tesserocr
EasyOCR
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tesserocr | EasyOCR | |
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17 | 38 | |
1,928 | 21,882 | |
- | 3.1% | |
5.9 | 4.6 | |
5 days ago | 29 days ago | |
Python | Python | |
MIT License | Apache License 2.0 |
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tesserocr
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Tesserocr
Did you read the instructions for windows? https://github.com/sirfz/tesserocr
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[Question] I am trying to segment the image using python.
If you’re using tesserocr then you can use OpenCV images directly, so you can just extract the relevant image rows (e.g. query_image = main_image[prev_line:this_line]) and process then without needing to save each image.
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Python app that will take a picture, scan it and upload that information into a excel file.
This tutorial is a good start towards getting the data from an image of a form with a known structure. I’d personally recommend using tesserocr (actual library binding, more efficient, more functionality) instead of pytesseract (requires images to be saved before processing, uses command-line options in a subprocess instead of binding to the library), but both should work (that tutorial uses pytesseract, which is also what u/Iceberg_Bart_Simpson linked to).
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[Question] Working on a simple OCR program but the text from the image is returned in a backward order and it has trouble reading multiple words on a line
Side note, but I’d suggest using tesserocr over pytesseract. It’s an actual binding to the tesseract library, so comes with numerous efficiency and interface benefits, and can operate on OpenCV images directly (whereas pytesseract saves them to disk first).
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Optimizing ImageGrab and pytesseract
If you’re after speed I’d recommend mss for screenshots/recording, and tesserocr instead of pytesseract (note in particular the OpenCV option.
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Is pytesseract the only option for OCR in python?
tesserocr is an actual binding to the tesseract library, and is better in practically every way than pytesseract (more efficient, more options for usage, doesn’t require saving images to disk before they can be processed, and more).
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OCR with Python
If you have an electronically created pdf (not scanned) and you’re just wanting to run OCR on embedded images then you’ll want a pdf library that can extract the figure images for you, and then you can use tesserocr to run OCR on those images.
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Pytesseract/OCR: RuntimeError: can't start new thread when no multi-threading
If you want a suggestion, use tesserocr instead of Pytesseract. It’s an actual binding to the tesseract library (Python talks to it directly, instead of calling a program as a subprocess), which means it runs more efficiently, you can process multiple images sequentially with the same OCR engine (pytesseract has to start a process and a new engine for every image that gets processed), you get access to more functionality options, and a bunch of other beneficial stuff. If you’re doing preprocessing with OpenCV it’s even possible to pass those arrays directly to tesseract in memory, whereas Pytesseract requires that you save each image to a file before it can process it.
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Can´t get part of this REGEX-pattern to work?
As a somewhat unrelated side note, I’d strongly suggest using tesserocr instead of pytesseract, and even more so if you’re working with opencv as well. It’s a true library binding which means it’s more efficient, you have more functionality available to you, you can process multiple images with the same Tesseract engine, and you can process opencv images directly (compared to pytesseract which saves them as a file first and then calls the tesseract CLI as a subprocess).
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OCR Video Game Text
In Python the library PyTesseract constructs a command to run and calls Tesseract via the command-line as a subprocess, which is inefficient if you have more than one image to process, because it has to reinitialize the OCR engine for every image. tesserocr is a different library which came around a bit later, which is a direct binding to the Tesseract library, so you can initialise the engine once and process several images with it, and for images that are stored in memory (e.g. OpenCV arrays that you’ve done some processing on) you can process them directly instead of having to save them as individual files (which PyTesseract requires).
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
What are some alternatives?
doctr - docTR (Document Text Recognition) - a seamless, high-performing & accessible library for OCR-related tasks powered by Deep Learning.
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)
pytesseract - A Python wrapper for Google Tesseract
tesseract-ocr - Tesseract Open Source OCR Engine (main repository)
OCRmyPDF - OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them to be searched
OpenCV - Open Source Computer Vision Library
Face Recognition - The world's simplest facial recognition api for Python and the command line
awesome-colab-notebooks - Collection of google colaboratory notebooks for fast and easy experiments
Kornia - Geometric Computer Vision Library for Spatial AI
LaTeX-OCR - pix2tex: Using a ViT to convert images of equations into LaTeX code.