--- annotations_creators: [] language: en size_categories: - 10K ![image/png](dataset_preview.jpg) This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 20580 samples. ## Installation If you haven't already, install FiftyOne: ```bash pip install -U fiftyone ``` ## Usage ```python 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](http://people.csail.mit.edu/khosla/papers/fgvc2011.pdf) - **Homepage:** http://vision.stanford.edu/aditya86/ImageNetDogs/ ## Uses Fine-grained visual classification ## Citation **BibTeX:** ```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](https://huggingface.co/jamarks) ## Dataset Contacts aditya86@cs.stanford.edu and bangpeng@cs.stanford.edu