August 5, 2026
Brush strokes and blunt takes
Painting with Gaussians
This coder taught a computer to paint, and the comments got wonderfully messy
TLDR: A developer built a tool that turns photos into painting-like images by following the picture’s outlines instead of blindly guessing. Commenters were split between cheering the clever approach, suggesting a simpler AI shortcut, and roasting the sample images for possibly making the results look better than they are.
A developer showed off a wild experiment: instead of having a computer "guess" its way toward a painted-looking image, they used the picture’s own outlines and shapes to decide where digital brush marks should go. In plain English, the program tries to follow the natural borders in a photo so the result looks more like a hand-made painting and less like a blurry filter. The creator also took a swipe at slower trial-and-error methods, basically saying, why let the machine fumble around when the image is already telling you where the details are?
And the comments? A tiny but delightfully chaotic art-school critique session. One camp was pure applause — "Very cool" and "Super impressive results" energy — the kind of supportive cheering that makes indie tech demos feel like mini movie premieres. But then came the spicy side-eye. One commenter essentially asked, why do all this hidden-art-teacher work at all? Why not just train an image model on paintings and be done with it? That instantly turned the post into a classic tech culture split: clever handcrafted approach versus "just use AI" shortcuts.
Then came the funniest jab of the thread: a deadpan complaint that the sample images were "mostly bokeh" — a brutally concise way of saying the examples might be doing the demo some favors. Another commenter rolled in with a humblebrag-meets-show-and-tell about their own brush-stroke project and a lone Mona Lisa gif, which is exactly the kind of nerdy one-upmanship the internet lives for. In other words: cool invention, but the real painting was in the comments
Key Points
- •The article builds on a prior edge-aware pixelation tool by reusing image edge information to guide digital painting.
- •Edges are presented as a source of information for stroke placement, scale, and orientation because they indicate boundaries and detail density.
- •The proposed brush-stroke representation is a 2D Gaussian splat with parameters for position, shape, rotation, color, and opacity.
- •The article contrasts its edge-guided method with prior Gaussian-painting systems that rely on gradient descent to fit splats to an image.
- •An initial attempt using a reference rasterizer with additive blending is reported to work poorly when thousands of splats are seeded directly rather than optimized.