A newer version of the Gradio SDK is available: 6.19.0
Three starter projects you can fork
Don't ship a thin wrapper around "type prompt → get image." The judges have seen a hundred of those. Each idea below is a real, finishable weekend project that uses klein for something the prompt box alone can't do, maps to one of the two tracks, and stacks merit badges.
The two tracks:
- 🏡 Backyard AI — solve a real problem for someone you know.
- 🍄 Thousand Token Wood — build something delightful and whimsical.
1. 🏡 "Shopfront" — product photos for a tiny business
The problem. A friend sells something handmade (jewelry, candles, baked goods) and their product photos are phone snaps on a cluttered table. Good product photography is expensive.
The build. Image → Image. They upload a plain phone photo of the product; your app re-lights and re-stages it on clean backgrounds — marble, linen, a sunlit windowsill — keeping the product itself intact. Add a row of preset "scenes" so they just click.
Why it's more than a wrapper. It's a focused tool for one real user with preset styling, not a generic prompt box. That's the whole point of Backyard AI.
Badges: 🔌 Off the Grid (runs the open weights), 🎨 Off-Brand (your own UI), 🎯 Well-Tuned if you train a LoRA on their brand look.
Push it further. Train a small LoRA on 20 of their existing on-brand shots so every generated scene matches their aesthetic. Add a "generate 4 variations" grid so they can pick.
2. 🍄 "Sticker Forge" — a whimsical creature/sticker maker
The idea. A playful generator that turns a few words ("a grumpy mushroom knight", "a sleepy cloud cat") into a die-cut sticker: bold outline, flat shading, transparent-ready background.
The build. Text → Image with a baked-in style. The user types just the subject; you append the sticker-style scaffolding to the prompt under the hood so every output is consistent. Show a sheet of 6 at once.
Why it's delightful. Constraint + consistency is what makes it feel like a product, not a demo. Thousand Token Wood rewards charm and polish.
Badges: 🎯 Well-Tuned (train a LoRA so the sticker style is truly yours and not promptable by anyone), 🎨 Off-Brand, 🔌 Off the Grid.
Push it further. Train a sticker-style LoRA from ~25 reference stickers so the look is locked and recognizable. Add post-processing that crops to the subject and adds a white die-cut border.
3. 🏡 / 🍄 "Before & After" — a personal restyle studio
The idea. Upload a photo of a room, an outfit, a garden — and see it restyled. "What would my living room look like in mid-century modern / cottagecore / Scandinavian?" Useful (Backyard) and fun (Wood) depending on how you frame it.
The build. Image → Image with a set of named style presets. Each preset is a curated edit prompt. Show the original and the restyle side by side.
Why it works. The side-by-side is inherently demo-friendly and the presets make it usable by someone non-technical in five seconds.
Badges: 🔌 Off the Grid, 🎨 Off-Brand. 🎯 Well-Tuned if you train a LoRA on one specific aesthetic and make that your app's signature look.
Push it further. Let users save a "look" and apply it across several of their photos so the whole set is consistent — that consistency is the thing a plain prompt can't give them.
The pattern behind all three
- Pick one real user or one delightful constraint. Narrow beats broad.
- Hide the prompt engineering. The user gives intent; your app supplies the craft (style scaffolding, presets, a LoRA).
- Make the output consistent — that's what a LoRA buys you, and what makes it read as a product.
- Show a before/after or a grid. It demos better than a single image.
See TRAIN_A_LORA.md for the LoRA step and PROMPTING.md for getting clean
output. Fork app.py — the three tabs are already wired up.