# esimov/pigo

Fast face detection, pupil/eyes localization and facial landmark points detection library in pure Go.

Repository: https://github.com/esimov/pigo
Canonical: https://ross.abutalabs.com/products/pigo
Language: Go
License: MIT
License Family: permissive
Topics: face-detection, computer-vision, machine-learning, golang, opencv, pixel-intensity-comparison, pupil-detection, eye-detection, facial-landmarks, wasm, webassembly
Last push: 2025-05-03T15:07:42+00:00

## Health v2 (maintenance only)
Score: 31/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 19, release rhythm 8, longevity 100
- inputs: {"age_days": 3033, "days_push": 487, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4728, forks 326 (observed 2026-08-28T04:08:57.636467+00:00)

## What it is
Pigo is a pure Go library for fast face detection, pupil/eye localization, and facial landmark detection based on the Pixel Intensity Comparison-based Object detection paper. It requires no OpenCV or third-party dependencies and also supports WebAssembly.

## Use cases
- detect faces in images without installing OpenCV
- localize pupils and eyes in photos
- detect facial landmark points
- run face detection in the browser via WebAssembly
- detect in-plane rotated faces
- build real-time face detection applications in Go

## When to choose
- you need face detection in Go without cgo or OpenCV dependencies
- performance matters and C bindings introduce latency
- you want pupil/eye or landmark detection alongside face detection
- you need WebAssembly support for browser-based detection

## When to avoid
- you need general object detection beyond faces (not yet supported)
- you need a full computer vision suite like OpenCV
- your stack is not Go or WebAssembly

## Facets
- artifact type: library
- maturity: stable
- function: computer-vision, image-processing, machine-learning
- domain: computer-vision, image-processing, machine-learning
- platform: go, cross-platform, wasm
- tags: face-detection, pupil-detection, facial-landmarks, pure-go, no-opencv, pixel-intensity-comparison

## Member repositories
- esimov/pigo (main) score 31

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:57.636467+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 2026-08-29T18:19:03.159462+00:00, confidence not recorded.
  - readme: https://github.com/esimov/pigo (fetched 2026-08-28T04:08:57.636467+00:00, sha 64d9f88fb3c1)
- Data as of 2026-08-30T08:39:29.467469+00:00.