tika-python
EasyOCR
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tika-python | EasyOCR | |
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4 | 38 | |
1,395 | 21,535 | |
- | 3.0% | |
3.2 | 4.6 | |
8 months ago | 7 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.
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.
EasyOCR
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Leveraging GPT-4 for PDF Data Extraction: A Comprehensive Guide
PyTesseract Module [ Github ] EasyOCR Module [ Github ] PaddlePaddle OCR [ Github ]
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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.
- 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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[P]Modern open-source OCR capabilities and which model to choose
I've used EasyOCR for number recognition tasks. Works fairly well. https://github.com/JaidedAI/EasyOCR
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[D] Looking for a fast OCR repo
Do you have hardware acceleration available? If so, check out https://github.com/JaidedAI/EasyOCR
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[P] Training to read PDF documents. Any ideas?
If all you need to do is OCR, check out https://github.com/JaidedAI/EasyOCR , it's a similar architecture to the cloud services, without all the $. You'll end up with extracted text and bounding boxes for it.
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Tesseract.js – Pure JavaScript OCR
I've had good results with EasyOCR, much better than Tesseract. I agree with you, Tesseract has performed very poorly in my experience.
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I have created a tool to translate any kind of VN by image analysis.
Currently the tool supports 2 different OCRs. PaddleOCR and EasyOCR. In both cases, the OCR has a specific model for Japanese characters. They work quite well, as long as the characters have clear contrast. The problem is that these OCR implement Torch, which makes the program very heavy. I am looking for a way to optimize this.
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)
tesseract-ocr - Tesseract Open Source OCR Engine (main repository)
doctr - docTR (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning.
OpenCV - Open Source Computer Vision Library
awesome-colab-notebooks - Collection of google colaboratory notebooks for fast and easy experiments
tesserocr - A Python wrapper for the tesseract-ocr API
LaTeX-OCR - pix2tex: Using a ViT to convert images of equations into LaTeX code.
Tesseract.js - Pure Javascript OCR for more than 100 Languages 📖🎉🖥
deep-text-recognition-benchmark - Text recognition (optical character recognition) with deep learning methods, ICCV 2019
CRAFT-pytorch - Official implementation of Character Region Awareness for Text Detection (CRAFT)
layout-parser - A Unified Toolkit for Deep Learning Based Document Image Analysis
scantailor-advanced - ScanTailor Advanced is the version that merges the features of the ScanTailor Featured and ScanTailor Enhanced versions, brings new ones and fixes.