UniEvent
UniEvent is the on-ramp I wish I'd had.
Core trick
One call converts any event-camera (x, y, t, p) stream into spike, voxel, frame, or graph representations through a canonical format.
Description
UniEvent is the on-ramp I wish I'd had. It's an open-source suite that turns the hardest sensor in computer
vision to get into — the event (neuromorphic) camera — into something you can see, understand, and build with in
a single sitting.
The problem: event cameras are the most exciting sensor in vision (microsecond latency, HDR, sparse, milliwatt
power) and the hardest to enter. Every dataset speaks its own format, the raw data looks like noise, and there's
no single place where a newcomer watches what an event stream is, feels why representation matters, and walks
out holding a real tool. That fragmentation slows research and locks learners out.
The suite, two legs: (1) the library — pip install, one import, any event stream (x,y,t,p) → every
representation (spike · voxel · frame · graph · time-surface) from a single call, with an enforced integrity
rule and real CC0 data; (2) the Labs — a scroll "zero-to-hero journey" that teaches event vision from first
principles and renders the library's real output. The thing that teaches you is the thing you build with.
It's research + education + open-source infrastructure in one: unification, visualization, and a bridge from raw
events to AI-ready representations — the on-ramp the field never had.
README excerpt
<div align="center"> # UniEvent ### One suite. Zero to hero — for event-based (neuromorphic) vision. <a href="https://uni-event-yazan-inquire.vercel.app"><img src="docs/hero.png" alt="UniEvent — real event stream as an orbitable space-time point cloud" width="860"></a> **Any event-camera recording → one canonical `(x, y, t, p)` stream → spike · voxel · frame · graph, from a single call.** ```python import unievent as ue ue.represent(stream, as_="frame") # spike · voxel · frame · graph — one call, any stream ``` ### [**▶ Open the live experience →**](https://uni-event-yazan-inquire.vercel.app) <sub><img src="docs/claude-mark.svg" width="15" align="top"> Built with **Claude** (Opus 4.8) · 🟠 **Anthropic Build Day** · San Francisco · 13 Jun 2026 · @Shack15</sub> </div> --- > **Why this exists.** Event cameras are the most exciting sensor in computer vision — microsecond latency, HDR, sparse, power-sipping — and the hardest to *get into*: no on-ramp where a newcomer sees what an event stream *is*, feels why the representation matters, and walks out building with a real tool. **UniEvent is that on-ramp** — research-and-education infrastructure: one problem → one solution, taught from first principles, available for noncommercial research. > > Built by **Yazan** ([@INQUIRELAB](https://github.com/INQUIRELAB)) — PhD researcher and educator in neuromorphic, event-based vision. *(An Event-Vision-to-AI textbook is on the way from our INQUIRE.ai team.)* ## Two legs, one sui