Offline AI food recognition and nutrition diary for Android
BunnyNutri is a functional Android offline-first MVP for visual food logging and orientative nutrition tracking. The app uses an on-device LiteRT/Google AIY Food Classifier V1 model to suggest a food label from a photo. The user remains in control: they can confirm or correct the food, portion, preparation, oil and sauces before saving a meal. A small local USDA FoodData Central catalogue is used to calculate orientative calories, protein, carbohydrates, fat and fiber. Core features include a local Room/SQLite meal diary, optional local meal photos, CameraX and Android Photo Picker integration, and JSON export that does not expose private photo paths. The project is designed to work offline and does not require a backend or cloud account. Tech stack: Kotlin, Jetpack Compose, Material 3, CameraX, Room/SQLite, LiteRT/TFLite runtime, Gradle Wrapper and Android SDK target 37. The package includes the complete source code, debug APK, unsigned release APK, tests, QA screenshots, documentation, license notices and checksums. Current status: pre-revenue, no active users, no live store listing and no signed commercial APK. This is an MVP/starter product for a buyer who wants to continue development, branding, validation or commercialization. Nutrition values are estimates for general tracking and are not medical advice; the app does not claim exact calories, gram-level measurement, ingredients or allergen detection.
Next step: <p>A buyer can continue product validation and UX polish, add more foods and languages, improve the estimation catalogue and onboarding, prepare a signed commercial build, publish to Google Play, add optional backend/sync features, and develop a compliant commercial and marketing strategy. The current MVP is offline-first and does not make medical claims.</p>
For sale
Asking price: $50 USD
What's included
Source code, All related design work
The sale includes the complete BunnyNutri source code, debug APK, unsigned release APK, documentation, tests, QA screenshots, icon/wordmark, license notices and checksums. No domain, social accounts, email accounts or user data are included; the project is pre-revenue with no active users.
Reason for selling
I am offering this functional MVP to a buyer who wants to continue development, validation, branding or commercialization.
Project metrics
Average Monthly Visitors: Pre-launch
Average Monthly Revenue: Pre-revenue
Average Monthly Downloads: Pre-launch / New project
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