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Dataset Card for Flowers102
Dataset Details
Dataset Description
This is a 102 category dataset, consisting of 102 flower categories. The flowers chosen to be flower commonly occuring in the United Kingdom. Each class consists of between 40 and 258 images.
Dataset Sources
- Homepage: https://www.robots.ox.ac.uk/~vgg/data/flowers/102/
- Paper: Nilsback, M. E., & Zisserman, A. (2008, December). Automated flower classification over a large number of classes. In 2008 Sixth Indian conference on computer vision, graphics & image processing (pp. 722-729). IEEE.
Dataset Structure
Total images: 8,189
Classes: 102
Splits:
Train: 1,020 images
Validation: 1,020 images
Test: 6,149 images
Image specs: JPG format, 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/flowers102", split="train", trust_remote_code=True)
# dataset = load_dataset("randall-lab/flowers102", split="validation", trust_remote_code=True)
# dataset = load_dataset("randall-lab/flowers102", 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{nilsback2008automated, title={Automated flower classification over a large number of classes}, author={Nilsback, Maria-Elena and Zisserman, Andrew}, booktitle={2008 Sixth Indian conference on computer vision, graphics & image processing}, pages={722--729}, year={2008}, organization={IEEE} }