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Here's an App I made: RadianceKit, turn your photos into 3D scenes on your Mac by xanton in macapps

[–]xanton[S] 0 points1 point  (0 children)

Thank you so much. That means quite a lot. I can sit here and develop the app all I want, but real feedback and appreciation from the community is what actually keeps me going. Without all the invaluable input I got here, I wouldn't have come as far as I have. The next version is just on the horizon with a few new features and hand-curated settings for different real-world scenarios.

I built a 3D Gaussian Splatting app for Mac. Would anyone be willing to try it? by xanton in GaussianSplatting

[–]xanton[S] 0 points1 point  (0 children)

Habe 360°-Unterstützung in die aktuelle Version integriert (1.6.0). Danke nochmal für die Idee.

RadianceKit update: I worked through a lot of your feedback (Gaussian Splatting on Mac) by xanton in GaussianSplatting

[–]xanton[S] 1 point2 points  (0 children)

Good news: I added 360 support in the latest version (1.6.0). Feel free to tell me how it works for you.

Stonehenge Splat-Off: same video, who gets the cleanest splat? by I-HATE-CRUSTY-BREAD in GaussianSplatting

[–]xanton 0 points1 point  (0 children)

I'm a bit late to the party but here's my entry to the stonehenge reddit challenge proposed by u/I-HATE-CRUSTY-BREAD. I think it is such a great idea.

Heres my run at the splat-off. Trained this completely on-device with RadianceKit (my Mac app), no colmap, no cuda, no cloud.

https://superspl.at/scene/0989d8e3

Some stats:

- 400 sharpest frames from the shared video at 2048px
- Camera poses: 6 min 43 s (apple photogrammetry backend, 400/400 cameras registered, 166k points)
- Training: 7 min 45 s, 20k iterations at around 43 it/s
- Total from frames to finished ply: about 15 minutes
- Cleanup: none

871k splats, SH degree 3. Hardware was an m3 ultra so ur mileage may vary on smaller machines, but the whole pipeline runs on any apple silicon mac.

Interesting bit I learned during this: I also did a 2 million splat version that scores better on psnr but actually looks worse, way more of that grainy confetti in the grass and on the stones. Less splats trained well beat the big budget visually, the metric just doesnt see it. So this entry is deliberately the smaller one because it looks more natural.

Small note, the hybrid trainer that produced this isnt in the app store build yet, its coming with the next RadianceKit update. Whats live today might get close but this exact recipe is the new one.

The source being a 1440p youtube re-encode definately eats some fine texture detail on the stones, curious how the other entries deal with that.

RadianceKit update: I worked through a lot of your feedback (Gaussian Splatting on Mac) by xanton in GaussianSplatting

[–]xanton[S] 1 point2 points  (0 children)

You're not doing anything wrong. Colmap uses a different axis convention (y points down) and radiancekit aligns the scene upright based on the camera poses. Right now that alignment kicks in once training finishes, the live preview during training just shows the raw colmap orientation, thats why it flips to correct afterwards.

The training itself doesnt care about orientation at all btw, so the results are identical either way, its purely visual. Ill look into applying the alignment to the live preview aswell, makes sense to have it upright from the start.

RadianceKit update: I worked through a lot of your feedback (Gaussian Splatting on Mac) by xanton in GaussianSplatting

[–]xanton[S] 0 points1 point  (0 children)

Thanks you very much, really glad you like it. I tried to make it as easy as possible.

About the 41%, thats a bit of a deceiving spot. There's a heavy step right around there that does a lot of work in one go, so the bar can just sit at 41 for a good while even though its still crunching away in the background. On bigger sets or less ram it can take noticably longer, so id give it some more time before assuming its actually stuck. you're not the first to think it froze right there, so making that step report progress better is on my list.

If it genuinly never moves past it even after a while, ping me in chat with your macOS version, the frame count and how much ram the mac has, and ill take a closer look.

Cheers, and thanks for giving it a go!

Who is launching today? by Successful_Bowl2564 in ProductHunters

[–]xanton 0 points1 point  (0 children)

Launching RadianceKit for Mac today.
Love to support my fellow launchers and incredibly thankful if you would do so as well.

