README.md

---
{}
---

# Dataset Card for Tiny ImageNet

<!-- Provide a quick summary of the dataset. -->

## Dataset Details

### Dataset Description

<!-- Provide a longer summary of what this dataset is. -->
In Tiny ImageNet, there are 100,000 images divided up into 200 classes. 

- **License:** MIT License

### Dataset Sources

<!-- Provide the basic links for the dataset. -->

- **Homepage:** https://www.kaggle.com/c/tiny-imagenet
- **Paper:** Le, Y., & Yang, X. (2015). Tiny imagenet visual recognition challenge. CS 231N, 7(7), 3.

## Dataset Structure

<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->

Total images: 110,000

Classes: 200 categories

Splits:

- **Train:** 100,000 images

- **Validation:** 10,000 images

Image specs: JPEG format, 64×64 pixels, 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/tiny-imagenet", split="train", trust_remote_code=True)
# dataset = load_dataset("randall-lab/tiny-imagenet", split="validation", 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:**

@article{le2015tiny,
  title={Tiny imagenet visual recognition challenge},
  author={Le, Yann and Yang, Xuan},
  journal={CS 231N},
  volume={7},
  number={7},
  pages={3},
  year={2015}
}