Dataset Card for usps

This is a FiftyOne dataset with 9298 samples.

Installation

If you haven't already, install FiftyOne:

pip install -U fiftyone

Usage

import fiftyone as fo
import fiftyone.utils.huggingface as fouh

# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = fouh.load_from_hub("Voxel51/USPS")

# Launch the App
session = fo.launch_app(dataset)

Dataset Details

Dataset Description

• Curated by: Introduced by Jonathan J. Hull in A Database for Handwritten Text Recognition Research and available at https://paperswithcode.com/dataset/usps.
• Language(s) (NLP): en
• License: unknown

Dataset Sources [optional]

• Repository: https://paperswithcode.com/dataset/usps
• Paper: A Database for Handwritten Text Recognition Research

Dataset Structure

Name:        usps
Media type:  image
Num samples: 9298
Persistent:  False
Tags:        []
Sample fields:
    id:           fiftyone.core.fields.ObjectIdField
    filepath:     fiftyone.core.fields.StringField
    tags:         fiftyone.core.fields.ListField(fiftyone.core.fields.StringField)
    metadata:     fiftyone.core.fields.EmbeddedDocumentField(fiftyone.core.metadata.ImageMetadata)
    ground_truth: fiftyone.core.fields.EmbeddedDocumentField(fiftyone.core.labels.Classification)

The dataset has 2 splits: "train" and "test". Samples are tagged with their split.

Dataset Creation

Introduced by Jonathan J. Hull in A Database for Handwritten Text Recognition Research

Citation

BibTeX:

@ARTICLE{291440,
  author={Hull, J.J.},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, 
  title={A database for handwritten text recognition research}, 
  year={1994},
  volume={16},
  number={5},
  pages={550-554},
  keywords={Text recognition;Image databases;Testing;Cities and towns;Handwriting recognition;Gray-scale;Performance analysis;Writing;Digital images;Postal services},
  doi={10.1109/34.291440}}

More Information

Dataset conversion and data card contributed by Rohith Raj Srinivasan.

Dataset Card Authors

Rohith Raj Srinivasan