datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
td02_urban-surface-texturesThe Dataset Teaser is now enabled instead! Isn't this better?
TD 02: Urban Surface Textures
This dataset contains multi-photo texture captures in outdoor urban scenes — many focusing on the ground and the others are walls. Each set has different photos that showcase texture variety, making them ideal for training a domain-specific image generator!
Overall information about this dataset:
Format — JPEG-XL, lossless RGB
Resolution — 4032 × 2268
Device — mobile camera
Technique —… See the full description on the dataset page: https://huggingface.co/datasets/texturedesign/td02_urban-surface-textures.Describable-Textures-Dataset
Dataset Card for Describable Textures Dataset
This is a FiftyOne dataset with 5640 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
import fiftyone.utils.huggingface as fouh
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = fouh.load_from_hub("Voxel51/Describable-Textures-Dataset")
# Launch the App
session = fo.launch_app(dataset)… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/Describable-Textures-Dataset.td01_natural-ground-texturesThe Dataset Teaser is now enabled instead! Isn't this better?
TD 01: Natural Ground Textures
This dataset contains multi-photo texture captures in outdoor nature scenes — all focusing on the ground. Each set has different photos that showcase texture variety, making them ideal for training a domain-specific image generator!
Overall information about this dataset:
Format — JPEG-XL, lossless RGB
Resolution — 4032 × 2268
Device — mobile camera
Technique — hand-held
Orientation —… See the full description on the dataset page: https://huggingface.co/datasets/texturedesign/td01_natural-ground-textures.Describable-Textures-Dataset-DTD
Not sure about the license.
Source: https://www.robots.ox.ac.uk/~vgg/data/dtd/
Describable Textures Dataset (DTD)
The Describable Textures Dataset (DTD) is an evolving collection of textural images in the wild, annotated with a series of human-centric attributes, inspired by the perceptual properties of textures. This data is made available to the computer vision community for research purposes.
Download… See the full description on the dataset page: https://huggingface.co/datasets/cansa/Describable-Textures-Dataset-DTD.Franka_GraspNet_Test_texturetextures-for-blendertextures-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.
Data Fields… See the full description on the dataset page: https://huggingface.co/datasets/dream-textures/textures-color-normal-1k.LAST_Large_Shapes_And_Textures_Dataset
LAS&T Large Shapes And Textures Dataset
LAS&T is a large scale highly diverse dataset for shape, texture and material recognition and retrieval in 2D and 3D with 650,000 images, based over on 300,000 different real world shapes, materials and textures.
Overview
The LAS&T Dataset aims to test/train models on identifying/retrieval of any shape, texture, and material in any setting and environment, without being limited to specific types or classes of… See the full description on the dataset page: https://huggingface.co/datasets/FlyingFrog/LAST_Large_Shapes_And_Textures_Dataset.Texture-AD-Benchmarkdataset_sugar_1709_texture-rawmetaworld_mt10_roboe_textureThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": null,
"total_episodes": 500,
"total_frames": 46327,
"total_tasks": 10,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 80,
"splits": {
"train": "0:500"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/Beegbrain/metaworld_mt10_roboe_texture.cc0-textures
Dataset Card for CC0 Textures
Dataset Summary
This dataset contains 18,785 texture images from cc0-textures.com. It includes textures of wood, metal, concrete, fabric, stone, ceramic, and other materials. The original archives were downloaded, unpacked, and images were compressed using PNG optimization and JPEG quality compression (90%) to reduce file size while keeping good quality.
Languages
The dataset is monolingual:
English (en): Texture titles and tags… See the full description on the dataset page: https://huggingface.co/datasets/nyuuzyou/cc0-textures.TextureADE
TextureADE
Real scenes carrying several appearance transitions each, mined from the ADE20K validation split.
One of the four evaluation routes in the ICLR 2027 submission on sub-semantic
image segmentation: partitioning an image into regions that are coherent in
appearance and describable in language, but that need not correspond to any
object, part or material class.
Images: 212
Code: github.com/aviadcohz/Qwen2SAM_Detecture_Benchmark
Weights: aviadcohz/Detecture-ICLR-2027
All… See the full description on the dataset page: https://huggingface.co/datasets/aviadcohz/TextureADE.DTD_Describable-Textures-DatasetDTD is a texture database, consisting of 5640 images, organized according to a list of 47 terms (categories) inspired from human perception. There are 120 images for each category. Image sizes range between 300x300 and 640x640, and the images contain at least 90% of the surface representing the category attribute. The images were collected from Google and Flickr by entering our proposed attributes and related terms as search queries. The images were annotated using Amazon Mechanical Turk in several iterations. For each image we provide key attribute (main category) and a list of joint attributes.planet-texturesSource: https://planet-texture-maps.fandom.com/wiki/Planet_Texture_Maps_Wiki
GitHub: https://github.com/sshh12/planet-diffusion
textures-color-1k
textures-color-1k
Dataset Summary
The textures-color-1k dataset is an image dataset of 1000+ color image textures in 512x512 resolution with associated text descriptions.
The dataset was created for training/fine-tuning diffusion models on texture generation 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… See the full description on the dataset page: https://huggingface.co/datasets/dream-textures/textures-color-1k.grabette-tactile-textureThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"robot_type": "grabette",
"total_episodes": 16,
"total_frames": 6834,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 200,
"fps": 50,
"splits": {
"train": "0:16"
},
"data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
"video_path":… See the full description on the dataset page: https://huggingface.co/datasets/CarolinePascal/grabette-tactile-texture.Kather-texture-2016
Collection of textures in colorectal cancer histology
Description
This data set represents a collection of textures in histological images of human colorectal cancer.
