berkus
/
wifi-densepose
mirror of https://github.com/ruvnet/wifi-densepose.git
1
0
Fork 0
Code Issues Packages Projects Releases Wiki Activity

docs: Update README with Google Colab instructions 

Added a new section to the README providing step-by-step instructions on how to run the project virtually using Google Colab. This includes
guidance on obtaining ngrok tokens, setting up the environment, and accessing the UI.
This commit is contained in:
Amaan Ahmad 2026-06-03 11:45:34 +05:30 committed by GitHub
parent 6f0030b231
commit fb9ab94f97
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
1 changed files with 14 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

14
README.md
View File

@ -38,6 +38,20 @@ The system learns each environment locally using spiking neural networks that ad
RuView turns ordinary WiFi into a contactless sensor. A $9 ESP32 board reads the radio reflections off the people in a room, and a small pretrained model — published on Hugging Face at [`ruvnet/wifi-densepose-pretrained`](https://huggingface.co/ruvnet/wifi-densepose-pretrained) — tells you who's there, how they're breathing, and how their heart rate is trending. The model fits in 8 KB (4-bit quantized) and runs in microseconds on a Raspberry Pi. (The [v2 encoder](https://huggingface.co/ruvnet/wifi-densepose-pretrained) reports an honest, label-free held-out **temporal-triplet accuracy of 82.3%** — up from 66.4% raw; the older "100% presence" figure was measured on a single-class recording and has been retracted in favor of this.) No cameras, no wearables, no app on the user's phone.
## Run `RuView` in Google Colab
Experience `RuView` virtually using Google Colab. This notebook sets up and runs the `wifi-densepose-sensing-server` in a cloud environment.
[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ruvnet/RuView/blob/main/path/to/your/notebook.ipynb) <!-- IMPORTANT: Replace `path/to/your/notebook.ipynb` with the actual path to your Colab notebook in this repo -->
### Quick Start:
1. **Open the Colab Notebook** using the badge above.
2. **Obtain an ngrok Auth Token** from [ngrok.com](https://dashboard.ngrok.com/get-started/your-authtoken) and paste it into `NGROK_AUTH_TOKEN` in Cell 0.
3. **Run All Cells** (`Runtime` > `Run all`).
4. After Cell 6 provides a "Public URL", copy the hostname (e.g., `example.ngrok-free.dev`) and update `NGROK_HOST` in Cell 5 with it. Re-run Cell 5 and subsequent cells.
5. **Access the UI** via the ngrok public URL displayed in Cell 6.
### Built for low-power edge applications
[Edge modules](#edge-intelligence-adr-041) are small programs that run directly on the ESP32 sensor — no internet needed, no cloud fees, instant response.