JoJoGAN VS tesseract-ocr

I've tried style transfer and some GANs like this one: https://github.com/mchong6/JoJoGAN

🔗 https://github.com/mchong6/JoJoGAN

And I quite liked and wanted to train this model with my own dataset, and always fell into the same error CUDA Out of Memory again and again. After searching across the internet for answers ended up finding it -> here.

Code for https://arxiv.org/abs/2112.11641 found: https://github.com/mchong6/JoJoGAN

Since you want to use multiple images for style, it reminded me of this pipeline. In it you can take a dataset of style images and finetune a pretrained model for 500-1000 iterations to achieve the style from these images on new ones. I am not sure if that pipeline is what you need or not though, because it is built for faces in particular, but maybe you can take inspiration from their approach for a generic method.

Here are some models that do that with face images that I have tried out: AnimeGANv3 - this one just came out ArcaneGAN - for faces JoJoGAN - for faces

github: https://github.com/mchong6/JoJoGAN

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).