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draco3d

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Version 1.1.0 release

The latest version of Draco brings a number of new compression enhancements for even smaller models:

  • Improved compression
    • Up to 40% better compression of normals
    • Up to 5% better compression for models with multiple attributes
  • Faster decode speeds
    • 30% faster decoding for models with multiple attributes for lower compression levels 4 and below
      • Note: Decreases compression by 10%.
  • Encoding of metadata to .obj (e.g. Draco can preserve material or sub-object names)
  • Security fixes

Description

Draco is a library for compressing and decompressing 3D geometric meshes and point clouds. It is intended to improve the storage and transmission of 3D graphics.

Draco was designed and built for compression efficiency and speed. The code supports compressing points, connectivity information, texture coordinates, color information, normals, and any other generic attributes associated with geometry. With Draco, applications using 3D graphics can be significantly smaller without compromising visual fidelity. For users, this means apps can now be downloaded faster, 3D graphics in the browser can load quicker, and VR and AR scenes can now be transmitted with a fraction of the bandwidth and rendered quickly.

Draco is released as C++/Javascript source code that can be used to compress 3D graphics as well as decoders for the encoded data.

NPM Package

The code shows a simple example of using Draco encoder and decoder with Node.js. draco_encoder_node.js and draco_decoder_node.js are modified Javascript encoding/decoding files that are compatible with Node.js. draco_nodejs_example.js has the example code for usage.

How to run the code:

(1) Install draco3d package :

$ npm install draco3d

(2) Run example code to test:

$ cp node_modules/draco3d/draco_nodejs_example.js .
$ cp node_modules/draco3d/bunny.drc .
$ node draco_nodejs_example.js

The code loads the Bunny model, it will first decode to a mesh and then encode it with different settings.

References

Bunny model from Stanford's graphic department https://graphics.stanford.edu/data/3Dscanrep/