DTD: Describable Textures Dataset

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

Usage

from datasets import load_dataset

dataset = load_dataset('tanganke/dtd')

• Features:

  • Image: The primary data type, which is a digital image used for classification. The format and dimensions of the images are not specified in this snippet but should be included if available.
  • Label: A categorical feature representing the texture or pattern class of each image. The dataset includes 46 classes with descriptive names ranging from 'banded' to 'zigzagged'.
    • Class Labels:
      • '0': banded
      • '1': blotchy
      • '2': braided
      • ...
      • '45': wrinkled
      • '46': zigzagged

• Splits: The dataset is divided into training and test subsets for model evaluation.

  • Training: containing 3760 examples with a total size of 448,550 bytes.
  • Test: containing 1880 examples with a total size of 220,515 bytes.