It contains 5000 histological images of 150 * 150 px each (74 * 74 µm). Each image belongs to exactly one of eight tissue categories.
Image format
All images are RGB, 0.495 µm per pixel, digitized with an Aperio ScanScope (Aperio/Leica biosystems), magnification 20x.
Histological samples are… See the full description on the dataset page: https://huggingface.co/datasets/1aurent/Kather-texture-2016.libero_plus_object_texture_all_ur5e_failuresThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 20,
"features": {
"observation.state": {
"dtype": "float32",
"shape": [
8
],
"names": {
"motors": [
"x",
"y",
"z",
"axis_angle1",
"axis_angle2"… See the full description on the dataset page: https://huggingface.co/datasets/LSY-lab/libero_plus_object_texture_all_ur5e_failures.libero_plus_spatial_texture_all_ur5e_failuresThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 20,
"features": {
"observation.state": {
"dtype": "float32",
"shape": [
8
],
"names": {
"motors": [
"x",
"y",
"z",
"axis_angle1",
"axis_angle2"… See the full description on the dataset page: https://huggingface.co/datasets/LSY-lab/libero_plus_spatial_texture_all_ur5e_failures.Texture
Dataset Description
The Describable Textures Dataset (DTD) includes 5,640 images of textures annotated with human-centric attributes. This split is derived from the OpenOOD benchmark OOD evaluation splits.
Homepage: https://www.robots.ox.ac.uk/~vgg/data/dtd/
OpenOOD Benchmark: https://github.com/Jingkang50/OpenOOD/
Citation
@inproceedings{cimpoi2014describing,
title={Describing textures in the wild},
author={Cimpoi, Mircea and others},
booktitle={CVPR}… See the full description on the dataset page: https://huggingface.co/datasets/torch-uncertainty/Texture.libero_plus_10_texture_all_ur5e_failuresThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 20,
"features": {
"observation.state": {
"dtype": "float32",
"shape": [
8
],
"names": {
"motors": [
"x",
"y",
"z",
"axis_angle1",
"axis_angle2"… See the full description on the dataset page: https://huggingface.co/datasets/LSY-lab/libero_plus_10_texture_all_ur5e_failures.lora-garment-textures
LoRA Garment Texture Training Dataset
📋 Dataset Description
This dataset contains high-quality garment texture images organized by categories for training LoRA (Low-Rank Adaptation) models. These images are specifically curated for fine-tuning diffusion models to generate virtual try-on results with specific fabric textures and patterns.
Key Features
🎨 Multiple texture categories for diverse garment styles
📸 High-resolution images suitable… See the full description on the dataset page: https://huggingface.co/datasets/zyuzuguldu/lora-garment-textures.describable_textures
Dataset Card for "describable_textures"
More Information needed
owm-earth-textures
OWM Earth Textures
Full-globe equirectangular Earth imagery for the renderer in
sisl/outofthisworldmodel-envs.
maps/ -- the finished maps the renderer reads. earth_color_full.jpg and
earth_clouds_full.jpg are 16384x8192 (~2.4 km/texel at the equator);
earth_bump_full.png is 8192x4096 and stays PNG because the normal map is
computed from height gradients, which JPEG block artifacts corrupt.
sources/ -- the high-resolution imagery the maps are downsampled from.
The renderer… See the full description on the dataset page: https://huggingface.co/datasets/sislaboratory/owm-earth-textures.asphalt-3d-laser-texture
Asphalt pavement 3D laser surface height maps with pendulum skid resistance (PTV)
Derivative of the Zenodo record 20606458, "Raw 3D laser scan point clouds and pendulum test value (PTV) and Traction
Watcher One (TWO) friction measurements from 45 asphalt pavement test sections" by Matus Kovac, Matej Brna and Peter Pisca
(University of Zilina, Faculty of Civil Engineering), https://doi.org/10.5281/zenodo.20606458, licensed CC-BY-4.0. This
derivative is redistributed under the… See the full description on the dataset page: https://huggingface.co/datasets/RaymondAllen/asphalt-3d-laser-texture.dagm_defect_detection_textured_surfaceslibero_plus_10_texture_allThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 20,
"features": {
"observation.state": {
"dtype": "float32",
"shape": [
8
],
"names": {
"motors": [
"x",
"y",
"z",
"axis_angle1",
"axis_angle2"… See the full description on the dataset page: https://huggingface.co/datasets/max-chr/libero_plus_10_texture_all.Texture_images
Textuer images
This is a dataset to train text-to-image or other models without any copyright issue.
All materials used in this dataset are CC0 (Public domain /P.D.).
Dataset Summary
This dataset card aims to be a base template for new datasets. It has been generated using this raw template.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
[More Information Needed]
Dataset Structure
Data Instances
[More… See the full description on the dataset page: https://huggingface.co/datasets/JapanDegitalMaterial/Texture_images.libero_plus_10_texture_all_failuresThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 20,
"features": {
"observation.state": {
"dtype": "float32",
"shape": [
8
],
"names": {
"motors": [
"x",
"y",
"z",
"axis_angle1",
"axis_angle2"… See the full description on the dataset page: https://huggingface.co/datasets/LSY-lab/libero_plus_10_texture_all_failures.