Do I need background removal for the clothing photos?

Not for version one. A square crop on a plain surface looks fine in a grid, and shipping without background removal saves you an image-processing dependency and a per-image API cost. Add it later as a paid perk if users ask — and they will tell you clearly whether they care.

Where should the photos be stored?

On the device, in the app's document directory, with only the file path in your database. A hundred clothing photos is tens of megabytes, which is nothing locally and a real hosting bill in the cloud. Add optional cloud backup once people have enough items to fear losing them.

How to Build a Wardrobe Planner App with AI (2026)

What a wardrobe planner app needs

Photograph an item and auto-crop it onto a plain background
Tag by category, colour, season, and occasion
Build outfits by dragging saved items together
Plan outfits onto a calendar for the week ahead
Wear counts, cost-per-wear, and a "never worn" list

The screens

Screen	What it does
Closet	Grid of every item, filtered by category, colour, or season
Add Item	Camera, crop, then category, colour, brand, and price
Item Detail	Wear history, cost-per-wear, outfits it appears in
Outfits	Saved outfits as collages, with the occasion they suit
Plan	Week calendar — assign an outfit to a day, mark it worn
Insights	Most and least worn, unworn over 90 days, spend by category

The data model

Item: photoUri, category, colour, brand, price, season, purchasedAt
Outfit: name, itemIds, occasion, coverPhotoUri
WearLog: itemId, outfitId, date
PlannedDay: date, outfitId, weather (optional)

The build prompt (copy this)

Paste this into ShipNative and it becomes a working React Native app with these screens, navigable in a live preview, in about two minutes:

“A wardrobe planner app. Users photograph each clothing item, tag it with category, colour, brand, price and season, and browse everything as a filterable grid. They combine saved items into outfits shown as collages, and assign outfits to days on a week calendar. Marking a day as worn writes a wear log entry for every item in that outfit, which drives per-item wear counts and cost-per-wear. An Insights screen lists most-worn, least-worn, and anything unworn for over 90 days, plus spend by category. Screens: Closet, Add Item, Item Detail, Outfits, Plan, Insights. Photos stay on the device; everything works offline.”

Then iterate with small, screen-specific prompts (“make the primary button bigger”, “add an empty state”), preview on your own phone, and export the full Expo project whenever you want. The full method: how to build an app with AI.

How it makes money

Freemium with a cap — around 30 items free, unlimited on a subscription of $3-5/mo. The cap works here because a user only feels the value once a real portion of their closet is in the app, and by then re-photographing everything elsewhere is a genuine cost. Resist charging for the insights: that is the screen that sells the subscription.

Implementation and the revenue math for every model: how to make money from an app. When you’re ready to ship: App Store and Google Play publishing guides.

Build it now

The prompt above is free to run at shipnative.dev — working wardrobe planner app on your phone today, full code export, no credit card.

How to Build a Wardrobe Planner App with AI