Datasets:
metadata
license: mit
language:
- fr
task_categories:
- image-to-text
pretty_name: PELLET Casimir Marius
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_examples: 842
data_files: parquet/train.parquet
- name: validation
num_examples: 122
data_files: parquet/validation.parquet
- name: test
num_examples: 125
data_files: parquet/test.parquet
dataset_size: 1089
tags:
- atr
- htr
- ocr
- historical
- handwritten
PELLET Casimir Marius - Line level
Table of Contents
Dataset Description
Dataset Summary
The PELLET Casimir Marius dataset includes 100 annotated French letters written between 1914 and 1918. Annotations were done at line-level and all images do not have any text.
Note that all images are resized to a fixed height of 128 pixels.
Languages
All the documents in the dataset are written in French.
Dataset Structure
Data Instances
{
'image': <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=1684x128 at 0x1A800E8E190,
'text': 'LE HAVRE - panorama de la rue de Paris'
}
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.
Usage with the PyLaia library
- clone the repository or at least the
data
folder - you can use this dataset to reproduce the training, train a new model, infer on any of the set