ZenonZhou/IAM-line

---
license: mit
language:
- en
task_categories:
- image-to-text
pretty_name: IAM-line

dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_examples: 6482
- name: validation
num_examples: 976
- name: test
num_examples: 2915
dataset_size: 10373
tags:
- atr
- htr
- ocr
- modern
- handwritten
---

# IAM - line level

## Table of Contents
- [IAM - line level](#iam-line-level)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)

## Dataset Description

- **Homepage:** [IAM Handwriting Database](https://fki.tic.heia-fr.ch/databases/iam-handwriting-database)
- **Paper:** [The IAM-database: an English sentence database for offline handwriting recognition](https://doi.org/10.1007/s100320200071)
- **Point of Contact:** [TEKLIA](https://teklia.com)

## Dataset Summary

The IAM Handwriting Database contains forms of handwritten English text which can be used to train and test handwritten text recognizers and to perform writer identification and verification experiments.

Note that all images are resized to a fixed height of 128 pixels.

### Languages

All the documents in the dataset are written in English.

## Dataset Structure

### Data Instances

```
{
'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=2467x128 at 0x1A800E8E190,
'text': 'put down a resolution on the subject'
}
```

### Data Fields

- `image`: a PIL.Image.Image object containing the image. Note that when accessing the image column (using dataset[0]["image"]), the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the "image" column, i.e. dataset[0]["image"] should always be preferred over dataset["image"][0].
- `text`: the label transcription of the image.

---
许可证: MIT协议
语言:
- 英语
任务类别:
- 图像到文本
展示名称: IAM-line

数据集信息:
特征:
- 名称: image
数据类型: 图像
- 名称: text
数据类型: 字符串
数据集划分:
- 名称: 训练集
样本数量: 6482
- 名称: 验证集
样本数量: 976
- 名称: 测试集
样本数量: 2915
数据集总规模: 10373
标签:
- ATR(Automatic Text Recognition，自动文本识别)
- HTR(Handwritten Text Recognition，手写文本识别)
- OCR(Optical Character Recognition，光学字符识别)
- 现代
- 手写
---

# IAM行级数据集

## 目录
- [IAM行级数据集](#iam行级数据集)
- [目录](#目录)
- [数据集说明](#数据集说明)
- [数据集概述](#数据集概述)
- [语言说明](#语言说明)
- [数据集结构](#数据集结构)
- [数据实例](#数据实例)
- [数据字段](#数据字段)

## 数据集说明

- **主页**: [IAM手写数据库](https://fki.tic.heia-fr.ch/databases/iam-handwriting-database)
- **相关论文**: [The IAM-database: an English sentence database for offline handwriting recognition](https://doi.org/10.1007/s100320200071)
- **联系方式**: [TEKLIA](https://teklia.com)

## 数据集概述

IAM手写数据库包含手写英语文本表单，可用于训练和测试手写文本识别器，以及开展书写者识别与验证相关实验。

请注意，所有图像均已调整至固定高度128像素。

### 语言说明

数据集中所有文档均采用英语书写。

## 数据集结构

### 数据实例

{
'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=2467x128 at 0x1A800E8E190>,
'text': 'put down a resolution on the subject'
}

### 数据字段

- `image`: PIL.Image.Image类型对象，承载对应图像。请注意，当通过`dataset[0]["image"]`访问图像列时，图像文件会自动完成解码。解码大量图像文件可能会耗费可观时间，因此建议优先采用"样本索引后接图像列"的访问方式，即始终优先使用`dataset[0]["image"]`而非`dataset["image"][0]`。
- `text`: 对应图像的标签转录文本。