caveman273/aida-typewritten
typewritten OCR training data from AIDA-project Dataset Summary This dataset contains typewritten textline images and their transcriptions from the AIDA-project. It is a subset of the full AIDA dataset, containing only the best-quality typwritten annotations — lines where the annotator was confident about every character. The majority of lines are in Finnish, with some Swedish, English, French, and German. Supported Tasks The dataset was created for… See the full description on the dataset page: https://huggingface.co/datasets/caveman273/aida-typewritten.
typewritten OCR training data from AIDA-project
Dataset Summary
This dataset contains typewritten textline images and their transcriptions from the AIDA-project. It is a subset of the full AIDA dataset, containing only the best-quality typwritten annotations — lines where the annotator was confident about every character. The majority of lines are in Finnish, with some Swedish, English, French, and German.
Supported Tasks
The dataset was created for optical char recognition (OCR).
Languages
The majority of the textlines are in Finnish, but some are in Swedish and English. In addition to this there are few French and German textlines.
Dataset structure
Data Instances
Each row contains:
image: the textline image (PNG bytes + filename)text: the transcriptionfile_name: the original image filename
Data Fields
Data Splits
This dataset contains only the "best" typewritten annotations (every character understood by the annotator). The number in parentheses shows the additional "semi" lines (some characters unclear) not included here.
Dataset Creation
Source Data
The data is collected from Central Archives for Finnish Business (ELKA). It consists of various document types including letters, ship records, business publications etc. It includes correspondence between companies, organizations and the public.
Who are the source language producers?
Given the various types of archival material used in annotation, the scope of producers of the original texts is broad. It includes private individuals and employees of different companies.
Annotations
The textlines were first cropped out of the original image and then transcribed. If the transcription was unclear, the annotator marked it as either "somewhat unclear" or "unclear". Unclear images were discarded, but the "somewhat discarded" images are presented here as in the "semi" annotation files. The rough estimate for "somewhat unclear" class is that less than 100% and more than 50% of the characters are unclear.
Who are the annotators?
Annotators were employees of National Archives of Finland and ELKA.
Synthetic data
As a way to increase the amount of training data, we created synthetic data by using this library https://github.com/Belval/TextRecognitionDataGenerator. We collected Finnish books from https://www.gutenberg.org/ and Finnish magazines from https://archive.org/ and created different kinds of textlines. The different kinds include normal textlines, rotated textlines, textlines following a sinosoidal curve and textlines where characters are subjected to noise.
Personal and Sensitive Information
The dataset is not anonymized, so individuals' names can be found in the dataset.