惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

博客园 - 聂微东
Y
Y Combinator Blog
WordPress大学
WordPress大学
L
LangChain Blog
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
A
About on SuperTechFans
小众软件
小众软件
有赞技术团队
有赞技术团队
S
SegmentFault 最新的问题
宝玉的分享
宝玉的分享
Recent Announcements
Recent Announcements
GbyAI
GbyAI
I
InfoQ
The GitHub Blog
The GitHub Blog
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
酷 壳 – CoolShell
酷 壳 – CoolShell
罗磊的独立博客
C
Check Point Blog
V
V2EX
Apple Machine Learning Research
Apple Machine Learning Research
月光博客
月光博客
量子位
雷峰网
雷峰网
Hugging Face - Blog
Hugging Face - Blog

Hacker News: Show HN

PurrrrrFocus: Pomodoro Timer App - App Store Workflow Engine — Multi-Step Orchestration for Bun RapidPhoto: Pro Photo Editor App - App Store GitHub - DheerG/swarms: Achieve extraordinary results with claude code across a variety of tasks SPICE simulation → oscilloscope → verification with Claude Code — Lucas Gerads Show HN: VCoding – A 5 MB native Windows IDE with no dynamic dependencies Show HN: LLMs don't hallucinate because they're bad at math, it's the format GitHub - Agent-FM/agentfm-core: AgentFM is a peer-to-peer network that turns everyday computers into a decentralized AI supercomputer. AgentFM lets you run massive AI workloads directly across a global mesh of idle CPUs and GPUs. Show HN: Tracking Top US Science Olympiad Alumni over Last 25 Years GitHub - Potarix/agent-hub: One place to talk to all your agents Show HN: Runtime security for AI agents(injection,tool abuse, data exfiltration) GitHub - dubeyKartikay/lazyspotify: Terminal Spotify client for macOS and Linux GitHub - the-banana-tool/king-louie: Easy to use GUI Personal AI Assistant. Win/Linux/Mac. Show HN I made my vacation rental bookable by AI agents–no Airbnb, 0% commission GitHub - basteez/jsf-autoreload: maven plugin to enable hot reload on jsf projects uvm32/hosts/host-gdbstub at main · ringtailsoftware/uvm32 GitHub - labsai/EDDI: Config-driven engine that turns JSON into production-grade AI agents. Multi-agent orchestration, 12+ LLM providers, MCP/A2A protocols, RAG, persistent memory, and enterprise compliance (EU AI Act, GDPR, HIPAA). Built on Quarkus. GitHub - glitchnsec/fortyone-oss: AI Executive Assistant Platform Quickstart | Alien GitHub - muxshed/shed: One stream in, or many. Every destination, simultaneously. No cloud middleman, no per-channel fees, no limits. GitHub - ocrbase-hq/ocrbase: 📄 PDF/IMG ->.MD/JSON Document OCR API for PaddleOCR and GLMOCR. Self-hostable. GitHub - impactjo/home-memory: MCP server that lets your AI assistant remember everything about your home. GitHub - Sets88/dbcls: DbCls is a powerful terminal database client that supports various databases GitHub - neptun2000/heor-agent-mcp GitHub - SeanFDZ/macmind: Single-layer transformer in HyperTalk for the classic Macintosh RollQuation: Math Puzzles - Apps on Google Play GitHub - dropbox/witchcraft Show HN: Agent-cache – Multi-tier LLM/tool/session caching for Valkey and Redis GitHub - opentalon/opentalon: OpenTalon is an open-source platform built from the ground up in Go as a robust alternative to OpenClaw LinkedIn™ 职位抓取工具 - Chrome 应用商店
GitHub - themartiano/luz: C++ Path Tracer from scratch wi...
martiano · 2026-06-15 · via Hacker News: Show HN

Luz is a C++20 Path Tracer developed from scratch with zero third-party dependencies.

It supports Monte Carlo path tracing, global illumination, BVH acceleration, adaptive sampling, denoising, atmospheric scattering, custom scene files, and a Blender-to-Luz exporter.

Features

  • Monte Carlo path tracing
  • Global illumination
  • Multithreaded CPU rendering
  • Adaptive sampling
  • Denoiser (NFOR-style)
  • Spheres, planes, rectangles, triangles, cubes, volumes, and OBJ meshes
  • Lambertian, metal, dielectric, emissive, and isotropic materials
  • Area, point, sphere and directional lights
  • Custom .luz scene files
  • .blend to .luz converter
  • Fully customizable render parameters via CLI or scene file
  • Importance sampling with PDFs
  • BVH acceleration, including packed mesh BVHs with binned SAH construction and near-first traversal
  • Atmospheric simulation w/ scattering
  • Depth of field, antialiasing, exposure, contrast, tone mapping, gamma correction, and bloom
  • BMP and TIFF output
  • Deterministic benchmark harness with render, denoise, post-process, and score breakdowns

Requirements

  • C++20 compiler
  • Make or CMake 3.16+
  • Python 3, only for optional tools/scripts

Quick Start

Build with the Makefile:

Render a bundled example scene:

./Luz --file examples/scenes/blender_monkey.luz --samples 50 --resolution 300x300

The default output is render.bmp. Scene files can set outputfilename=..., and the CLI can override common render settings.

Run the test suite:

Benchmarking

Luz includes deterministic benchmarks for render, denoise, post-process, and overall score comparisons.

make benchmark BENCH_CPUS=1 BENCH_THREADS=1 > before.csv
make benchmark BENCH_CPUS=1 BENCH_THREADS=1 > after.csv
make benchmark-compare BEFORE=before.csv AFTER=after.csv

For details, see docs/benchmarks.md.

