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---
license: mit
language:
- fr
task_categories:
- image-to-text
pretty_name: PyLaia RIMES
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_examples: 10188
- name: validation
num_examples: 1138
- name: test
num_examples: 778
dataset_size: 12104
---
# PyLaia RIMES Dataset
## Table of Contents
- [PyLaia RIMES Dataset](#pylaia-rimes-dataset)
- [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)
- [Data Splits](#data-splits)
## Dataset Description
- **Homepage:** [ARTEMIS](https://artemis.telecom-sudparis.eu/2012/10/05/rimes/)
- **PapersWithCode:** [Papers using the RIMES dataset](https://paperswithcode.com/dataset/rimes)
- **Point of Contact:** [TEKLIA](https://teklia.com)
### Dataset Summary
Briefly summarize the dataset, its intended use and the supported tasks. Give an overview of how and why the dataset was created. The summary should explicitly mention the **languages** present in the dataset (possibly in broad terms, e.g. *translations between several pairs of European languages*), and describe the domain, topic, or genre covered.
### Languages
All the documents in the dataset are written in French.
## Dataset Structure
### Data Instances
```
{
'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=2560x128 at 0x1A800E8E190,
'text': 'Comme indiqué dans les conditions particulières de mon contrat d'assurance'
}
```
### Data Fields
- `image`: A PIL.Image.Image object containing the image. Note that when accessing the image column: 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.
### Data Splits
Describe and name the splits in the dataset if there are more than one.
Describe any criteria for splitting the data, if used. If there are differences between the splits (e.g. if the training annotations are machine-generated and the dev and test ones are created by humans, or if different numbers of annotators contributed to each example), describe them here.
Provide the sizes of each split. As appropriate, provide any descriptive statistics for the features, such as average length. For example:
| | train | validation | test |
|-------------------------|------:|-----------:|-----:|
| Input Sentences | | | |
| Average Sentence Length | | | |
|