dream-textures/textures-normal-1k

textures-normal-1k

Table of Contents

• —Table of Contents
• —Dataset Description
• —Dataset Summary
• —Languages
• —Dataset Structure
• —Data Instances
• —Data Fields
• —Data Splits
• —Dataset Creation
• —Curation Rationale
• —Source Data
• —Additional Information
• —Dataset Curators
• —Licensing Information
• —Citation Information
• —Contributions

Dataset Description

• —Homepage:
• —Repository:
• —Paper:
• —Leaderboard:
• —Point of Contact:

Dataset Summary

The textures-normal-1k dataset is an image dataset of 1000+ normal map textures in 512x512 resolution with associated text descriptions. The dataset was created for training/fine-tuning models for text to image tasks. It contains a combination of CC0 procedural and photoscanned PBR materials from ambientCG.

Languages

The text descriptions are in English, and created by joining the tags of each material with a space character.

Dataset Structure

Data Instances

Each data point contains a 512x512 image and and additional text feature containing the description of the texture.

Data Fields

• —image: the normal map as a PIL image
• —text: the associated text description created by merging the material's tags

Data Splits

Dataset Creation

Curation Rationale

textures-normal-1k was created to provide an accesible source of data for automating 3D-asset creation workflows. The Dream Textures add-on is one such tool providing AI automation in Blender. By fine-tuning models such as Stable Diffusion on textures, this particular use-case can be more accurately automated.

Source Data

Initial Data Collection and Normalization

The data was obtained from ambientCG's CC0 textures. Only the normal maps were included in this dataset.

Text descriptions were synthesized by joining the tags associated with each material with a space.

Additional Information

Dataset Curators

The dataset was created by Carson Katri, with the images being provided by ambientCG.

Licensing Information

All of the images used in this dataset are CC0.

Citation Information

[N/A]

Contributions

Thanks to @carson-katri for adding this dataset.