unstructured VS awesome-document-understanding

Compare unstructured vs awesome-document-understanding and see what are their differences.

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unstructured awesome-document-understanding
12 4
6,682 1,128
17.7% -
9.8 4.5
5 days ago 12 months ago
HTML
Apache License 2.0 -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

unstructured

Posts with mentions or reviews of unstructured. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-02-20.

awesome-document-understanding

Posts with mentions or reviews of awesome-document-understanding. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-11-06.
  • [R] Are there any open-source implementations of Document Understanding pipelines?
    1 project | /r/MachineLearning | 4 Nov 2022
    I have worked on several Document Understanding (DU) projects for my company during the last year. We've mainly used UiPath and Google's DocumentAI.
  • Pdfsandwich
    6 projects | news.ycombinator.com | 6 Nov 2021
    While trying to find a specific project I recalled, I encountered this list of projects which might be of interest: https://github.com/tstanislawek/awesome-document-understandi...

    The project I had in mind was similar to this one but I can't remember the name currently: https://github.com/tabulapdf/tabula

    However, if you're looking for a ML-based, invoice-specific project looks like the other comment to your reply might be more useful.

  • Extract informations from invoices with machine learning
    2 projects | /r/deeplearning | 7 Apr 2021
    Check out this repository for inspiration: https://github.com/tstanislawek/awesome-document-understanding
  • [P] Curated List of Document Understanding (DU) Papers & Resources.
    1 project | /r/deeplearning | 7 Apr 2021
    In the last few years, I spent a lot of time working on automate business processes of big companies and seeing rising interest in DU topics (especially from Key Information Extraction field). Therefore, I create a list https://github.com/tstanislawek/awesome-document-understanding of resources to make easier to track all the papers out there which are relevant to this topic.

What are some alternatives?

When comparing unstructured and awesome-document-understanding you can also consider the following projects:

llmsherpa - Developer APIs to Accelerate LLM Projects

InvoiceNet - Deep neural network to extract intelligent information from invoice documents.

Parsr - Transforms PDF, Documents and Images into Enriched Structured Data

Awesome-pytorch-list - A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

ragflow - RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.

awesome-ocr

pdfGPT - PDF GPT allows you to chat with the contents of your PDF file by using GPT capabilities. The most effective open source solution to turn your pdf files in a chatbot!

awesome-document-understandi

llama_parse - Parse files for optimal RAG

awesome-huggingface - 🤗 A list of wonderful open-source projects & applications integrated with Hugging Face libraries.

vault-ai - OP Vault ChatGPT: Give ChatGPT long-term memory using the OP Stack (OpenAI + Pinecone Vector Database). Upload your own custom knowledge base files (PDF, txt, epub, etc) using a simple React frontend.

tocPDF - Generates bookmarks from the table of contents already available at the beginning of pdf files.