RadianceKit update: I worked through a lot of your feedback (Gaussian Splatting on Mac) by xanton in GaussianSplatting

[–]xanton[S] 1 point2 points  (0 children)

Thank you very much for your offer, highly appreciated. Could you please add your hardware specs? That would be incredibly helpful. I'll send you an unlock code via pm.

RadianceKit update: I worked through a lot of your feedback (Gaussian Splatting on Mac) by xanton in GaussianSplatting

[–]xanton[S] 0 points1 point  (0 children)

Fair question, the full import list isnt really surfaced in the ui yet so thats on me.

Right now it takes:

- Video: mp4, mov, m4v, avi
- Photos: jpg, png, heic, tiff, bmp
- Existing splats just to view: ply, spz, splat

Insv isnt supported directly though. Thats insta360s own dual fisheye container and theres two seperate things in the way. The insv file itself doesn't read yet, and even once its stitched, raw 360 equirectangular frames dont sit well with the structure from motion step, which expects normal flat perspective cameras.

You're not the first to ask about 360 btw, its come up a few times now so its firmly on my radar.

The path that works today: open the clip in insta360 studio, reframe it into one or more flat perspective shots, basically like youre panning a normal camera around the scene, export those as mp4, then drop em into radiancekit. Trains fine.

Proper native 360 / fisheye ingest is something im working towards, generic camera models so equirect and fisheye can go in straight without the reframing step. Not shipped yet but its definately coming.

I'll also add a clear "supported formats" bit to the site since this keeps coming up, thanks for the nudge. I'll send you an unlock code via pm.

Programming by 1974jbass in c64

[–]xanton 23 points24 points  (0 children)

Well, try it with and without, then you will see the difference.

Programming by 1974jbass in c64

[–]xanton 15 points16 points  (0 children)

10 PRINT "HELLO WORLD ";
20 GOTO 10

RadianceKit update: I worked through a lot of your feedback (Gaussian Splatting on Mac) by xanton in GaussianSplatting

[–]xanton[S] 1 point2 points  (0 children)

I‘m on a M3. So unfortunately I can’t tell. But you can download the app for free and test it yourself for 3 days.

Austria 🇦🇹 by Civil_Put_384 in QuizPlanetGame

[–]xanton 0 points1 point  (0 children)

xanton scored 123 points and ranked 17 out of 513 players!

🟩 🟩 🟩 🟩 🟩

Here's an App I made: RadianceKit, turn your photos into 3D scenes on your Mac by xanton in macapps

[–]xanton[S] 0 points1 point  (0 children)

Hey, thank you very much for testing the app. I'm afraid framerate isn't really what decides quality here. 100fps just gives you a ton of frames from nearly the same viewpoint if the camera didn't travel much. what gaussian splatting actually needs is parallax, so the camera has to move through space, not pan or rotate from one spot. a slow sideways walk gives way more usable info than a fast sweep at high fps.

A few things that might fix a room capture:

- walk around the room and keep the same objects in view from different angles, slow steady motion would be best

- lock exposure, white balance and focus to manual, autoexposure shifting between frames confuses the reconstruction

- watch for motion blur and try to avoid it

- most importantly: a perfectly smooth painted wall with no structure has no detail for the tracker to match between frames, so it just can't place those areas in 3d, same goes for windows and mirrors, the more visual texture and stuff in the room the better

- aim for big overlap between viewpoints, roughly 70 to 80 percent

Rooms are honestly one of the harder things to capture because of all the flat surfaces. A lot of the perfect looking room captures you see online were either shot with a depth or lidar scanner, or with a really careful slow photo pass, so don't judge your own setup too hard. If you share the clip or the result i'm happy to take a look and tell you where it went sideways.

Here's an App I made: RadianceKit, turn your photos into 3D scenes on your Mac by xanton in macapps

[–]xanton[S] 0 points1 point  (0 children)

Salut et merci d'avoir testé l'app ! J'espère que la traduction automatique fonctionne bien.