CMake

A CMake build is also available:

cmake -S . -B build
cmake --build build
ctest --test-dir build

Platform Support

Supported platforms:

  • macOS
  • Linux
  • Windows

On macOS and Linux, the Makefile is the primary path. On Windows, use CMake with MSVC or the MinGW-based Makefile target:

WSL is also supported as a Linux build environment.

Build Optimizations

Release builds are tuned for the machine doing the build by default. The Makefile enables -O3, native CPU tuning with -march=native, and link-time optimization with -flto. It also enables a fast floating-point mode where the compiler/platform supports it. CMake uses the same release intent: -O3, native CPU tuning, and interprocedural optimization/LTO when supported.

These defaults produce faster local renders, but binaries built with -march=native may not run on older or different CPUs, and LTO can expose toolchain-specific linker issues. If you hit an illegal-instruction crash, linker error, or need a more portable binary, disable the aggressive options and rebuild from clean objects:

make clean
make NATIVE=0 LTO=0

For CMake builds, configure with the optimization toggles off:

cmake -S . -B build -DLUZ_NATIVE_OPTIMIZATIONS=OFF -DLUZ_ENABLE_LTO=OFF
cmake --build build --clean-first

CLI

Usage: ./Luz [options]

  -f, --file PATH             Load a .luz scene file
  -r, --resolution WxH        Override render resolution
  -s, --samples N             Override samples per pixel
  --adaptive [true|false]     Enable adaptive per-pixel sampling
  --no-adaptive               Disable adaptive sampling
  --adaptive-min-samples N    Minimum samples before adaptive stopping
  --adaptive-threshold F      Relative adaptive noise threshold
  --adaptive-check-interval N Adaptive convergence check interval
  -mlb, --maxLightBounces N   Override maximum light bounces
      --max-light-bounces N   Alias for --maxLightBounces
  -t, --threads N             Render with N worker threads
  --seed N                    Seed random sampling
  --gamma true|false          Toggle gamma correction
  -tm, --tonemapping true|false  Toggle tone mapping
  --bloom true|false          Toggle bloom
  --exposure EV              Exposure compensation in stops
  --contrast F               Display contrast multiplier
  --denoise [true|false]      Write a denoised companion render
  --no-denoise                Disable denoising
  -o, --output PATH           Override render output path
  --denoise-output PATH       Override denoised output path
  --render-times              Write renderTime.bmp
  --benchmark                 Run the built-in benchmark scene
  --benchmark-case NAME       Benchmark case: default, many-objects, mesh-bvh, diffuse, postprocess, atmosphere, lights, emissive-geometry, primitives-materials, volumes, obj-mesh

Adaptive Sampling

--adaptive treats --samples as the maximum samples per pixel. Each pixel uses a progressive per-pixel sample sequence, renders at least --adaptive-min-samples, then periodically checks luminance and RGB confidence intervals. Very dark pixels use a conservative minimum before they can stop, so rare light contributions are less likely to be mistaken for converged black.

Lower thresholds keep more detail and cost more time. For final renders, start with a high max sample count and tune with values like:

./Luz --file exports/stormtroopers.luz --samples 4096 --adaptive --adaptive-min-samples 512 --adaptive-check-interval 64 --adaptive-threshold 0.005 --denoise

Denoising

--denoise enables Luz's NFOR-style feature-buffer denoiser and writes a separate companion image. By default, render.bmp becomes render_denoised.bmp; use --denoise-output PATH to choose the exact path.

The denoiser has no hard minimum resolution or sample count, but it needs enough signal to estimate useful color and feature statistics. One sample per pixel is mainly a stress test: there is no per-pixel variance estimate, so the denoised image can look almost unchanged or can smooth the wrong details. Use at least a few samples per pixel for previews, and prefer roughly 16+ samples per pixel when judging denoiser quality. Very low resolutions also make evaluation misleading because each local filter window covers too much of the image.

Scene Files

Example scenes live in examples/scenes/. Mesh assets live in assets/objects/. The scene-file format is documented in docs/scene-files.md.

Object paths in .luz files are resolved relative to the scene file first, then relative to the current working directory, then under assets/objects/. This means examples/scenes/blender_monkey.luz can reference ../../assets/objects/blender_monkey.obj and still run from the repository root.

OBJ meshes can also be offset and assigned a scene material:

obj=mesh.obj,(x,y,z),material[
metal=(0.8,0.8,0.8),0.1
]

Blender Exporter

Blender scenes can be exported through Blender's Python API:

"/Applications/Blender.app/Contents/MacOS/Blender" -b scene.blend --python tools/blender_export_luz.py -- --output exports/scene.luz
./Luz --file exports/scene.luz --threads 8

The exporter writes a .luz file plus OBJ meshes. Usage and current fidelity limits are documented in docs/blender-exporter.md.

Repository Layout

include/luz/       Public headers
src/core/          Math, geometry, materials, image, and sampling code
src/renderer/      Rendering implementation
src/scene/         Scene model and scene helpers
src/io/            Scene-file, OBJ, BMP, and TIFF loading/writing
src/cli/           Command-line entry point and flags
examples/scenes/   Example .luz scene files
assets/objects/    OBJ assets used by examples
docs/images/       Compressed showcase images
tools/             Export and utility scripts
tests/             Standard-library-only test program
docker/            Benchmark container

Showcase

Personal Note

Special thanks to the Ray Tracing in One Weekend book series. It was a great source of inspiration and information during a big part of the development of Luz, specially since those were times before AI.

Attribution

Stormtrooper Scene by @ScottGraham on BlendSwap.

Bust Statue by @geoffreymarchal on BlendSwap.

License

MIT. See LICENSE.