The dataset viewer is not available for this dataset.
Error code: ConfigNamesError
Exception: RuntimeError
Message: Dataset scripts are no longer supported, but found dtd.py
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
config_names = get_dataset_config_names(
^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
dataset_module = dataset_module_factory(
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1207, in dataset_module_factory
raise e1 from None
File "/usr/local/lib/python3.12/site-packages/datasets/load.py", line 1167, in dataset_module_factory
raise RuntimeError(f"Dataset scripts are no longer supported, but found {filename}")
RuntimeError: Dataset scripts are no longer supported, but found dtd.pyNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
Dataset Card for Describable Textures Dataset (DTD)
Dataset Details
Dataset Description
The Describable Textures Dataset (DTD) is a texture classification dataset consisting of 5,640 images categorized into 47 texture classes based on human perception. Each image is labeled with a primary texture category (key attribute) and may have additional joint attributes representing secondary textures. The dataset is divided into three equal splits (train, validation, test) with 40 images per class per split.
Dataset Sources
- Homepage: https://www.robots.ox.ac.uk/~vgg/data/dtd/
- Paper: Cimpoi, M., Maji, S., Kokkinos, I., Mohamed, S., & Vedaldi, A. (2014). Describing textures in the wild. In Proceedings of the IEEE conference on computer vision and pattern recognition (pp. 3606-3613).
Dataset Structure
Each sample in the dataset contains:
image: A variable-sized RGB image
label: A categorical label representing the texture class
Total images: 5,640
Classes: 47 (e.g., banded, blotchy, chequered, cracked, dotted, grid, lined, marbled, porous, striped, etc.)
Splits:
Train: 1,880 images (40 per class)
Validation: 1,880 images (40 per class)
Test: 1,880 images (40 per class)
Image specs: Variable sizes (300×300 to 640×640 pixels), RGB
Example Usage
Below is a quick example of how to load this dataset via the Hugging Face Datasets library.
from datasets import load_dataset
# Load the dataset
dataset = load_dataset("randall-lab/dtd", split="train", trust_remote_code=True)
# dataset = load_dataset("randall-lab/dtd", split="validation", trust_remote_code=True)
# dataset = load_dataset("randall-lab/dtd", split="test", trust_remote_code=True)
# Access a sample from the dataset
example = dataset[0]
image = example["image"]
label = example["label"]
image.show() # Display the image
print(f"Label: {label}")
Citation
BibTeX:
@inproceedings{cimpoi2014describing, title={Describing textures in the wild}, author={Cimpoi, Mircea and Maji, Subhransu and Kokkinos, Iasonas and Mohamed, Sammy and Vedaldi, Andrea}, booktitle={Proceedings of the IEEE conference on computer vision and pattern recognition}, pages={3606--3613}, year={2014} }
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