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metadata
dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype:
        class_label:
          names:
            '0': banded
            '1': blotchy
            '2': braided
            '3': bubbly
            '4': bumpy
            '5': chequered
            '6': cobwebbed
            '7': cracked
            '8': crosshatched
            '9': crystalline
            '10': dotted
            '11': fibrous
            '12': flecked
            '13': freckled
            '14': frilly
            '15': gauzy
            '16': grid
            '17': grooved
            '18': honeycombed
            '19': interlaced
            '20': knitted
            '21': lacelike
            '22': lined
            '23': marbled
            '24': matted
            '25': meshed
            '26': paisley
            '27': perforated
            '28': pitted
            '29': pleated
            '30': polka-dotted
            '31': porous
            '32': potholed
            '33': scaly
            '34': smeared
            '35': spiralled
            '36': sprinkled
            '37': stained
            '38': stratified
            '39': striped
            '40': studded
            '41': swirly
            '42': veined
            '43': waffled
            '44': woven
            '45': wrinkled
            '46': zigzagged
  splits:
    - name: train
      num_bytes: 463693721.28
      num_examples: 3760
    - name: test
      num_bytes: 171623828
      num_examples: 1880
  download_size: 629499529
  dataset_size: 635317549.28
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*

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.