Contact person: AI Food Calorie Estimator App

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Location: HONG KONG, France

Budget: Recommended by industry experts

Time to start: As soon as possible

Project description:
"I’m building “CalorieSnap,” a cross-platform mobile application that lets people snap or upload a photo of any meal, instantly see an estimated calorie count, view a macronutrient breakdown, and save the entry to a personal food log. The goal is a fast, intuitive experience that works equally well on iOS and Android.

Here’s what I need you to deliver:

• A polished mobile app for both iOS and Android with seamless camera capture and gallery import.
• An on-device or hybrid AI pipeline (TensorFlow Lite, Core ML, or a comparable framework) that recognises common foods, estimates portion size, and returns calories plus basic nutritional insights.
• A persistent food log where each analysed photo is stored, editable, and totals are aggregated by day.
• Optional but welcome: a lightweight backend (Firebase, Supabase, Django, or Node) to sync data across devices and enable simple account management.
• Full source code, model files, build instructions, and a short screen-recorded walkthrough.

Acceptance criteria
• Calorie estimation accuracy within ±15 % for at least 1,000 popular dishes.
• Camera and gallery workflows complete in under five seconds on a mid-range device.
• Logged meals can be created, updated, and deleted, with daily calorie totals visible at a glance.

Share any relevant computer-vision or nutrition-tracking projects you’ve delivered, the stack you prefer, and how long you’d need to get to an MVP. Let’s create something that makes healthy eating effortless." (client-provided description)