scantailor-universal VS OpenCV

You could try ScanTailor: https://scantailor.org/

There's also https://scantailor.org/ (and a maintained fork at https://github.com/4lex4/scantailor-advanced ) which semi-automates unwarping and other corrective tasks in scanned books.

Scantailor (https://scantailor.org) is the tool for self-scanned books that exist in images (png, jpg, etc). However, I usually use Irfanview with PDF plugin (https://irfanview.com - download both Irfanview and the Plugins from this home page) I have elsewhere in r/PDF shown how you can do batch splitting of two-page scans, clean up muddy pages (yellowed or browned) . In the Reddit search box, search for Irfanview in this subreddit. Irfanview has lots of commands, so the instructions are very specific, and which I did trial and error on before posting. This is because Irfanview is an image processor and viewer, and PDF transformations are recent to the last couple of years. Note that you will want to run OCR after Irfanview processing, as Irfanview treats PDFs as images (which is what you have now).

Scantailor https://scantailor.org/ might be useful.

scantailor is a good open source option that has a lot of features centered towards this process.

I use OCRmyPDF on a regular basis to OCR journal articles my library sends me.

I've found it works great on English but (with appropriate language packs installed) works poorly on Greek and Hebrew. It also makes no effort to understand the layout of pages (e.g., tables).

The project is fantastic, though. I've often considered building a web frontend that cleans up PDFs and then OCRs them using OCRmyPDF.

For cleaning, check out https://scantailor.org/

Next is the cleanup. Scan Tailor is the best game in town for this, but it's a dead project. Instead, there are two forks that have picked up where the original developers left off. Scan Tailor Advanced is my current fork of choice, though Scan Tailor Universal tries to add new usability features. For whatever reason, only Advanced makes full use of my CPU, so it's several times faster than Universal for the time being.

Referenceshttps https://www.kaggle.com/datasets/riyaelizashaju/skin-disease-image-dataset-balanced?fbclid=IwAR3wbTp8l5yo_5fx6HAX8Vd2-9cca3khAc8EiBGFObaALfdVid29IuB_rYE https://keras.io/api/applications/vgg/ https://www.tensorflow.org/tutorials/images/cnn?hl=th https://opencv.org/

Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks.

You'll need to plot the predictions. There are a few open source tools to do that, supervision is one you can use (https://github.com/roboflow/supervision) and opencv is another common option (https://github.com/opencv/opencv)

You might be able to achieve this with scripting tools like AutoHotkey or Python with libraries for GUI automation and image recognition (e.g., PyAutoGUI https://pyautogui.readthedocs.io/en/latest/, OpenCV https://opencv.org/).

The OpenCV4NodeJs A.I. library provides an interface for calling OpenCV routines in NodeJS.