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} }