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---
dataset_info:
  features:
  - name: image_uri
    dtype: string
  - name: image_label
    dtype: string
  - name: image_issues
    list:
    - name: confidence
      dtype: float64
    - name: description
      dtype: string
    - name: duplicate_group_id
      dtype: string
    - name: issue_type
      dtype: string
  splits:
  - name: train
    num_bytes: 9787660
    num_examples: 70000
  download_size: 3571333
  dataset_size: 9787660
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---
<div style="text-align: center;">
  <a href="https://app.visual-layer.com/dataset/efbbf2ae-6507-11ef-a4e6-aa6d4667de12/data?p=1&page=1&utm_source=hugging_face" style="display: inline-block; padding: 10px 20px; background-color: rgba(128, 0, 128, 0.5); color: white; text-decoration: none; border-radius: 5px; font-family: Arial, sans-serif; font-size: 16px;">
    Visualize on Visual Layer
  </a>
</div>

<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/66c73598ac384b32b9c7725a/OZzZ2QpJe1ZM6srWnB1Yj.qt"></video>


# Mnist-VL-Enriched

An enriched version of the Mnist Dataset with image captions, bounding boxes, and label issues! With this additional information, the Mnist dataset can be extended to various tasks such as image retrieval or visual question answering.

The label issues help curate a cleaner and leaner dataset.

## Description

The dataset consists of 3 columns:

- `image_uri`: The uri of original of the image from the Mnist dataset.
- `label`: Label for the image, provided by the authors of the Mnist dataset.
- `image_issues`: Quality issues found using Visual Layer enrichment process, such as duplicate, mislabeled, dark, blurry, bright, and outlier images.

## Usage

This dataset can be used with the Hugging Face Datasets library:

```python
import datasets
ds = datasets.load_dataset("visual-layer/mnist-vl-enriched")
```

## Interactive Visualization

Visual Layer provides a platform to interactively visualize a dataset and highlight quality issues such as duplicates, mislabels, outliers, etc. Check it out [here](https://app.visual-layer.com/dataset/3972b3fc-1809-11ef-bb76-064432e0d220/data?p=1&page=1&utm_source=hugging_face). No sign-up required.

<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/66c73598ac384b32b9c7725a/OZzZ2QpJe1ZM6srWnB1Yj.qt"></video>

<div style="text-align: center;">
  <a href="https://app.visual-layer.com/dataset/efbbf2ae-6507-11ef-a4e6-aa6d4667de12/data?p=1&page=1&utm_source=hugging_face" style="display: inline-block; padding: 10px 20px; background-color: rgba(128, 0, 128, 0.5); color: white; text-decoration: none; border-radius: 5px; font-family: Arial, sans-serif; font-size: 16px;">
    Visualize on Visual Layer
  </a>
</div>


## License & Disclaimer

We provide no warranty on the dataset, and the user takes full responsibility for the usage of the dataset. By using the dataset, you agree to the terms of the Mnist dataset license.


## About Visual Layer

<div style="text-align: center; margin-top:50px;">
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</div>
<div style="text-align: center;">
    <img style="width:200px; display: block; margin: 0 auto;" alt="logo" src="https://d2iycffepdu1yp.cloudfront.net/design-assets/VL_horizontal_logo.png">
    <div style="margin-top:20px;">Copyright © 2024 Visual Layer. All rights reserved.</div>
</div>