Closed ss756 closed 1 year ago
Dear Suyash,
Eynollah uses a mixture of models based on the input and options wished by the user. Eynollah by default can detect main texts, separators, images, background, and marginals. If you are interested in headings and drop capitals you need to apply -fl option. Based on your source test dataset (if they are very dark or bright ) you can turn -ib (--input_binary) option. As you see based on the dataset and user-case Eynollah uses different models. You can share some of your documents and I may help you how you can use Eynollah to get optimum results :)
We should also come up with better names and introduce versioning for the individual models @vahidrezanezhad - cf. https://github.com/qurator-spk/eynollah/issues/5.
The models and their names should then be shortly described in the models section of the README.
Hi, I would love to test out your pre-trained models on some documents. Could you point me to the right model to perform pixel wise region (text, image, separator) classification. Would be of gr8 help. Keep up the amazing work!!