hidapi VS OpenCV

On the computer, write a program (the "host" or "server") that talks over the raw HID protocol. It is open ended how you do this, but IME both the Python pyhidapi and C hidapi were simple enough to get something started. The trickiest part might be getting the program to run with the permissions to talk the raw HID protocol (at least on Linux, there was some udev rule to set up). Read the documentation for these libraries for details about how to get set up.

now I'm trying to figure out what to do with the next step for building my own host. Am I supposed to put this test file in my qmk code? or run it on my computer as it's own separate program? https://github.com/libusb/hidapi/blob/master/hidtest/test.c

HIDAPI

I did star https://github.com/libusb/hidapi too, as well as this GitHub.

I used ffigen to get the bindings from hidapi.h and cleaned up quite some of the resulting output to make it Dart compatible. Quite some typedef and some minor stuff.

I figured out the problem with JoyconLib! The hidapi.dll file was broken so I replaced it with a new file from https://github.com/libusb/hidapi/releases and not it's working.

https://github.com/libusb/hidapi#prerequisites

Install the HID API, instructions here: https://github.com/libusb/hidapi

Inspired by https://askubuntu.com/questions/699138/logitech-k380-bluetooth-keyboard-make-function-keys-default and https://github.com/libusb/hidapi, it's almost re-implementation of hidapi actually, with dart:ffi calling the syscall directly.

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.