π Process PDFs, Word documents and more with spaCy
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Updated
Mar 8, 2025 - Python
π Process PDFs, Word documents and more with spaCy
Detectron2 for Document Layout Analysis
Trained Detectron2 object detection models for document layout analysis based on PubLayNet dataset
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Proof of concept of training a simple Region Classifier using PdfPig and ML.NET (LightGBM). The objective is to classify each text block in a pdf document page as either title, text, list, table and image.
Trained Detectron2 object detection models for document layout analysis based on PubLayNet dataset
A collection of machine learning apis in fastapi, can be deployed with uvicorn, hypercorn or docker
Enable the line numbering and implement the LayoutVisitor to count rows in a document.
π Pre-trained YOLOv11 for Document Layout Analysis. Instantly find text π, tables π, and figures πΌοΈ. Fast, accurate, and ready to use! β¨
Obtain document layout elements located under the mouse pointer and show information in the tooltip
Add a description, image, and links to the document-layout topic page so that developers can more easily learn about it.
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