EasyOCR
tika-python
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EasyOCR | tika-python | |
---|---|---|
38 | 4 | |
21,882 | 1,411 | |
3.1% | - | |
4.6 | 2.2 | |
about 1 month ago | 12 days ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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.
EasyOCR
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Leveraging GPT-4 for PDF Data Extraction: A Comprehensive Guide
PyTesseract Module [ Github ] EasyOCR Module [ Github ] PaddlePaddle OCR [ Github ]
- OCR a lot of hand written invoice and records?
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[P] EasyOCR in C++!
I just uploaded my C++ implementation of EasyOCR, a well known ocr library for python. Also dusted some cobwebbs from some audio related projects as well, feel free to leave feedback or contribute! I only implemented the most salient parts, so certainly could use some community help! Cheers!
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OCR at Edge on Cloudflare Constellation
EasyOCR is a popular project if you are in an environment where you can use run Python and PyTorch (https://github.com/JaidedAI/EasyOCR). Other open source projects of note are PaddleOCR (https://github.com/PaddlePaddle/PaddleOCR) and docTR (https://github.com/mindee/doctr).
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Donut: OCR-Free Document Understanding Transformer
The main one was https://github.com/JaidedAI/EasyOCR, mostly because, as promised, it was pretty easy to use, and uses pytorch (which I preferred in case I wanted to tweak it). It has been updated since, but at the time it was using CRNN, which is a solid model, especially for the time - it wasn't (academic) SOTA but not far behind that. I'm sure I could've coaxed better performance than I got out of it with some retraining and hyperparameter tuning.
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Help with OCR of pixel-y numbers
Anyways, you can give a shot to EasyOCR, pretty solid and flexible
- How to perform document OCR?
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Python unexpectedly quits (macOS ventura, M1)
The easyocr library: https://github.com/JaidedAI/EasyOCR
- I made a website for a friend who owns a restaurant. He's wondering if there's a way to upload a picture of his menu daily. What is the best way to do this?
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Raspberry Pi Easyocr
Not used it on a Pi but maybe a Docker version (if there is one) would run? Compose file here
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
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.
What are some alternatives?
PaddleOCR - Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices)
txtai - π‘ All-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows
tesseract-ocr - Tesseract Open Source OCR Engine (main repository)
layout-parser - A Unified Toolkit for Deep Learning Based Document Image Analysis
doctr - docTR (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning.
py-pdf-parser - A Python tool to help extracting information from structured PDFs.
OpenCV - Open Source Computer Vision Library
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.
awesome-colab-notebooks - Collection of google colaboratory notebooks for fast and easy experiments
paperai - π π€ Semantic search and workflows for medical/scientific papers
tesserocr - A Python wrapper for the tesseract-ocr API
paperetl - π βοΈ ETL processes for medical and scientific papers