python-mss VS OpenCV

VidGear provides an easy-to-use, highly extensible, Multi-Threaded + Asyncio Framework on top of many state-of-the-art specialized libraries like OpenCV, FFmpeg, ZeroMQ, picamera, starlette, streamlink, pafy, pyscreenshot, aiortc and python-mss at its backend, and enable us to flexibly exploit their internal parameters and methods, while silently delivering robust error-handling and real-time performance.

I'm using a python library called mss https://github.com/BoboTiG/python-mss

You can use PyGetWindow to get the info of a window based on its name, and then use your screenshot library of choice to get that part of the screen (personally I use mss because it’s fast and cross-platform).

mss can do this efficiently and cross-platform. What’s the use-case?

That was one of the main reasons I made my library pythonic-cv - I had solved the problem once (not super well), and realised I was going to have to do it again repeatedly, and thought that was a waste of time. While I was at it I added some additional nice features like iterating over a camera/video stream, using a context manager to handle cleaning it up/releasing it afterwards, and convenient processing and threaded recording loops. I've recently also added mss integration so you can use your screen as a video input in the same way as a camera or video file.

You may also want to consider using mss for taking screenshots efficiently, which allows specifying the screen region you want when taking the screenshot. It has OpenCV/numpy support.

That error shouldn't be happening, and is most likely some kind of error in mss. If you haven't already, I'd suggest trying to update your mss (e.g. python3 -m pip install --upgrade mss, and if that doesn't help then you should create an Issue on the GitHub page, mentioning your OS and what you're doing that's causing that error.

If you’re after speed I’d recommend mss for screenshots/recording, and tesserocr instead of pytesseract (note in particular the OpenCV option.

Your blog post claims to do image preprocessing with pyautogui, but I couldn’t find any image processing steps? Also, if you’re only using pyautogui to take screenshots, you might want to look at a library like mss, which is more efficient and also has support for multiple monitors :-)

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.