Datasets:
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 59834059.794
num_examples: 1447
download_size: 52173880
dataset_size: 59834059.794
license: cc0-1.0
task_categories:
- text-to-image
language:
- en
size_categories:
- 1K<n<10K
textures-normal-1k
Table of Contents
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 imagetext
: the associated text description created by merging the material's tags
Data Splits
train | |
---|---|
ambientCG | 1447 |
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.