README.md

metadata

license: mit

AlphaNum Dataset

Table of Contents

• Dataset Summary
• Supported Tasks and Leaderboards
• Languages
• Dataset Structure
  • Data Instances
  • Data Fields
  • Data Splits
• Dataset Creation
  • Curation Rationale
  • Source Data
• Dataset Use
  • Use Cases
  • Usage Caveats
  • Getting Started

Dataset Summary

The AlphaNum dataset, created by Louis Rädisch, is a comprehensive handwritten dataset specifically designed for the development and improvement of OCR (Optical Character Recognition) models. The dataset comprises handwritten characters A-Z and numbers 0-9, providing a realistic challenge for OCR models.

Supported Tasks and Leaderboards

This dataset supports a range of tasks including text recognition, document processing, and machine learning. It can contribute to improving the performance of OCR models by providing a diverse set of writing styles and formats.

Languages

The dataset is primarily in English.

Dataset Structure

Data Instances

A data instance in this dataset represents an image of a handwritten character and the associated labels.

Data Fields

The fields are:

1. 'image': The image of the handwritten character.
2. 'label': The label for the character in the image.

Data Splits

The dataset is split into training, validation, and test sets.

Dataset Creation

Curation Rationale

The dataset was created to provide a rich and diverse source of data for the development and improvement of OCR models.

Source Data

The source data comes from handwritten characters created by various individuals.

Dataset Use

Use Cases

The dataset can be used for tasks related to text recognition, document processing, and machine learning.

Usage Caveats

There are no specific restrictions on the use of this dataset.

Getting Started

The dataset can be utilized for the development and improvement of OCR models.