libvips VS tesseract-ocr

After some research, I found libvips, a demand-driven, horizontally threaded image processing library. It is designed to run quickly while using as little as memory as possible.

Sharp is a fast and efficient image optimization Node.js module that makes use of the native libvips library.

h2non/bimg can handle both if the underlying libvips is compiled with support for both formats.

if you're using linux (which it doesn't seem so) there's also vispdisp https://github.com/jcupitt/vipsdisp which is based on https://github.com/libvips/libvips which will likely take over how images are decoded in the future for everything, at least methodology wise.

The magic happens by way of a library called Libvips, which contains an ultra-high-speed low-memory image resizer.

imagor uses one of the most efficient image processing library libvips. It is typically 4-8x faster than using the quickest ImageMagick and GraphicsMagick settings.

Try the solutions here: https://github.com/libvips/libvips/issues/2479

in that case maybe take a look at https://github.com/libvips/libvips

libvips v8.6+ or ImageMagick for image analysis and transformations

You will also need to install the Tesseract OCR engine, which can be downloaded and installed from the following link: https://github.com/tesseract-ocr/tesseract

PyTesseract Module [ Github ] EasyOCR Module [ Github ] PaddlePaddle OCR [ Github ]

It uses teseract for the OCR https://github.com/tesseract-ocr/tesseract

Last update was pretty recent, and the git mentions tesseract 5 as a dep. so it's likely moved on a bit from when you last tried it:

https://github.com/tesseract-ocr/tesseract/releases

I suppose it depends on your use-case. For personal tasks like this it should be more than sufficient, and won't need user details/cc or whatever to use it.

Tesseract is an open-source OCR engine developed by Google. It is highly accurate and supports multiple languages. This library will do all the heavy lifting for us. We'll use it in this tutorial to quickly read the text in some images.

> Does android even have native OCR?

Tesseract? https://github.com/tesseract-ocr/tesseract

Install Google Tesseract OCR (additional info how to install the engine on Linux, Mac OSX and Windows). You must be able to invoke the tesseract command as tesseract. If this isn’t the case, for example because tesseract isn’t in your PATH, you will have to change the “tesseract_cmd” variable pytesseract.pytesseract.tesseract_cmd. Under Debian/Ubuntu you can use the package tesseract-ocr. For Mac OS users. please install homebrew package tesseract.

OCR detection will be done with Tesseract.

I’ve used Tesseract for this. It seems to work well with tabular data. https://github.com/tesseract-ocr/tesseract

If you go this route, then using an app that can convert your handwritten notes to a digital format (indexed text), will give you a good balance between cognitive processing and efficient data storage/management; you can likely find many such apps on the App Store or Google Play. If you're interested in something more hands-on, on Arch you can probably experiment with Tesseract OCR in an interesting way (Example).