openresty VS OpenCV

OpenResty? Open.

Anyways, I recommend you check out OpenResty’s website (https://openresty.org) first. OpenResty offers binary packages, but you can also compile from source code. I used the latter option (because I have an obsession with compiling stuff from scratch), and it didn’t take me long to do it, about 4-5 minutes.

Varnish somewhat predates Nginx. Varnish has VCL, Varnish Configuration Language, giving flexible "edge" rule-based features. On the other hand, OpenResty, an open-source fork of Nginx, does a similar thing with a Lua-based language.

> Is Lua backend-able?

Yes and some of the largest web infrastructures in the world run on it! I'm not sure if it's still true, but it's my understanding the CloudFlare runs it at the edge. I personally know of several other very _large services_ running it at massive scale.

[0] https://openresty.org

Okay.

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.