This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass
What I Built
Grasshopper turns a walk into a tiny side quest. Tap one button and a local Gemma model writes five things to find nearby, from easy ("a bicycle") to hard ("finding a rickshaw with grafiti").
Tell it where you are and the quests get local: in Jhansi, mine included a decorated
auto-rickshaw and a hand-painted shop sign.
Then the phone goes back in your pocket. When you spot something, snap it, and an
open-source vision model checks the photo right on your phone. No upload, no signal needed.
The screen is just a checklist; the walk is the point.
It's for anyone who opens their phone "for a second" on a walk and spent the whole walk glued to their phones. It makes every day walks around your city more enjoyable.
Taking it outside:
Ok that was from claude, i actually tried it, out in my walk, it worked pretty well, it was fun, to actually click photos of things i can actually find in my locality.
The finding a guy in a lungi, cycling around, was a quest i really enjoyed lol i went out with my sister, and we laughed so much finding A photo like that.
Yes, but its not perfect, CLIP got some wrong,, like one time it could really tell what the image uploaded represents, but that was only once.
Demo
Code
How I Built It
- Gemma 3 (4B), running locally with Ollama. It writes the quests. An Express + TypeScript server asks for exactly five, constrained to a JSON schema, so the output is always valid. Gemma tended to miscount the easy/medium/hard split, so the app assigns difficulty by position and lets Gemma focus on what to find.
-
CLIP (
clip-vit-base-patch32) via Transformers.js in a Web Worker. It checks photos in the browser. Each photo is compared against the quest, the other quests, and decoys like "a phone screen" or "the inside of a room", so a picture of your ceiling doesn't count. - IndexedDB keeps quests and photos on the device.
- When CLIP isn't convinced, it says what it thinks it sees ("looks more like a cat to me") and you can count it anyway. The AI suggests; the human decides.
Why Does Open Innovation Matter?
- Your photos stay yours. A walk produces photos of your street, your neighbourhood, maybe your home. With an open model running in the browser, none of them get uploaded.
- It works with no signal. The photo checker downloads once and is cached. Out on a trail or in a dead zone, it still works. A closed vision API would fail exactly when you're outside.
- It costs nothing to run. Both models run on my own hardware: no API key, no per-photo bill, no rate limit.
- I could change the model's behaviour. I could see exactly how Gemma's output was shaped, constrain it to a schema, and swap hosts without rewriting the app.
My Agent Session
Prize Categories
- Best Use of Gemma
- Best Use of Entire





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