WiFi DensePose: WiFi-based dense human pose estimation system through walls (github.com)

Putting "privacy first" as the first bullet point on something like this sure is rich.

The dense AI docs say a lot to convey little, both the user guide and deployment guide do little to explain what's needed on the router side.

For example, their diagram has several CSI sources. Does the user need 3 or more CSI sources?

I'm capable of pointing an LLM at a GitHub repository, what I want is real documentation written by a human to address users' needs, not emoji-filled docs that read like ad copy.

> The WiFi-DensePose project represents a framework/prototype rather than a functional WiFi-based pose detection system. While the architecture is excellent and deployment-ready, the core functionality requiring WiFi signal processing and pose estimation is largely unimplemented.

> Current State: Sophisticated mock system with professional infrastructure Required Work: Significant development to implement actual WiFi-based pose detection Estimated Effort: Major development effort required for core functionality

> The codebase provides an excellent foundation for building a WiFi-based pose detection system, but substantial additional work is needed to implement the core signal processing and machine learning components.

https://github.com/ruvnet/wifi-densepose/tree/main/docs/revi...

Over 1k stars. Has a single person tried running it? Even the author?

I've learned that if the project describes itself as "Production-ready", it was definitely vibe-coded.

The Docker repository and PyPi packages in the README link to nowhere. There are only 3 issues. Is this legitimate?

After trying to click through some of the docs and realizing most of those sections don’t exist, I checked the commit log. I can confidently say there is a lot of AI slop in here. Anyone who has watched one of the AI coding tools add imaginary sounds-good features to a project and draw useless diagrams in README files will recognize it.

So now the question is: Does this repo actually contain anything useful at all? Or is it just one big AI vibecoding project that amassed 1.3K stars based on sounding really amazing from the README? I’m leaning toward the latter.

There are no usable instructions for actually trying this out, as far as I can see. It does claim to have a section for deploying and scaling with Kubernetes, which is hilarious for something that is supposedly working with WiFi routers.

I’m continually amazed at how much leverage people are getting out of letting vibecoding tools run absolutely wild and then posting it to GitHub. I wouldn’t be surprised if the author was leveraging this in job interviews based on the almost certainly correct assumption that many interviewers will assume it’s real without checking anything. This kind of trick won’t work at a real company or with a serious hiring manager, but if you can impress a recruiter and get in front of a checked out hiring manager who just wants to build their empire this kind of thing can work. For a while.

EDIT: This has 123 forks!? Now I’m going down the rabbit hole of exploring all of the other vibecoding and spam accounts that are forking this. This is a weird chapter in GitHub development.

This whole repository is a bunch of vibe-coded boilerplate that doesn’t include almost any of the core thing it claims to do. The README is generic slop and the “performance metrics” (“Pose Detection Accuracy”; “Person Tracking Accuracy”) appear to be completely invented / hallucinated. In other words, it isn’t real.