Touch Grass Bingo - offline nature bingo checked by an AI that lives on your phone

A developer built Touch Grass Bingo, an offline nature bingo web app that uses the open-weight CLIP ViT-B/32 vision model, 8-bit quantized to about 150 MB, running entirely in the phone's browser via Transformers.js on ONNX Runtime Web. Each bingo square is a zero-shot text prompt such as "a photo of an acorn," and a single photo is scored against the season's items plus distractors like screens and indoor rooms, with inference taking roughly 100 ms per photo on a laptop. The app requires no backend or accounts, caches the model in the browser for airplane-mode play, and lets groups share a deterministic card code such as FERN-42.

This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass https://dev.to/challenges/hacktoberfest-week1-2026-10-05 What I Built Touch Grass Bingo is a nature bingo card that you play outside. You open it, get a seasonal card a red leaf, an acorn, moss, a feather, a mushroom… , and put your phone away. When you find something, you take one photo. An open-weight vision model running on your phone checks it and marks the square. The center square is never free. It is "Touch grass" : a photo of your hand on real grass. Who it is for: - Families who want a reason to make a walk last longer. - Run clubs and hiking groups. Everyone types the same card code like FERN-42 and gets the same card. First to bingo wins. There are no accounts and no server. - Anyone doomscrolling who needs a nudge. If you photograph your monitor, the model detects a screen and tells you that you cannot touch grass through a monitor. The screen is the shortest part of the game: one glance at the card, then the phone goes in the pocket until you find something. Demo Play it: https://prateekiiitg56.github.io/touch-grass-bingo/ https://prateekiiitg56.github.io/touch-grass-bingo/ Open it on your phone. Tap Download photo checker once on Wi-Fi about 150 MB . After that, it works in airplane mode. Play the same card as a friend: https://prateekiiitg56.github.io/touch-grass-bingo/?code=FERN-42 https://prateekiiitg56.github.io/touch-grass-bingo/?code=FERN-42 Code Offline nature bingo. Snap what you find outside; open-weight CLIP checks it on your phone. No signal, no uploads. Touch Grass Bingo Offline nature bingo for walks, hikes and run clubs. The app deals you a seasonal bingo card a red leaf, an acorn, moss, a feather… . You go outside and take a photo only when you find a square. An open-weight AI model running on your phone checks the photo. No signal is needed and no photo leaves the device. - Open-weight model: CLIP ViT-B/32 https://huggingface.co/Xenova/clip-vit-base-patch32 ONNX, 8-bit quantized - Open-source runtime: Transformers.js https://github.com/huggingface/transformers.js 3.7.6 on ONNX Runtime Web WASM - No backend: static files only. Host on GitHub Pages, Netlify or any static host. How it works 1. Field kit. On Wi-Fi, tap Download field kit . The model about 150 MB goes into the browser cache. A service worker caches the app shell and runtime. From then on the app works in airplane mode. 2. Deal a card. A card code for example FERN-42 seeds a deterministic shuffle of the season's item… How I Built It - Model: CLIP ViT-B/32 https://huggingface.co/Xenova/clip-vit-base-patch32 , open weights, ONNX export, 8-bit quantized about 150 MB . - Runtime: Transformers.js https://github.com/huggingface/transformers.js on ONNX Runtime Web WASM . Inference runs in the browser tab. - App: plain HTML, CSS and JavaScript modules. No framework, no build step, no backend. Hosted free on GitHub Pages. - Design: styled like a topographic map. Grid references A1, B2… run along the edge of the card, so a group can shout "got B2". A finished line is drawn as an orange trail-blaze route. - Offline: a service worker caches the app shell and runtime. Transformers.js caches the model weights in the browser. After a one-time download on Wi-Fi, the app works in airplane mode. The core trick is zero-shot classification . Each bingo square is only a text prompt, for example "a photo of an acorn" . When you take a photo, CLIP scores it against every item in the season's pool plus a set of distractors a screen, an indoor room, a selfie, a document, a city street . On a laptop, one photo takes about 100 ms: - If the square you tapped wins, you found it. - If a different unfound square on your card wins clearly, the app marks that one as a bonus "Not running water, but it is a mushroom" . - If a seasonal item that is not on your card wins, you get "Good find, but it is not on this card." - If a distractor wins, the find does not count, and you get a hint. My first version scored photos only against the squares on the card. In testing, a red maple leaf was marked as the "yellow leaf" square with 95% confidence, because it was the closest option. Scoring against the full season pool fixed this: the same photo now comes back as "red leaf, not on this card." Group play uses a seeded shuffle: the card code, season and size feed a hash, which seeds a small PRNG that shuffles the season's item pool. Every phone with the same code deals the same card, with no network. Why Does Open Innovation Matter? - It works where the grass is. Trails, parks and forests often have no signal. A closed vision API needs a network round trip for every photo. Open weights let the model live on the phone, so the game works in airplane mode. - Photos stay private. Families take photos of kids' hands, backyards and favorite spots. With an on-device model, no photo is uploaded to a server that the player does not control. - It costs nothing to run. No API key, no per-image bill, no rate limit. I can host it on GitHub Pages for free, and a whole run club can play without anyone paying. - It is easy to change. Because CLIP is zero-shot and open, a new square is one line of text. A teacher can make a "schoolyard" card, a birding club can make a "local birds" card, and anyone can swap in a different open model for example SigLIP by changing one constant. Prize Categories Best Use of Gemma Using Gemma, Google's open-weight model, in building my project