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Project 11 - Jul 16, 2026

Reddy-Fit Body Scanner

Open the link, look at the camera — AI estimates your body fat % in seconds, and every daily selfie becomes a data point

A camera-first body composition tracker. The front camera opens on page load, MediaPipe Pose finds 33 body landmarks entirely in the browser, and the app fuses the peer-reviewed Deurenberg equation (height, weight, age, sex) with a visual hip-to-shoulder ratio read from the live video to estimate body fat percentage. Take a selfie and log your weight every day — each entry is a labeled data point (image + weight + estimate) stored via a FastAPI backend in SQLite and mirrored to Azure Blob Storage, building a personal dataset that charts your progress and can later fine-tune a real vision model.

🔴 Try the Live Demo View on GitHub

Tech Stack

MP
MediaPipe Pose

33 landmarks, 100% in-browser

PY
FastAPI + SQLite

Daily entries API

AZ
Azure Blob Storage

Selfie dataset mirror

RW
Railway + Docker

One-command deploy

The Problem

Tracking body composition is high-friction:

  • DEXA scans cost $50-150 per visit and need appointments
  • Smart scales are inconsistent and can't see body shape
  • A bathroom-scale number hides recomposition — losing fat while gaining muscle looks like "no progress"
  • No daily feedback loop means motivation dies in week two
  • Sending body photos to cloud AI services is a privacy nightmare

The Solution

Make the camera the measuring tape:

  • Passwordless login — email + 6-digit OTP, then the camera does the rest
  • Pose analysis runs in the browser; video never leaves the device for inference
  • Deurenberg BMI equation + hip/shoulder ratio from live landmarks = instant estimate
  • One selfie + weight per day per user — before/after comparison across any two days
  • Chart.js trend of body fat % vs weight makes recomposition visible

The Daily Loop

  • Open — front camera starts, skeleton overlay confirms the AI sees you
  • Scan — MediaPipe Pose extracts shoulder and hip landmarks in real time
  • Estimate — Deurenberg baseline from your numbers, adjusted ±6% by torso shape ratio
  • Log — save selfie + today's weight; FastAPI writes SQLite + mirrors the image to Azure Blob
  • Track — dual-axis chart plots body fat % and weight, one point per day
  • Learn — the labeled selfie archive becomes training data for a personalized vision model

By the Numbers

  • 33 body landmarks tracked in real time
  • 0 video frames sent to a server for analysis
  • <3s from page load to first estimate
  • 1 labeled data point per day (selfie + weight + estimate)
  • 2 storage tiers: SQLite + Azure Blob mirror
  • $0 inference cost — the model runs on your device

Scan Yourself

Grab the code and run it locally, or deploy your own instance to Railway in one command. Estimates are for personal fitness tracking — not a medical measurement.

🔴 Try the Live Demo View on GitHub