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# 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}
}
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