README.md

metadata

annotations_creators:
  - expert-generated
language: []
language_creators: []
license:
  - cc-by-nc-4.0
multilinguality: []
pretty_name: 'TD01: Natural Ground Texture Photos'
size_categories:
  - n<1K
source_datasets:
  - original
tags:
  - texture-synthesis
  - photography
  - non-infringing
task_categories:
  - unconditional-image-generation
task_ids: []
viewer: false

The 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 — portrait or landscape
• Author: Alex J. Champandard
• Configurations: 4K, 2K (default), 1K

To load the medium- and high-resolution images of the dataset, you'll need to install jxlpy from PyPI with pip install jxlpy:

# Recommended use, JXL at high-quality.
from jxlpy import JXLImagePlugin
from datasets import load_dataset
d = load_dataset('texturedesign/td01_natural-ground-textures', 'JXL@4K')

print(len(d['train']), len(d['test']))

The lowest-resolution images are available as PNG with a regular installation of pillow:

# Alternative use, PNG at low-quality.
from datasets import load_dataset
d = load_dataset('texturedesign/td01_natural-ground-textures', 'PNG@1K')

# EXAMPLE: Discard all other sets except Set #1.
dataset = dataset.filter(lambda s: s['set'] == 1)
# EXAMPLE: Only keep images with index 0 and 2.
dataset = dataset.select([0, 2])

Use built-in dataset filter() and select() to narrow down the loaded dataset for training, or to ease with development.

Set #1: Rock and Gravel

• Description:
  • surface rocks with gravel and coarse sand
  • strong sunlight from the left, sharp shadows
• Number of Photos:
  • 7 train
  • 2 test
• Edits:
  • rotated photos to align sunlight
  • removed infrequent objects
• Size: 77.8 Mb

Set #2: Dry Grass with Pine Needles

• Description:
  • field of dry grass and pine needles
  • sunlight from the top right, some shadows
• Number of Photos:
  • 6 train
  • 1 test
• Edits:
  • removed dry leaves and large plants
  • removed sticks, rocks and sporadic daisies
• Size: 95.2 Mb

Set #3: Chipped Stones, Broken Leaves and Twiglets

• Description:
  • autumn path with chipped stones and dry broken leaves
  • diffuse light on a cloudy day, very soft shadows
• Number of Photos:
  • 9 train
  • 3 test
• Edits:
  • removed anything that looks green, fresh leaves
  • removed long sticks and large/odd stones
• Size: 126.9 Mb

Set #4: Grass Clumps and Cracked Dirt

• Description:
  • clumps of green grass, clover and patches of cracked dirt
  • diffuse light on cloudy day, shadows under large blades of grass
• Number of Photos:
  • 9 train
  • 2 test
• Edits:
  • removed dry leaves, sporadic dandelions, and large objects
  • histogram matching for two of the photos so the colors look similar
• Size: 126.8 Mb

Set #5: Dirt, Stones, Rock, Twigs...

• Description:
  • intricate micro-scene with grey dirt, surface rock, stones, twigs and organic debris
  • diffuse light on cloudy day, soft shadows around the larger objects
• Number of Photos:
  • 9 train
  • 3 test
• Edits:
  • removed odd objects that felt out-of-distribution
• Size: 102.1 Mb

Set #6: Plants with Flowers on Dry Leaves

• Description:
  • leafy plants with white flowers on a bed of dry brown leaves
  • soft diffuse light, shaded areas under the plants
• Number of Photos:
  • 9 train
  • 2 test
• Edits:
  • none yet, inpainting doesn't work well enough
  • would remove long sticks and pieces of wood
• Size: 105.1 Mb