Dataset Card for StanfordDogs

This is a FiftyOne dataset with 20580 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/StanfordDogs")

# Launch the App
session = fo.launch_app(dataset)

Dataset Details

Dataset Description

The Stanford Dogs dataset contains images of 120 breeds of dogs from around the world. This dataset has been built using images and annotation from ImageNet for the task of fine-grained image categorization. Contents of this dataset:

• Number of categories: 120
• Number of images: 20,580
• Annotations: Class labels, Bounding boxes

• Language(s) (NLP): en
• License: [More Information Needed]

Dataset Sources [optional]

• Paper: Novel dataset for Fine-Grained Image Categorization
• Homepage: http://vision.stanford.edu/aditya86/ImageNetDogs/

Uses

Fine-grained visual classification

Citation

BibTeX:

@inproceedings{KhoslaYaoJayadevaprakashFeiFei_FGVC2011,
  author = "Aditya Khosla and Nityananda Jayadevaprakash and Bangpeng Yao and Li Fei-Fei",
  title = "Novel Dataset for Fine-Grained Image Categorization",
  booktitle = "First Workshop on Fine-Grained Visual Categorization, IEEE Conference on Computer Vision and Pattern Recognition",
  2011,
  month = "June",
  address = "Colorado Springs, CO",
}

Dataset Card Authors

Jacob Marks

Dataset Contacts

aditya86@cs.stanford.edu and bangpeng@cs.stanford.edu