---
license: cc0-1.0
task_categories:
- image-segmentation
- zero-shot-classification
tags:
- textures
- PBR materials
size_categories:
- 100M<n<1B
---
# General
VasTexture is a large-scale dataset of textures and PBR materials extracted from real-world images. 
The repository contains 500,000 highly diverse texture images and PBR materials. All assets are free to download and use for any purpose (CC0 license).
The dataset is divided into textures images, and PBR materials. Where texture image are simply crop of regions in images with uniform textures.


The PBR materials and textures were extracted from natural images using an unsupervised statistical approach (no human intervention).
As a result, the textures and PBR materials are significantly more diverse but less refined compared to assets made using manual and AI approaches. This dataset is more suitable for tasks needing a large number of highly diverse assets like building datasets or large scale procedural generation.

[##Project Website](https://sites.google.com/view/infinitexture/home)



## File Structure
The dataset is composed into two assets types textures images and PBR materials. 


Texture image files contain the world **Texture** in the file. 
PBR materiasl files contain the world **PBR** in the file. 
If the PBR are seamless/tilable, the world **seamless** will appear in the file name (note that for textures images this mean some modification was done on texture edges). 

If the PBR is   512x512 or larger, the world **large** will appear in the file name.
Most files will have texture size in their name.

Each file contain between 1,000 to 40,000 assets.
Files with the the word **sample** contain few dozens to few hundered samples.

## Data generation code:

The Python scripts used to extract these assets are supplied at: 

Texture_And_Material_ExtractionCode_And_Documentation.zip

The code could be run in any folder of random images extract regions with uniform textures and turn these into PBR materials. 

Code for transforming data to seamless available at [https://github.com/sagieppel/convert-image-into-seamless-tileable-texture](https://github.com/sagieppel/convert-image-into-seamless-tileable-texture)
 

# GITHUB and Alternative download sources:
GitHub: [Texture/PBR extraction](https://github.com/sagieppel/Unsupervised-extraction-of-textures-and-PBR-materials-from-images), [Texture To Seamless](https://github.com/sagieppel/convert-image-into-seamless-tileable-texture)

https://sites.google.com/view/infinitexture/home

https://zenodo.org/records/12629301 

## Papers
Main paper:
[Infusing Synthetic Data with Real-World Patterns for
Zero-Shot Material State Segmentation](https://proceedings.neurips.cc/paper_files/paper/2024/file/6ef4a4b387a5a547ea699f3df7fc1248-Paper-Datasets_and_Benchmarks_Track.pdf)

More detailed:
[Vastextures: Vast repository of textures and PBR materials
extracted from real-world images using unsupervised methods](https://arxiv.org/pdf/2406.17146)