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-*
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:
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. No sign-up required.
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
