Extract key Information from Document using Hugging Face DocQuery Pipeline | PDF | LayoutLM | Donut

Document Visual Question Answering (DocVQA) or DocQuery: Document Query Engine, seeks to inspire a “purpose-driven” point of view in Document Analysis and Recognition research.

You can now parse PDFs of documents and invoices to get answers using the Hugging Face document-question-answering pipeline!

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[ngoduyvu]

Really love your video about extract data from pdf sources

[NickWindham]

I just subscribed. Please keep sharing the easiest to use cutting edge tools. 😀

[TejasMA-tx]

Hey Karndeep! Great Video! How would i be able to annotate a custom dataset on documents with questions and answers and finetune a docvqa model?

[sivachellappan]

Interesting Video. Thanks for sharing this. Do you have any video to explain how to train these models?

[henkhbit]

Interesting tutorial. It would be nicer if there's a library that can output an invoice based on the block of information. For example the address block transformed as dictionary, the invoices details as a table and the total info as the last block as a dictionary 2.

[Ashesoftheliving]

Great Tutorials! Keep up the good work😀

[NickWindham]

Your videos are gold. Thank you for sharing!

[Kaan]

How is prepare custom dataset for this ?

[aadilrafiq]

Thanks sir

Sir can you explain multiclass classification using layoutlm

Sir, where is the notebook of this code??

[TejaKumarGoud]

when i run this code:
pipe(image = img_path, question="what is the amount")

i am getting an error saying that:
ValueError: If you provide an image without word_boxes, then the pipeline will run OCR using Tesseract, but pytesseract is not available

but i installed all the required Library's.

@karndeep singh Help me on this.