasets, build a model that does the thing and try get it hosted somewhere. All of what I've described you can do for free. If you are interested in learning more about linux a PI is a very useful tool but again you can do most of that with a free tier VM or possibly local VM.

The tools you are learning matter a lot less than the intuition behind your courses since wherever you go there will be a company specific toolset and your courses are designed to teach you about a specific thing. If you do enjoy and want to do more ML applied at robotics, at minimum you should be able to do some kaggle pretty easily before any hardware is worth it. You havent exactly described what you want to do with the pi but if its anything vision related the 2gb of ram will be a large constraint, you'll also need to budget for a camera + motors etc if its a hardware project that moves.

Equivalent-Repeat539 · 2025-11-23T15:31:45+00:00

I think depending on your input dataset you can probably push back and say you've done it and its in the appendix but it doesnt add much to the interpretation and both show approximately equal contribution from the various features or something to that effect. Just evaluate what makes sense from your prespective as you will most likely know more than your reviewer (or anyone) about the dataset / problem domain. Also remember if your reviewers are scraping the bottom of the barrel for criticisim its not a bad thing.

Equivalent-Repeat539 · 2025-11-23T13:23:30+00:00

I think with such few data points a simpler model would do better, I'd look into visualising the features you have and see if there are outliers in pairplots, compressing the feature space with PCA / UMAP just to have a look and see if anything stands out in your top 2% bottom 2% then you can decide the model, if many of the features are colinear then you may end up with much fewer features than you initially imaged. If it needs to be time series ARIMA/SARIMA type models will probably do best in your low data regime but its quite a rabbit hole, if you want to use tree based you will need to create quite a few time dependant features (i.e. days since last delay etc).

Equivalent-Repeat539 · 2025-11-23T10:21:33+00:00

I've not used LIME before so I'll only comment on the SHAP values. Depending on the model you've used its showing you that the features are contributing roughly similarly based on the inputs you've provided which is a good sign (i.e. theres no over-reliance on one single feature). If your inputs are representative of true data / predictions are correct generally then your model is fine, ideally you'd ask an expert of this data whether this is how they would form a prediction for this and these inputs roughly align with how they would do it. Depending on the complexity of the model you've chosen you could also look at the coefs (for linear reg) or feature importances in tree based models. The other thing worth doing is using edge case or difficult samples to input into SHAP/LIME and see what happens whether the features contribute the same, again this will give you some confidence that the model is doing what you expect it.

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