The idea behind Pixel2Motion — that minimal smooth geometry IS animatable geometry — is doing real work in the demos. The CueRecord fitting strip, where the teal overlays march toward a clean C-mark before any motion is authored, makes the geometry-first discipline visible. Most logo animation tools skip that discipline and jump straight to keyframes on traced outlines; the fact that you enforce structural QA before choreography means the resulting SVGs actually hold up as editable vectors, not just as one-shot renders.
@nolangz
I set up an online entry point where anyone can upload a raster logo and run the pixel-to-motion pipeline directly — no clone, no local environment. A designer browsing your repo can try the full workflow here and get back the SVG + animated HTML + GIF preview without installing Python scripts or setting up the Codex/Claude environment.
Every run through that entry point leaves a usage record on Socialistic: what logos people upload, which reveal patterns they ask for, where the fitting iterations stall. That signal is hard to get from a GitHub Pages showcase alone — the static demo shows what the skill can produce, but it doesn't show you what real users actually try to feed it.
The five logos in the gallery are strong proof cases, but they're all clean geometric marks. Usage records would show whether people are throwing in photographic logos, hand-drawn sketches, or wordmark-only inputs — the kind of edge-case distribution that sharpens the complexity ladder and smoothness gate over time.
Feel free to close this if it's not relevant.
shesonglin@tinkerland.ai
The idea behind Pixel2Motion — that minimal smooth geometry IS animatable geometry — is doing real work in the demos. The CueRecord fitting strip, where the teal overlays march toward a clean C-mark before any motion is authored, makes the geometry-first discipline visible. Most logo animation tools skip that discipline and jump straight to keyframes on traced outlines; the fact that you enforce structural QA before choreography means the resulting SVGs actually hold up as editable vectors, not just as one-shot renders.
@nolangz
I set up an online entry point where anyone can upload a raster logo and run the pixel-to-motion pipeline directly — no clone, no local environment. A designer browsing your repo can try the full workflow here and get back the SVG + animated HTML + GIF preview without installing Python scripts or setting up the Codex/Claude environment.
Every run through that entry point leaves a usage record on Socialistic: what logos people upload, which reveal patterns they ask for, where the fitting iterations stall. That signal is hard to get from a GitHub Pages showcase alone — the static demo shows what the skill can produce, but it doesn't show you what real users actually try to feed it.
The five logos in the gallery are strong proof cases, but they're all clean geometric marks. Usage records would show whether people are throwing in photographic logos, hand-drawn sketches, or wordmark-only inputs — the kind of edge-case distribution that sharpens the complexity ladder and smoothness gate over time.
Feel free to close this if it's not relevant.
shesonglin@tinkerland.ai