Datasets:
Tasks:
Image Classification
Modalities:
Image
Languages:
English
Size:
10K<n<100K
ArXiv:
Libraries:
FiftyOne
metadata
annotations_creators: []
language: en
size_categories:
- 10K<n<100K
task_categories:
- image-classification
task_ids: []
pretty_name: EMNIST-Letters-10k
tags:
- fiftyone
- image
- image-classification
dataset_summary: >
![image/png](dataset_preview.png)
This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 10000
samples.
## Installation
If you haven't already, install FiftyOne:
```bash
pip install -U fiftyone
```
## Usage
```python
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("Voxel51/emnist-letters-tiny")
# Launch the App
session = fo.launch_app(dataset)
```
Dataset Card for EMNIST-Letters-10k
A random subset of the train and test splits from the letters portion of EMNIST
This is a FiftyOne dataset with 10000 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("Voxel51/emnist-letters-tiny")
# Launch the App
session = fo.launch_app(dataset)
Dataset Details
Dataset Description
- Curated by: [More Information Needed]
- Funded by [optional]: [More Information Needed]
- Shared by [optional]: [More Information Needed]
- Language(s) (NLP): en
- License: [More Information Needed]
Dataset Sources
- Homepage: https://www.nist.gov/itl/products-and-services/emnist-dataset
- Paper : https://arxiv.org/abs/1702.05373v1
Citation
BibTeX:
@misc{cohen2017emnistextensionmnisthandwritten,
title={EMNIST: an extension of MNIST to handwritten letters},
author={Gregory Cohen and Saeed Afshar and Jonathan Tapson and André van Schaik},
year={2017},
eprint={1702.05373},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/1702.05373},
}