lunalisa
Free design-led AI images in one focused studio
What it does
lunalisa is a focused AI image studio for turning prompts and references into polished visual directions. Start with free image generation, explore distinct art-directed styles and aspect ratios, then upgrade for faster 1K–4K output and watermark-free downloads. Dedicated workflows for text-to-image, photo editing, upscaling, background removal and face swap keep creative controls clear, while a curated prompt gallery helps you discover and reuse stronger visual ideas.
Create polished AI images with LunaLisa using GPT Image, 10 aspect ratios, curated visual styles, up to 3 reference images, and flexible output controls.
Create free 1K images without signing in, then use credits for 1-4 images at up to 4K. Explore distinct design directions. Hover over any image to reveal its prompt, then make it unmistakably yours. The essential choices stay close to the prompt, so experimentation remains quick and deliberate. Shape subject, material, light, and mood in one focused writing surface. Switch between fast drafts, balanced renders, and detail-first passes. Move from square studies to landscape and portrait formats without rebuilding the prompt. Generate up to four directions together and compare the visual language at a glance. Load cinematic, editorial, surreal, minimal, analog, or sculptural language in one…from lunalisa.art
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Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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