Disclaimer: Unless otherwise stated I don't own any rights to data linked on this page. All usage of external data must comply with their licensing.
This folder should contain all data used in the project. Most of the data are too large to be included here, so you have to download them and placed them according to instructions below. If you have any suggestion or issues with the dataset, send me an email or create a new issue in the repository.
All together it should total in about 188000 images. After extraction, each word is named as: <word>_<dataset-num>_<timestamp>.png. The way of labelling can be changed, currently '_' is prohibited in all words. The number of a dataset is written behind each name in brackets. For example: car_1_1528457794.9072268.png - file corresponds to the image of a word 'car' from Breta’s data.
After downloading these datasets, there are scripts in src/data/ folder which extract words from each dataset and place them in words-final/ folder under each dataset folder. Another script takes all words from all words-final/ folders and normalized them. Normalized words are placed in processed/ folder. Finally, you run the script which separates data into training, validation and test sets, placing them into sets/ folder.
5000 images
All data owned by @Breta01 are available on this link (distributed under the same license as this repository). The data should be placed either in raw/breta/ or processed/breta/ folder according to their location in archive from the link below. (I removed the Czech accents from words. If you want to use them, you have to recover them using CSV files containing: word_without_accents, original_word in UTF-8 encoding.)
85000 images
The data can be obtained from the link below. First, you have to register (please read the terms and conditions). Then on the download page, from link data/ascii download words.txt file and from data/words download words.tgz file. Both of these files should be placed in raw/iam/ folder. Then you should extract the words.tgz archive into words/ folder.
http://www.fki.inf.unibe.ch/databases/iam-handwriting-database
84000 images
First, read the terms and conditions. After that, you can download cvl-database-1-1.zip archive. Place this archive into raw/cvl/ folder and extract it (it should create cvl-database-1-1/ folder).
https://zenodo.org/record/1492267
11700 images (only number strings)
Once again read the licensing. Then you can download ORAND-CAR-2014.tar.gz archive and place it into raw/orand/ folder. Here you should extract the archive, resulting in ORAND-CAR-2014/ folder.
http://www.orand.cl/en/icfhr2014-hdsr/#datasets
5200 images
First, read the README file (the first link). After that, you can download lob.tar and numbers.tar archives and place them into raw/camb/ folder. Here you should extract each archive into the corresponding folder lob.tar to lob/ and numbers.tar to numbers/.
ftp://svr-ftp.eng.cam.ac.uk/pub/data/handwriting_databases.README
ftp://svr-ftp.eng.cam.ac.uk/pub/data/
dictionaries/ folder contains a list of most common words for simple autocorrection.
It contains photos of pages which are used for testing of page detection, words detection and testing in general.
characters/ folder contains single character images. There is only a few of them and they are already pre-processed. I advise using different dataset (for example NIST Special Database 19). Currently, there is no pre-processing script for it.
- NIST Special Database 19: https://www.nist.gov/srd/nist-special-database-19
- MNIST - the legend (only numbers): http://yann.lecun.com/exdb/mnist/