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Datasets:
whyen-wang
/
mnist

Tasks:
Image Classification
Modalities:
Image
Formats:
parquet
Size:
10K - 100K
Libraries:
Datasets
pandas
Dataset card Viewer Files Community
2
mnist
File size: 4,376 Bytes 
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---
size_categories:
- n<1K
task_categories:
- image-classification
pretty_name: MNIST
dataset_info:
  features:
  - name: image
    dtype:
      image:
        mode: L
  - name: label
    dtype:
      class_label:
        names:
          '0': '0'
          '1': '1'
          '2': '2'
          '3': '3'
          '4': '4'
          '5': '5'
          '6': '6'
          '7': '7'
          '8': '8'
          '9': '9'
  splits:
  - name: train
    num_bytes: 17223300.0
    num_examples: 60000
  - name: test
    num_bytes: 2875182.0
    num_examples: 10000
  download_size: 18157556
  dataset_size: 20098482.0
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: test
    path: data/test-*
---

# Dataset Card for "MNIST"

## Quick Start
### Usage
```python
>>> from datasets.load import load_dataset

>>> dataset = load_dataset('whyen-wang/mnist')
>>> example = dataset['train'][0]
>>> print(example)
{'image': <PIL.PngImagePlugin.PngImageFile image mode=L size=28x28>,
 'label': 5}
```

### Visualization
```python
>>> import cv2
>>> import numpy as np
>>> from PIL import Image

>>> def visualize(example):
    image = np.array(example['image'])
    image = cv2.resize(image, (280, 280))
    cv2.putText(
        image, str(example['label']), (0, 50), cv2.FONT_HERSHEY_SIMPLEX,
        2, (255), 1, cv2.LINE_AA, False
    )
    return image

>>> Image.fromarray(example)
```


## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:** http://yann.lecun.com/exdb/mnist/
- **Repository:** None
- **Paper:** None
- **Leaderboard:** [Papers with Code](https://paperswithcode.com/dataset/imagenet)
- **Point of Contact:** None

### Dataset Summary

The MNIST database of handwritten digits, available from this page, has a training set of 60,000 examples, and a test set of 10,000 examples. It is a subset of a larger set available from NIST. The digits have been size-normalized and centered in a fixed-size image.

### Supported Tasks and Leaderboards

[Image Classification](https://huggingface.co/tasks/image-classification)

### Languages

None

## Dataset Structure

### Data Instances

An example looks as follows.

```
{
    "image": PIL.Image(mode="L"),
    "label": "0"
}
```

### Data Fields

[More Information Needed]

### Data Splits

| name  |  train |   test |
| ----- | -----: | -----: |
|default| 60,000 | 10,000 |

## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

[More Information Needed]

### Citation Information

[More Information Needed]

### Contributions

Thanks to [@github-whyen-wang](https://github.com/whyen-wang) for adding this dataset.