tika-python
layout-parser
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tika-python | layout-parser | |
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4 | 6 | |
1,395 | 4,369 | |
- | 3.2% | |
3.2 | 0.0 | |
8 months ago | 22 days ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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tika-python
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Document Parsing - an unsolved problem?
At my previous job we had the same problem which we solved by using Tika. We called it on the server along with other stuff, but there is also a Python binding.
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Extract text from PDF
Hey, I’ve spent quite a bit of time looking at extracting text as accurately as possibly from PDFs, it’s turns out that it is not as simple as it might seem. It is especially tricky once you get a wide variety of PDFs (including PDFs with image based text or tables). While I unfortunately cannot share the code I used to extract this text, I will tell you that for what I think your doing, the best solution will require a few things. First you should pick a good module. I’ve spent a long time going over open source solutions to this and the best two I’d say are Excalibur and Apache Tika .
Tika is from Apache so yes its original code base is Java but it has bindings in other languages. Checkout Tika-Python!
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Extract text from documents
The Textractor instance is the main entrypoint for extracting text. This method is backed by Apache Tika, a robust text extraction library written in Java. Apache Tika has support for a large number of file formats: PDF, Word, Excel, HTML and others. The Python Tika package automatically installs Tika and starts a local REST API instance used to read extracted data.
layout-parser
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Crates for converting PDF's into Markdown
I built my own solution using a combination of Tesseract and OpenCV (in python). But even though the source PDF content is computer generated, I still get sporadic OCR errors. After writing my solution, I came across this https://github.com/Layout-Parser/layout-parser which might be a better starting point for dealing with PDFs but I haven't tried it yet.
- Amateur programmer here. Will Rust be used in backend for software in the future?
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Extract text from PDF
One of the tools I'm excited about (but haven't used in production) is LayoutParser. It's open-source, and can do some document image analysis especially on non-generic docs.
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Document Classification
One project that I saw not to long ago which might be useful is this: https://github.com/Layout-Parser/layout-parser
What are some alternatives?
EasyOCR - Ready-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
py-pdf-parser - A Python tool to help extracting information from structured PDFs.
txtai - 💡 All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
BCNet - Deep Occlusion-Aware Instance Segmentation with Overlapping BiLayers [CVPR 2021]
ssd_keras - A Keras port of Single Shot MultiBox Detector
contextualized-topic-models - A python package to run contextualized topic modeling. CTMs combine contextualized embeddings (e.g., BERT) with topic models to get coherent topics. Published at EACL and ACL 2021.
paperai - 📄 🤖 Semantic search and workflows for medical/scientific papers
simpletransformers - Transformers for Information Retrieval, Text Classification, NER, QA, Language Modelling, Language Generation, T5, Multi-Modal, and Conversational AI
paperetl - 📄 ⚙️ ETL processes for medical and scientific papers
Machine-Learning-Cyrillic-Classifier - This is a web app where you can draw a letter in the russian alphabet and the ML algorithm will predict the letter that you drew.