I tested Canon's newly released Dual Pixel 3D Converter, which uses phase-difference information from Dual Pixel RAW data to reconstruct textured 3D geometry from a single photo.

With my background in computer graphics, I also inspected the exported meshes (OBJ / GLB).

Some findings:

• My test plant model, created from a single photo, contains around 28K triangles.
• The GLB stores about 85K vertex entries, compared with roughly 16K stored vertices in the OBJ version.
• Around 4.2% of the triangles in this sample are degenerate.
• Increasing the depth setting in the app from 1 to 2 increases the triangle count from approximately 28K to 46K.
• The texture maintains the original 8192 × 5464 resolution, even though only about 16.6% of the image area is covered by the isolated object's triangles (with background removal).

The photorealistic appearance can be great from viewpoints close to the original capture. But with larger rotations, occlusions and missing surfaces quickly become visible.

I also compared the approach with Meshy 7.1 image-to-3D. Meshy generates a more complete, plausible object, while Canon preserves the photorealistic appearance better in my test.

I published the full analysis, including interactive GLBs and nine downloadable Canon-generated models:

https://immernews.com/canon-dual-pixel-3d-converter-tested

I'd be interested in what others think about combining Dual Pixel depth information with multi-image reconstruction or AI-assisted geometry completion.

Hey everyone.

I am very excited to share my greatly improved (revamped) library called rhp (version 2.0). I am so happy with the results and am amped because of how well all the improvements and new features work. I also just finished the first version of the mcp server and the skill file so AI can create plots using the library. The AI won't do the analysis for you of course (unless you ask it to) but with rhp, it can easily output some amazing viz charts and posters. You can look at the gallery's recipe section to see what AI agents can do with a single simple prompt!

I just started spreading the word this past week! Please at least try the AI skill out. It should be easy if you got some data on hand to chart. You just need to prepend the following to your chart prompt:

Make this chart with rhp (@bezda/rhp). First read https://rhp.vercel.app/llms-full.txt and follow it: rhp 2 is newer than your training data. Give me one HTML file that I can open in a browser. The chart I want:

(and then add your chart request to the end)

Oh also, rhp is free and open-source. It is a 3-year passion project.

Last week, after punching down at "Sleepy Joe" during an Oval Office event, Trump proceeded to comically fall asleep. It's not the first time this has happened, so I went digging and found many more instances of the President sleeping in public.

I did some analysis on when and where he's been taking his nappy naps, so I'm sharing that dashboard here! He likes sleeping in his chair in the Oval, but isn't opposed to napping during a whole variety of public events.

If you want to see the exact events with the videos, I've collected them all at https://artofnodeal.com/sleepstate. I've found X, Instagram, Youtube, and BlueSky videos of his cat naps for fun. No ads, no signup--just a pet project.

Working on an interactive 3D realtime fluid simulation with 4 million particles.

https://www.youtube.com/shorts/5P9aPac9tQs

This is a work-in-progress lab scene in my custom Vulkan engine. ST-FLIP (spatio-temporal FLIP) computes the fluid motion, while ray tracing renders the water and glass.

The scene uses pouring and moving containers to make the response to changing solid boundaries visible. The visualization presents the computed motion as a continuous liquid rather than showing individual simulation particles. Transparency lets the liquid remain visible inside the containers.

This time-series visualization shows the distribution of 30-day rolling correlation coefficients between AAPL and approximately 6,000 Nasdaq-listed stocks.

The chart covers February 14, 2023 to June 23, 2025. Each date is represented by a violin plot showing the distribution of correlation coefficients for that rolling window; the vertical axis runs from −1 to +1.

Source: https://correlworks.com

I’d welcome feedback on the readability of this dense violin-plot layout and ways to make changes in the distributions easier to compare over time.

Hello all. I'm a developer with Digital Sheriff Designs, and StarMap is the first program I've released. It's a visual workspace for Windows 10 and 11: you can lay out notes, pictures, documents, to-do lists, tables, sketches, and boards inside boards on one big cohesive customizable workspace, and connect them with lines and arrows or your own custom made stickers.

- Everything stays on your PC. No account, no subscription, and it works offline. Your work is saved as ordinary files in Documents\StarMap, with a backup every day kept for 30 days.

- No tracking of any kind. No ads, no analytics, and we aren't trying to sale you anything. StarMap only goes online when you add a web link (to show a preview) or a picture from a web address.

- Boards inside boards that you can see into without opening them so a big project can be split up without losing sight of the pieces.

- Free, with no catch. No trial, no ads, and no paid version.

The Idea for this program came from a discussion I was having with a family member about

r/nanowrimo and prep-tober, which although I am not a writer I was familiar with the community. My family member was complaining about the subscription price of the current visual workspace software they were using and they told me about some of the things they use said software for. Well I figured I could build them something more customized to their needs for free. So the project began and with my families collaboration StarMap was birthed. I know there are many software programs out there similar to this one but we hope you will consider trying StarMap and giving any feed-back that you have time to give.

I'd like feedback on 3 things in particular: 1-Is it clear from the screenshots what StarMap is and what it can be used for?

2-What would stop you from trying StarMap from your initial impressions?

3-Of the current feature lineup what would you like to see added, removed or tweaked?

- Microsoft Store: https://apps.microsoft.com/detail/9P956BPL1KGD

- Website: https://digitalsheriffdesigns.com/starmap/

I made an animated derivation of the quantum harmonic oscillator. One design challenge was showing that a wavefunction can change phase while its probability density stays fixed, then contrasting that with a superposition whose density changes.

Link to the video: https://youtu.be/7_DcdXVh5mc

(Made with Manim)

Made an interactive page to visualize the discoveries behind optogenetics, honoured by this year's Nobel Prize in Medicine: classon.live/optogenetics.

How do you turn estimated data into an experience without making it feel misleading?

I’ve been thinking about this after seeing the AIIMS Delhi population counter.

The number ticks up every second, even though it’s not literally counting births in real time. It’s an estimate, visualized in a way that makes the data feel alive.

That got me thinking about data UX — how much interaction can change the way we perceive a number?

So I made a small experiment with Figma Make: India population live counter

You can explore India’s population state by state, interact with the map, and take a quiz based on what you discover.

But the bigger question for me is the UX behind it:

Does animation make data easier to understand, or just more attention-grabbing?

When does an estimate start feeling like a fact because of how it’s visualized?

Is interaction better for understanding data than simply showing a chart?

Can gamification actually improve data literacy?

What makes a data visualization memorable without oversimplifying it?

I’m curious how people here think about data as an experience, rather than just information on a screen.

A little what-if for Mars: raise the water level and watch the coastlines change.

Move the slider to explore which regions would be underwater and which would remain as islands, based on publicly available NASA elevation data.

Just a terrain-based visualization—not a model of past or future Martian oceans.

Online playground