Some GT of the ocropus models found

[mittagessen]

Some GT of the ocropus models found

[jbaiter]

The raw Google-1000-Books dataset is still available from Google, although it's a bit cumbersome to get to:

wget http://commondatastorage.googleapis.com/books/icdar2007/README.txt
wget http://commondatastorage.googleapis.com/books/icdar2007/VERSION.txt
for i in $(seq -f "%04g" 0 9999); do
    wget -c "http://commondatastorage.googleapis.com/books/icdar2007/Volume_$i.zip"
done

I don't know if the data is really suitable as ground truth, though. Looking at a few volumes, it looks like it comes straight out of Google's OCR system (which as of 2011 was likely Tesseract), with a lot of errors.

[amitdo]

UNLV ISRI Document Collection for Research in OCR and Information Retrieval
https://code.google.com/archive/p/isri-ocr-evaluation-tools/downloads

[amitdo]

High Performance OCR for Printed English and Fraktur using LSTM Networks (2013)
Thomas M. Breuel, Adnan Ul-Hasan, Mayce Al Azawi. Faisal Shafait

For English input, we used the University of Washington (UW3) dataset, representing 1600 pages of document images from scientific journals and other common sources.
Text line images and corresponding ground-truth text were extracted from the data set using the layout ground-truth and transcriptions provided with UW3. Text lines containing mathematical equations were not used during either training or testing. Overall, we used a random subset of 95,338 text-lines in the training set and 1,020 text lines in the test set.

Fraktur

The training set was a fairly small set of about 20,000 text lines of mostly artificially
generated characters.