# 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.

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## 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

1. Pick **one** real user or **one** delightful constraint. Narrow beats broad.
2. Hide the prompt engineering. The user gives intent; your app supplies the
   craft (style scaffolding, presets, a LoRA).
3. Make the output **consistent** — that's what a LoRA buys you, and what makes
   it read as a product.
4. 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.