u/Sensiburner

Since december I've been pretty addicted to AI coding with the frontier models. When I got my seestar S30 pro 2 weeks ago I pretty much set it up in station mode on the second night; and asked gpt 5.6 in codex to see if it could control the telescope. It just asked me to install the official app on my mac mini (which is online 24/7 and reachable with my phone over codex remote). It needed some key code from the official app to communicate with the telescope.

I'm pretty new to astrophotography so I just put the telescope on my flat roof, then sent gpt 5.6 a screenshot from google maps of my house & the spot the telescope was at, mentioning which side would be blocked by my other roof.
It basically figured out all the rest by itself. Now it gives me a list for good targets & I can plan missions with it during the day that it carries out by itself at night (I do ofc still have to power on the scope & align it.).

So I got like a week of cloudy skies after that. In the mean time I made some back end pipeline with gpt 5.6 so it could also do the post processing stuff by itself. I'm going to have it explain what it does because I only understand half of it:

>Our current process For your Crescent data, I used this sequence: Raw-frame quality filtering Measured star count, FWHM, ellipticity, saturation, background brightness and noise. Of 340 FITS frames, 18 were rejected for poor FWHM, leaving 322.

>Debayering Siril debayered the raw CFA frames using the GRBG pattern recorded in their FITS headers.

>Registration Two-pass star registration, Lanczos-4 interpolation and center-of-gravity framing. The latter preserves more field with an alt-az telescope’s field rotation.

>Stacking Average stack with additive normalization plus scaling, RGB output equalization, and Winsorized Sigma Clipping at 3σ/3σ. This rejects satellite trails and other transient pixels.

>Background extraction Conservative GraXpert RBF subtraction with smoothing 0.85, intended to remove Merelbeke’s uneven light-pollution gradient without inventing structure.

>Denoising Siril NL-Bayes at restrained modulation 0.35.

>Stretching Two linked-channel Siril autostretches: Conservative: shadow parameter −2.8, background 0.16 Stronger: −2.5, background 0.24

>Export Linear master FITS, processed linear FITS, stretched FITS, 16-bit TIFF, full-resolution PNG/JPEG and comparison sheet.

The results I'm currently getting are not bad, but also not very great. Seems the post processing is way better with some human touch, but I'm just starting out with this.

I also just pre-ordered the S50 pro. I'm looking very much forward to having a small AI controlled seestar army on my rooftop. Surely, I'm not the first to try this? If you have any tips or need some help yourself with setting this up, leave a comment.

https://preview.redd.it/guy7qd8dgmbh1.png?width=959&format=png&auto=webp&s=c21162eca43e785e6c18d98b0081deee8fde80ad

Ik ben toegekomen met de fiets en iemand bood mij haar karretje aan. Dan ben ik op 6-8 minuten door de colruyt geraakt en gemakkelijk aan alle producten geraakt zonder zever. Enkel in de gekoelde afdeling kwam er ineens zo'n gigantische transpalet af. Toen ik bij de kassa kwam deden ze ineens niet één maar direct twee extra kassa's open. En als ik mijn boel net in mijn fietskar gestoken had op de parking, kwam er een bakfiets koppel toe met kindjes waar ik mijn karretje bij heb kunnen achterlaten. 10/10 colruyt run tbh.

edit: ben vergeten zeggen dat ze direct mijn leeggoed hebben gedaan van zodra ik binnenkwam.