# hunterloftis/pbr

a Physically Based Renderer (PBR) in Go

Repository: https://github.com/hunterloftis/pbr
Canonical: https://ross.abutalabs.com/products/hunterloftis-pbr
Language: Go
License: MIT
License Family: permissive
Last push: 2018-09-10T00:37:13+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3365, "days_push": 2915, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1152, forks 41 (observed 2026-08-28T04:03:47.263717+00:00)

## What it is
A Physically Based Renderer (PBR) implemented as a Go library, providing a unidirectional CPU-only Monte Carlo path tracer. It includes a standalone CLI and supports Wavefront .obj/.mtl meshes, .hdri environment maps, physically-based materials, cameras, and progressive rendering.

## Use cases
- render photorealistic 3d images from obj scenes in go
- cpu path tracer for physically based rendering
- render 3d models with metalness roughness materials
- progressive monte carlo rendering of hdri-lit scenes
- command line tool to render wavefront obj files
- learn how a path tracer works in go

## When to choose
- you need a pure-Go, dependency-light path tracer
- you want to render .obj scenes with physically based materials from the CLI or Go code
- you're learning how PBR and Monte Carlo path tracing work

## When to avoid
- you need GPU-accelerated or real-time rendering
- you need an actively developed renderer with recent releases
- you need production-grade features like distributed rendering or complex scene graphs

## Facets
- artifact type: library
- maturity: maintenance
- function: graphics, simulation, cli
- domain: graphics, developer-tools
- platform: go, cross-platform, cli
- tags: path-tracing, physically-based-rendering, monte-carlo, 3d-rendering, cpu-rendering, game-development

## Member repositories
- hunterloftis/pbr (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:47.263717+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 2026-08-30T06:33:33.323150+00:00, confidence not recorded.
  - readme: https://github.com/hunterloftis/pbr (fetched 2026-08-28T04:03:47.263717+00:00, sha dc32a7a86193)
- Data as of 2026-08-30T08:39:29.467469+00:00.