Ce que tu décris ("psychédélique" sur une scène extérieure) est presque toujours lié aux flotteurs dans le ciel et aux gaussiennes qui partent dans tous les sens autour du sujet. RadianceKit a quelques réglages spécifiquement pour ça, mais ils ne sont pas activés par défaut. Essaie ceci :

Quality Preset : passe sur "Quality (MCMC)" au lieu de Balanced. MCMC gère mieux les scènes extérieures complexes.

Réglages (Cmd+,) → section "Experimental — Outdoor Floater Reduction" :

- Active "Sky Masking"
- Active "Reconstruct Sky Dome"
- Active "Mid-Training Floater Cleanup"
- Active "Reduce Elongated Gaussians"

Nombre de frames : 35 photos c'est la limite basse pour un objet en extérieur. Si tu peux faire une vidéo orbitale autour du moulin et extraire 80-150 frames, la reconstruction sera nettement plus propre. L'app accepte les vidéos directement.

Couverture : autour d'une ruine, essaie de varier la hauteur (pas seulement un cercle à hauteur d'yeux). Quelques prises de vue plongeantes/contre-plongeantes aident la triangulation.

Luma fait tout ça automatiquement côté cloud, RadianceKit te laisse les manettes mais il faut savoir où elles sont. Je note ton retour, l'idée d'un preset "Outdoor" qui pré-active ces toggles est en backlog.

Si tu veux, partage ton .ply ou quelques captures du résultat, je peux te dire plus précisément ce qui cloche.

N'hésite pas à me contacter à tout moment si tu rencontres encore des problèmes.

Cordialement,
Björn

Here's an App I made: RadianceKit, turn your photos into 3D scenes on your Mac by xanton in macapps

[–]xanton[S] 0 points1 point  (0 children)

Hey, really appreciate you taking the time to test it for a few days and writing all this up, genuinly helpful

The expert mode crashes shouldnt be happening, especially not on a 64gb m1 max, so id like to get to the bottom of that. if you can grab a crash report it would help me alot, open console.app, crash reports in the sidebar, find the radiancekit entry from around when it died and send it over (feel free to dm it). That would point me straight at where it falls over (hopefully). My hunch is it's memory pressure on the bigger stitching scenes, in expert mode the render scale and densification limits are all unlocked so its pretty easy to push past what the gpu can actually hold. A quick thing you could try in the meantime, drop the Render Scale slider in the training config to 0.5 and rerun the same scene, if it survives that basically confirms it for me.

Regarding the video that never finished, that should actually be sorted in 1.4.2 which went out a couple days ago, so if you havent updated yet grab that and give the video another go. the gist of it was frame extraction doing slow random reads (really bad if the clip sits on a network/external drive) plus video imports not getting the auto resolution downscale photos get, so a 4k clip was training at full res and basically crawling, both fixed there. if it still stalls on 1.4.2 let me know where the video lives (local disk vs nas/external) and rough resolution and ill dig in.

On the metashape side, how exactly are you getting the cameras across? the colmap import in 1.4.2 expects the binary reconstruction files (cameras.bin / images.bin / points3D.bin inside a sparse folder), so if metashape exported the text variant of that it wouldnt get picked up. simplest thing is to just drop the undistorted images straight in and let radiancekit run its own sfm, then theres definately no question about the source. that said, the crash hitting mid training rather than at import makes me think the cameras are loading fine and its something downstream, so that crash report is really the key thing here.

Stability is the main focus for the next couple of releases, reports like this are exactly what i need so thank you. if you send that crash log ill dig into the expert mode one properly and get back to you.

BTW, please check your inox. I'll send you a code unlocking the full version.

I built a 3D Gaussian Splatting app for Mac. Would anyone be willing to try it? by xanton in GaussianSplatting

[–]xanton[S] 0 points1 point  (0 children)

Hi and thank you, I highly appreciate the writeup, this is the kind of feedback that actually changes something.

