Grass Pass: Photograph to Unlock Reddit
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass What I Built Grass Pass is a Chromium extension (Chrome, Edge, Brave) that blocks the sites you doomscroll on. To get them back, you have to go outside and prove it You maintain a block list (by default, X, Reddit, Instagram, TikTok, Facebook, YouTube). Opening one of such websites takes you to a blocked page…
Grass Pass is a Chromium extension that prevents users from getting stuck on websites they tend to endlessly scroll on. To regain access, users must step outside and prove it by taking photographs. The extension comes with a default block list consisting of popular social media and video platforms such as X, Reddit, Instagram, TikTok, Facebook, and YouTube.
Each blocked site redirects users to a "Go touch grass" page when accessed. This page prompts users to photograph three distinct leaves, either using their phone or webcam, before they can regain access to the restricted site.
The vision model running on users' computers examines each photograph, confirming that it meets the criteria. The default model used is SmolVLM-500M-Instruct, which operates through Transformers.js v3 and WebGPU in the browser. For certain models like Moondream, an optional Ollama backend can be used within the local network, along with an experimental, more accurate tier powered by Qwen2-VL-2B. These models are all connected through a single VisionBackend interface, allowing users to switch between them seamlessly.
Grass Pass prioritizes user privacy as its primary design limitation. Since users must take photographs of their surroundings, this information remains on their device, avoiding the need to upload it to a third-party server. Users only need to download the model weights once from Hugging Face, with no need for accounts, API keys, or paying for server usage.
The open-weight models enable the app to run various vision models without restrictions. However, this comes at the cost of reduced accuracy, as the 500M-parameter model is less precise than more advanced models. To mitigate potential misuse, the design relies on straightforward yes/no questions rather than attempting to counteract determined cheaters.
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