VoxelPlugin VS OpenCV

There's also a performance question. While we can now use Blueprint nativization to convert Blueprints to C++ the result will be a fairly naive version, fast enough for most purposes but not if you're trying to push every bit of performance. This is where you're looking at making sure you're hitting things such as using the CPU cache as well as possible for an ECS system (Look at ENTT or Flecs if you want to see what they're about and why you'd want one), or a system needing to process massive amounts of data quickly such as the Voxel Plugin.

There are some existing plugins, such as the voxel plugin that you can use, though keep in mind features like multiplayer are behind a paywall.

Is unreal/unity efficient? No. There is large amounts of overhead, as they were designed for other types of games. Voxels have many unique optimisations that won't be available. You'll need to do a lot of "patch-work" to the engine. This patch-work may make this overhead extremely small, and there are some very powerful projects on these engines that are efficient (e.g., Voxel Plugin). Having to ignore a lot of the a game engines features, such as physics, is a key reason people decide to just go through the extra effort of making their own game engine.

Thank you! I am using the Voxel Plugin for Unreal to generate my planets, there is a free version you can play around with: https://voxelplugin.com/

I used Voxel plugin

Anyway here it is https://voxelplugin.com/ you can research all about it.

No one has yet mentioned VoxelPlugin for Unreal which you could use alongside a Lua Unreal plugin.

Try https://voxelplugin.com/

I'd look at Voxel Plugin. It supports runtime edits.

Hmmm I don't have a lot of experience with that but I used the Voxel plugin once to make a planet map and it was pretty good. There's even a free version if you don't want to invest. Most other plugins cost hundreds so that's good. It has a ton of features, check it out.

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.