Austrian National Library and NewsEye project · PyLaia · Published October 21, 2021
ONB_Newseye_GT_M1+
Text Recognition
Description
The model works well with German "Fraktur" script from late 18th century to mid of 20th century. It also reads roman typeface which might be included in the documents.
The model was created in the NewsEye project and is based on training data coming from the ANNO collection of the Austrian National Library.
Note: the model is trained on German language documents and will therefore be less performant on other languages.
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Very low error rate1.1% CER
Character Error Rate (CER) measures the percentage of characters incorrectly recognised. Lower is better. This model scored 1.1% on its validation set. As a rule of thumb, a CER below 10% is considered good for most handwritten material.
Measured on the model's own validation data. Results on your documents may differ depending on handwriting style, document condition, language, and how closely your material resembles the training data.
Words442,121
Lines80,572
Training Pages214
Model ID37738