size_categories:1K<n<10K format:parquet modality:image modality:text library:datasets library:pandas library:mlcroissant library:polars region:us
---
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
  - name: object_labels
    list:
    - name: label
      dtype: string
    - name: bbox
      sequence: float64
    - name: bbox_id
      dtype: string
  splits:
  - name: train
    num_bytes: 335477
    num_examples: 1295
  download_size: 146416
  dataset_size: 335477
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---
<div style="text-align: center;">
  <a href="https://app.visual-layer.com/dataset/bc41491e-78ae-11ef-ba4b-8a774758b536/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/ogZKM2KyTMsVdzxHdNuId.qt"></video>

# Beans-VL-Enriched

An enriched version of the Beans Dataset with image captions, bounding boxes, and label issues! With this additional information, the Beans 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 4 columns:

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

## Usage

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

```python
import datasets
ds = datasets.load_dataset("visual-layer/beans-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/ogZKM2KyTMsVdzxHdNuId.qt"></video>

<div style="text-align: center;">
  <a href="https://app.visual-layer.com/dataset/bc41491e-78ae-11ef-ba4b-8a774758b536/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 Beans dataset license.

## About Visual Layer

<div style="text-align: center; margin-top:50px;">
    <a href="https://visual-layer.com/" style="padding:10px; display: inline-block;">
                <img alt="site" src="https://vl-blog.s3.us-east-2.amazonaws.com/imgs/web.png" width="50"></a>
    <a href="https://medium.com/visual-layer" style="padding:10px; display: inline-block;">
                <img alt="blog" src="https://vl-blog.s3.us-east-2.amazonaws.com/imgs/forum.png" width="50"></a>
    <a href="https://github.com/visual-layer/fastdup" style="padding:10px; display: inline-block;">
                <img alt="github" src="https://vl-blog.s3.us-east-2.amazonaws.com/imgs/github.png" width="50"></a>
    <a href="https://discord.com/invite/Dqw458EG/" style="padding:10px; display: inline-block;">
                <img alt="slack" src="https://vl-blog.s3.us-east-2.amazonaws.com/imgs/discord.png" width="50"></a>
    <a href="https://www.linkedin.com/company/visual-layer/" style="padding:10px; display: inline-block;">
                <img alt="linkedin" src="https://vl-blog.s3.us-east-2.amazonaws.com/imgs/linkedin.png" width="50"></a>
    <a href="https://www.youtube.com/@visual-layer" style="padding:10px; display: inline-block;">
                <img alt="youtube" src="https://vl-blog.s3.us-east-2.amazonaws.com/imgs/youtube.png" width="50"></a>
    <a href="https://twitter.com/visual_layer" style="padding:10px; display: inline-block;">
                <img alt="twitter" src="https://vl-blog.s3.us-east-2.amazonaws.com/imgs/x.png" width="50"></a>
</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>
