# espressif/esp-who

Face detection and recognition framework

Repository: https://github.com/espressif/esp-who
Canonical: https://ross.abutalabs.com/products/esp-who
Language: C++
License: NOASSERTION
License Family: other
Last push: 2026-08-21T15:10:09+00:00

## Health v2 (maintenance only)
Score: 67/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 98, release rhythm 8, longevity 100
- inputs: {"age_days": 2868, "days_push": 12, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2133, forks 547 (observed 2026-08-28T04:06:17.389173+00:00)

## What it is
ESP-WHO is an image processing development platform from Espressif providing face detection, face recognition, pedestrian detection, and QR code recognition examples for ESP32-series chips. It is built on ESP-DL and targets embedded deep learning applications with camera peripherals.

## Use cases
- face detection on esp32
- face recognition embedded device
- pedestrian detection with esp32 camera
- qr code recognition on microcontroller
- run deep learning models on esp32-p4
- build camera-based iot applications

## When to choose
- developing computer vision applications on Espressif chips
- you need on-device face detection or recognition without cloud
- building embedded camera projects with ESP32-P4 or ESP32-S3

## When to avoid
- you need vision on non-Espressif hardware
- you require high-accuracy large-scale models beyond embedded constraints
- you need support for older chips like esp32 or esp32-s2 in the current branch

## Facets
- artifact type: framework
- maturity: active
- function: computer-vision, image-processing, machine-learning, deep-learning
- domain: computer-vision, image-processing, embedded-systems, iot
- platform: embedded, iot, cpp
- tags: esp32, face-detection, face-recognition, espressif, edge-ai, qrcode, pedestrian-detection, esp-dl

## Member repositories
- espressif/esp-who (main) score 67

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:17.389173+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:51:58.130325+00:00, confidence not recorded.
  - readme: https://github.com/espressif/esp-who (fetched 2026-08-28T04:06:17.389173+00:00, sha d3df163ef420)
- Data as of 2026-08-30T08:39:29.467469+00:00.