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This document provides an overview of two powerful libraries: Apache POI, a Java library for manipulating Microsoft Office files, and Mitsuba 3, a research-oriented rendering system. Apache POI supports various formats, while Mitsuba 3 offers advanced features like differentiable rendering and GPU acceleration. Both are valuable tools for different application domains.

Apache POI™

A Java library for reading and writing Microsoft Office binary and OOXML file formats.

The Apache POI Project's mission is to create and maintain Java APIs for manipulating various file formats based upon the Office Open XML standards (OOXML) and Microsoft's OLE 2 Compound Document format (OLE2). In short, you can read and write MS Excel files using Java. In addition, you can read and write MS Word and MS PowerPoint files using Java. Apache POI is your Java Excel solution (for Excel 97-2008). We have a complete API for porting other OOXML and OLE2 formats and welcome others to participate.

OLE2 files include most Microsoft Office files such as XLS, DOC, and PPT as well as MFC serialization API based file formats. The project provides APIs for the OLE2 Filesystem (POIFS) and OLE2 Document Properties (HPSF).

Office OpenXML Format is the new standards based XML file format found in Microsoft Office 2007 and 2008. This includes XLSX, DOCX and PPTX. The project provides a low level API to support the Open Packaging Conventions using openxml4j.

For each MS Office application there exists a component module that attempts to provide a common high level Java api to both OLE2 and OOXML document formats. This is most developed for Excel workbooks (SS=HSSF+XSSF). Work is progressing for Word documents (WP=HWPF+XWPF) and PowerPoint presentations (SL=HSLF+XSLF).

The project has some support for Outlook (HSMF). Microsoft opened the specifications to this format in October 2007. We would welcome contributions.

There are also projects for Visio (HDGF and XDGF), TNEF (HMEF), and Publisher (HPBF).

This library includes the following components, roughly in descending order of maturity:

And lower-level, supporting components:

Getting started

Website: https://poi.apache.org/

Mailing lists:

Bug tracker:

Source code:

Requires Java 1.8 or later.

Contributing

Building jar files

To build the jar files for poi, poi-ooxml, poi-ooxml-lite, poi-ooxml-full and poi-examples:

example:

Mitsuba Renderer 3

Documentation	Tutorial videos	Linux	MacOS	Windows	PyPI

️

Warning

️

There currently is a large amount of undocumented and unstable work going on in

the master branch. We'd highly recommend you use our

latest release

until further notice.

If you already want to try out the upcoming changes, please have a look at

this porting guide.

It should cover most of the new features and breaking changes that are coming.

Introduction

Mitsuba 3 is a research-oriented rendering system for forward and inverse light

transport simulation developed at EPFL in Switzerland.

It consists of a core library and a set of plugins that implement functionality

ranging from materials and light sources to complete rendering algorithms.

Mitsuba 3 is retargetable: this means that the underlying implementations and

data structures can transform to accomplish various different tasks. For

example, the same code can simulate both scalar (classic one-ray-at-a-time) RGB transport

or differential spectral transport on the GPU. This all builds on

Dr.Jit, a specialized just-in-time(JIT) compiler developed specifically for this project.

Main Features

• Cross-platform: Mitsuba 3 has been tested on Linux (x86_64), macOS

  (aarch64, x8664), and Windows (x8664).

• High performance: The underlying Dr.Jit compiler fuses rendering code

  into kernels that achieve state-of-the-art performance using

  an LLVM backend targeting the CPU and a CUDA/OptiX backend

  targeting NVIDIA GPUs with ray tracing hardware acceleration.

• Python first: Mitsuba 3 is deeply integrated with Python. Materials,

  textures, and even full rendering algorithms can be developed in Python,

  which the system JIT-compiles (and optionally differentiates) on the fly.

  This enables the experimentation needed for research in computer graphics and

  other disciplines.

• Differentiation: Mitsuba 3 is a differentiable renderer, meaning that it

  can compute derivatives of the entire simulation with respect to input

  parameters such as camera pose, geometry, BSDFs, textures, and volumes. It

  implements recent differentiable rendering algorithms developed at EPFL.

• Spectral & Polarization: Mitsuba 3 can be used as a monochromatic

  renderer, RGB-based renderer, or spectral renderer. Each variant can

  optionally account for the effects of polarization if desired.

Tutorial videos, documentation

We've recorded several YouTube videos that provide a gentle introduction

Mitsuba 3 and Dr.Jit. Beyond this you can find complete Juypter notebooks

covering a variety of applications, how-to guides, and reference documentation

on readthedocs.

Installation

We provide pre-compiled binary wheels via PyPI. Installing Mitsuba this way is as simple as running

pip install mitsuba

on the command line. The Python package includes thirteen variants by default:

• scalar_rgb

• scalar_spectral

• scalarspectralpolarized

• llvmadrgb

• llvmadmono

• llvmadmono_polarized

• llvmadspectral

• llvmadspectral_polarized

• cudaadrgb

• cudaadmono

• cudaadmono_polarized

• cudaadspectral

• cudaadspectral_polarized

The first two perform classic one-ray-at-a-time simulation using either a RGB

or spectral color representation, while the latter two can be used for inverse

rendering on the CPU or GPU. To access additional variants, you will need to

compile a custom version of Dr.Jit using CMake. Please see the

documentation

for details on this.

Requirements

• Python >= 3.8

• (optional) For computation on the GPU: Nvidia driver >= 495.89

• (optional) For vectorized / parallel computation on the CPU: LLVM >= 11.1

Usage

Here is a simple "Hello World" example that shows how simple it is to render a

scene using Mitsuba 3 from Python:

# Import the library using the alias "mi"import mitsuba as mi# Set the variant of the renderermi.setvariant('scalarrgb')# Load a scenescene = mi.loaddict(mi.cornellbox())# Render the sceneimg = mi.render(scene)# Write the rendered image to an EXR filemi.Bitmap(img).write('cbox.exr')

Tutorials and example notebooks covering a variety of applications can be found

in the documentation.

About

This project was created by Wenzel Jakob.

Significant features and/or improvements to the code were contributed by

Sébastien Speierer,

Nicolas Roussel,

Merlin Nimier-David,

Delio Vicini,

Tizian Zeltner,

Baptiste Nicolet,

Miguel Crespo,

Vincent Leroy, and

Ziyi Zhang.

When using Mitsuba 3 in academic projects, please cite:

@software{Mitsuba3,title = {Mitsuba 3 renderer},author = {Wenzel Jakob and Sébastien Speierer and Nicolas Roussel and Merlin Nimier-David and Delio Vicini and Tizian Zeltner and Baptiste Nicolet and Miguel Crespo and Vincent Leroy and Ziyi Zhang},note = {https://mitsuba-renderer.org},version = {3.1.1},year = 2022}