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So far, only a handful of font types (Calibri, Times New Roman, etc.) are considered for the extraction of features. However, we may encounter many different fonts. We need to implement the following:

• During feature extraction, identify all possible font types
• After processing all documents, run another step, over all the fonts encountered, to extract features (font occurrence) for all the types.

This feature will be part of the feature extraction process, contained in server/application/feature.

Running the feature extraction with textline leads to a ValueError.

ValueError: Found array with 0 sample(s) (shape=(0, 1)) while a minimum of 2 is required by AgglomerativeClustering.

Despite we will add more complex models to extract features, perhaps add the following extra, to each of the tree levels

• Pages: percent of page covered, normalized page number
• Textbox: TBD
• Lines: TBD

We need to create one entry per page in the Table DB. The keys to fill in are quite straightforward, and the only question that arises is, when to do it??

• I do believe the best would be to just do it after the corresponding XML file is extracted. Hence, from the XML we read the number of pages, and we just create one entry per page.
• But we could also do it after the extraction of features.

Since this is just a matter of commit this to the DB, could you decide @c-jordi when is the best moment and implement it?
Thanks!