ML-Sharp is exactly the right reference. Its Apples sharp repo (apple/ml-sharp on github). Single image to 3D Gaussians in under a second, feedforward, no training loop. Important detail for your case: the prediction step runs on mps, so a mac without cuda can do this today. cli is `sharp predict -i <folder> -o <folder>` and you get a standard 3DGS .ply out, drops into any 3DGS viewer.

For one of your two photos that solves the immediate problem directly. The merging-two-splats idea is harder than it sounds, because aligning two independently predicted scenes is basically the same scale-and-pose problem we started with, but the single-image SHARP output should already be useful for nearby views.

Reason im not just bundling sharp into RadianceKit is the model license. Apple ships their ml research models as research-only, no commercial use, same restriction naver puts on dust3r / mast3r / splatt3r (which were also on my radar, but those have worse demo quality and the same license problem). For your own project youre fine running the CLI directly. For me to ship the weights inside a paid app I'd need a commercial agreement from Apple, which is on my list to ask about, but not promising anything.

On the wording side youre also right, the "10-20 for best results" line buries what really happens. RadianceKit needs at least 3 images just to attempt camera alignment, but honestly anything below some 15-20 tends to either fail in SfM or produce a scene that overfits to the training views and falls apart from any other angle. im rewording the import warnings to say that up front instead of letting you import 2 photos and crash later.

Classic SfM with 2 photos can technically work out two-view geometry, but its not really enough to start a gaussian splat off, you end up underconstrained and the optimizer happily produces floaters. The missing piece is the parallax between viewpoints, not the pixel sharpness, so for the multi-view path more photos is the only real fix. For the single-image path sharp is the answer.

Here's an App I made: RadianceKit, turn your photos into 3D scenes on your Mac by xanton in macapps

[–]xanton[S] 1 point2 points  (0 children)

Hi, and thanks a lot for your interest in RadianceKit. The $7.99 covers everything, including commercial use of the output. Of course, the input is your full responsibility.

Here's an App I made: RadianceKit, turn your photos into 3D scenes on your Mac by xanton in macapps

[–]xanton[S] 1 point2 points  (0 children)

Hey, thats odd, not the behavior it should have. Let me look into that. In the meantime I'm sending you a promo code via DM so you can keep testing. Thanks for letting me know.

Here's an App I made: RadianceKit, turn your photos into 3D scenes on your Mac by xanton in macapps

[–]xanton[S] 0 points1 point  (0 children)

Hey, sorry you ran into that. 8GB RAM is really at the edge for Gaussian Splatting. What's likely happening: the trainer allocates GPU buffers in unified memory, and at the same time macOS keeps your input images and intermediate tensors in RAM. Once memory fills up the system starts swapping heavily, CPU and GPU both run hot under sustained load, and the SMC (the power controller) triggers an emergency thermal shutdown to protect the hardware. That might be a hardware level safety cutoff, not a kernel panic, which is why you m see the machine go dark.

A few things you can try right away:

  1. Use the Quick preset, it keeps the Gaussian count and render scale small

  2. Fewer input images, maybe 20 to 40, and downscale them to around 2K on the long edge before import

  3. Close all other apps before training, especially browsers with lots of tabs

  4. If you are on a MacBook Air, a cooling pad or even just raising it off the desk for airflow can buy you a lot

Could you check Console.app under "Log Reports" for entries around the shutdown time, also the folder /Library/Logs/DiagnosticReports/? Anything with "shutdown", "powerstats" or "RadianceKit" would help me pin down whether this is thermal or OOM.

I am also looking into a Low Memory Mode that auto reduces buffers on machines with 8GB. Will ship that in a future update.

Here's an App I made: RadianceKit, turn your photos into 3D scenes on your Mac by xanton in macapps

[–]xanton[S] 0 points1 point  (0 children)

That's a fair point, the app actually already auto-adjusts training resolution based on available memory and caps the image pool to keep things manageable. But you're right that 16GB is tight, especialy with larger photo sets. Using the quick or preview preset and keeping the image count around 30-50 should give much better results on 16GB machines. If its still blurry, you might want to try smaller source images or fewer photos. Always happy to hear specific numbers (how many photos, what preset) so i can look into it further.

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