git404hub

what is mneme fr?

bthavanish/mneme — explained in plain English

Analysis updated 2026-05-18

1TypeScriptAudience · vibe coderComplexity · 2/5LicenseSetup · easy

tl;dr

A browser app that uses your webcam to detect and label everyday objects and recognize faces you save, all processed locally with nothing sent to a server.

vibe map

mindmap
  root((Mneme))
    What it does
      Object detection
      Face recognition
      Runs in browser
    Tech stack
      TypeScript
      TensorFlow.js
      face-api
    Use cases
      Live camera demos
      Private face matching
      Static site deploy
    Privacy
      No server
      No accounts
      Local storage only

Code map

Detail Auto

An interactive map of this repo's files and how they connect — its source is parsed live in your browser. Click Visualize to build it.

filefunction / class

what do people make with this?

VIBE 1

Try live object detection through a webcam without installing any app.

VIBE 2

Build a private face recognition demo that never sends data to a server.

VIBE 3

Learn how to run TensorFlow.js models directly in a browser tab.

VIBE 4

Deploy a static, camera-based detection tool to GitHub Pages or any static host.

what's the stack?

TypeScriptViteTensorFlow.jsCOCO-SSDface-api

how it stacks up fr

bthavanish/mneme0xkinno/neuralvault0xmayurrr/ai-contractauditor
Stars111
LanguageTypeScriptTypeScriptTypeScript
Setup difficultyeasyhardeasy
Complexity2/54/52/5
Audiencevibe coderdeveloperdeveloper

Figures from each repo's GitHub metadata at analysis time.

how do i run it?

Difficulty · easy time til it works · 5min

in plain english

Mneme is a browser app that points your webcam at the world and shows you what it sees. It can draw labeled boxes around everyday objects like people, dogs, cars, or cups, and it can recognize faces you have saved yourself. Everything happens inside your browser tab, nothing is sent to a server, and there are no accounts or API keys involved. The app offers two modes that can run separately or together. Object detection uses a model called COCO-SSD, which can identify 80 common types of objects and draw a box with a label around each one it spots. Face recognition works differently: you save a face under a name, and afterward the app tries to match new faces against your saved list, showing anyone it does not recognize as Unknown. You choose whether to run objects only, faces only, or both at once. Under the hood, all of the machine learning runs in the browser using a library called TensorFlow.js, which uses your graphics card through WebGL to keep things fast. Object detection runs faster on desktop computers than on phones, and the same is true for face recognition, which uses a separate library for detecting and comparing faces mathematically. Saved face data is stored locally in the browser's own storage, and the app shows a consent message before it saves anything. To try it, you can visit the hosted website directly, or run it yourself by installing Node.js, running a couple of npm commands, and opening the address it prints in a browser, then allowing camera access. There are also instructions for testing the app on a phone over the same Wi-Fi network, and for building a production version to deploy anywhere static files can be hosted. A settings panel lets you adjust things like confidence thresholds, camera mirroring, and dark mode, or delete all saved face data. The project is released under the Apache 2.0 license.

prompts (copy fr)

prompt 1
Walk me through running Mneme locally with npm install and npm run dev.
prompt 2
Explain how the object detection and face recognition modes work together in this app.
prompt 3
Show me how to test this app on my phone using the same Wi-Fi network.
prompt 4
Help me deploy the production build of this project to GitHub Pages.

Frequently asked questions

what is mneme fr?

A browser app that uses your webcam to detect and label everyday objects and recognize faces you save, all processed locally with nothing sent to a server.

What language is mneme written in?

Mainly TypeScript. The stack also includes TypeScript, Vite, TensorFlow.js.

How hard is mneme to set up?

Setup difficulty is rated easy, with roughly 5min to a first successful run.

Who is mneme for?

Mainly vibe coder.

peek the repo → explain another one

This repo across BitVibe Labs

double-check against the repo, no cap.