Nose ID: I Taught an AI to Recognize Dogs by Their Nose-Print

Rimsha Shehzadi — Mon, 17 Aug 2026 06:54:15 +0000

What I Built

Nose ID — a biometric dog identification system. Instead of a collar
tag, chip scanner, or manual lookup, it identifies a dog the way security
systems identify people: from a unique physical trait. In this case, the
dog's nose-print — the ridge and texture pattern on a dog's nose, which is
as individual to each dog as a fingerprint is to a human.

Scan a dog's nose → the system tells you who it is (with a spoken voice
response) or offers to enroll it if it's new.

Demo

How It Works

1. Embedding extraction (the core ML piece)
Rather than training a nose-print classifier from scratch, I used a
pretrained MobileNetV2 (ImageNet weights) as a feature extractor,
stripping its classification head and using the penultimate layer's
pooled output as a 1280-dimensional embedding vector. This is a standard
transfer-learning technique — mid-level CNN filters trained on general
images still respond well to texture, edges, and ridge patterns, which is
exactly what distinguishes one nose-print from another.

2. Matching
Each enrolled dog's embedding is L2-normalized and stored. A new scan's
embedding is compared against all stored ones using cosine similarity.
A similarity above a tuned threshold (0.90) counts as a match.

3. AI-generated personality
On enrollment, Google Gemini generates a short, fun bio for each dog
from its name and breed.

4. Voice confirmation
On identification, ElevenLabs turns the result into a spoken response
— "Welcome back, Bella. Access granted." or "I don't recognize this nose.
Would you like to enroll?"

Tech Stack

Frontend: React (Vite)
Backend: FastAPI (Python)
ML: PyTorch, pretrained MobileNetV2, cosine similarity matching
Google Gemini — dog bio generation
ElevenLabs — text-to-speech voice confirmation

Challenges I Ran Into

Both Gemini and ElevenLabs changed parts of their APIs the same week I
built this:

Google's new API key format required switching from the legacy generateContent endpoint to their new Interactions API.
ElevenLabs' free tier restricts which voices are callable via the API, even though the full library shows in their dashboard — had to query /v1/voices to find one my account could actually use.

Try It

rimsha-shehzadi98 / Nose_Print

React + Vite

This template provides a minimal setup to get React working in Vite with HMR and some ESLint rules.

Currently, two official plugins are available:

@vitejs/plugin-react uses Oxc
@vitejs/plugin-react-swc uses SWC

React Compiler

The React Compiler is not enabled on this template because of its impact on dev & build performances. To add it, see this documentation.

Expanding the ESLint configuration

If you are developing a production application, we recommend using TypeScript with type-aware lint rules enabled. Check out the TS template for information on how to integrate TypeScript and typescript-eslint in your project.

View on GitHub

Prize Categories

Best use of Google AI
Best use of ElevenLabs

DEV Community: Rimsha Shehzadi