hasy-v2 / README.md
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# Dataset Card for HASYv2
<!-- Provide a quick summary of the dataset. -->
## Dataset Details
### Dataset Description
<!-- Provide a longer summary of what this dataset is. -->
This is a dataset of handwritten symbols similar to MNIST. It contains 168233 instances of 369 classes.
### Dataset Sources
<!-- Provide the basic links for the dataset. -->
- **Homepage:** https://github.com/MartinThoma/HASY?tab=readme-ov-file
- **Paper:** Thoma, M. (2017). The hasyv2 dataset. arXiv preprint arXiv:1701.08380.
## 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: 168,233
Classes: 369 categories
Splits:
- **Train:** 151,241 images
- **Test:** 16,992 images
Image specs: PNG format, 32×32 pixels, Grayscale
## 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/hasy-v2", split="train", trust_remote_code=True)
# dataset = load_dataset("randall-lab/hasy-v2", 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:**
@article{thoma2017hasyv2,
title={The hasyv2 dataset},
author={Thoma, Martin},
journal={arXiv preprint arXiv:1701.08380},
year={2017}
}