README.md

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# Dataset Card for Flowers102

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## Dataset Details

### Dataset Description

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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

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- **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

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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

<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->

**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}
}