---
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
- name: object_issues
list:
- name: confidence
dtype: float64
- name: description
dtype: string
- name: duplicate_group_id
dtype: string
- name: issue_type
dtype: string
- name: bbox_id
dtype: string
splits:
- name: train
num_bytes: 10789219
num_examples: 70000
download_size: 3661592
dataset_size: 10789219
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
[](https://app.visual-layer.com/dataset/7e9674b6-648d-11ef-bb7d-4282573bcafb/data?p=1&page=1&utm_source=hugging_face )
# Fashion-Mnist-VL-Enriched
An enriched version of the Fashion-Mnist Dataset with image captions, bounding boxes, and label issues! With this additional information, the Fashion-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 5 columns:
- **image_uri**: The uri of original of the image from the Fashion-Mnist dataset.
- **label**: Label for the image, provided by the authors of the Fashion-Mnist dataset.
- **image_issues**: Quality issues found, such as duplicate, mislabeled, dark, blurry, bright, and outlier images.
- **object_labels**: Objects labels and bbox found in the image.
- **object_issues**: Image Objects quality issues found, such as duplicate, dark, blurry, bright, and outlier objects.
## Usage
This dataset can be used with the Hugging Face Datasets library:
```python
import datasets
ds = datasets.load_dataset("visual-layer/fashion-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.
[](https://app.visual-layer.com/dataset/7e9674b6-648d-11ef-bb7d-4282573bcafb/data?p=1&page=1&utm_source=hugging_face )
## 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 Fashion-Mnist dataset license.
## About Visual Layer