Datasets:
Tasks:
Image Classification
Modalities:
Image
Formats:
imagefolder
Languages:
English
Size:
100K - 1M
Tags:
OCR
Handwriting
Character Recognition
Grayscale Images
ASCII Labels
Optical Character Recognition
License:
license: mit | |
# AlphaNum Dataset | |
## Table of Contents | |
- [Dataset Summary](#dataset-summary) | |
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) | |
- [Languages](#languages) | |
- [Dataset Structure](#dataset-structure) | |
- [Data Instances](#data-instances) | |
- [Data Fields](#data-fields) | |
- [Data Splits](#data-splits) | |
- [Dataset Creation](#dataset-creation) | |
- [Curation Rationale](#curation-rationale) | |
- [Source Data](#source-data) | |
- [Dataset Use](#dataset-use) | |
- [Use Cases](#use-cases) | |
- [Usage Caveats](#usage-caveats) | |
- [Getting Started](#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. | |