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dream-textures/textures-color-normal-1k

textures-color-normal-1k Dataset Summary The textures-color-normal-1k dataset is an image dataset of 1000+ color and normal map textures in 512x512 resolution. The dataset was created for use in image to image tasks. It contains a combination of CC0 procedural and photoscanned PBR materials from ambientCG. Dataset Structure Data Instances Each data point contains a 512x512 color texture and the corresponding 512x512 normal map.… See the full description on the dataset page: https://huggingface.co/datasets/dream-textures/textures-color-normal-1k.

sourceHugging Facecc0-1.0updated 4y agoView on Hugging Face
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Dataset Card

textures-color-normal-1k

Table of Contents

Dataset Description

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Dataset Summary

The textures-color-normal-1k dataset is an image dataset of 1000+ color and normal map textures in 512x512 resolution. The dataset was created for use in image to image tasks. It contains a combination of CC0 procedural and photoscanned PBR materials from ambientCG.

Dataset Structure

Data Instances

Each data point contains a 512x512 color texture and the corresponding 512x512 normal map.

Data Fields

  • color: the color texture as a PIL image
  • normal: the normal map as a PIL image

Data Splits

train
ambientCG1426

Dataset Creation

Curation Rationale

textures-color-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 training models designed for image to image tasks, 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 color and normal maps were included in this dataset.

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.