RenPy VS OpenCV

Ren'Py - Visual Novel Engine. Python, Cython, C

Here are 2 interactive story game engines: * https://www.renpy.org/ * https://twinery.org/

###################################################### Credits label credits(): $ credits_speed = 20 scene black show text '''{b}Blabla:{/b}\n\n{i}Me{/i}\n\n\n {b}Clacla:{/b}\n\n{i}You{/i}\n\n\n {b}Dladla:{/b}\n\n {i}He{/i}\n\n\n {b}Hlahla:{/b}\n\n{i}She{/i}\n\n\n {b}Brrr:{/b}\n\n{i}Grrr{/i}\n\n\n {b}Drrr:{/b}\n\n{i}Hrrr{/i}\n\n\n\n\n Made with {a=https://www.renpy.org/}Ren'Py{/a} v[renpy.version_only]\n\n\n{b}Ren'Py License:{/b}\n[renpy.license!t]''' at Move((0.5, 1.0), (0.5, -1.0), credits_speed, xanchor=0.5, yanchor=0) with Pause(credits_speed+4) return init screen about(): tag menu add "main_menu" use game_menu(_("Credits"), scroll="viewport"): style_prefix "about" fixed: xalign 0.5 yalign 0.5 viewport id "vp": draggable True mousewheel True has vbox: spacing 3 textbutton _("whattheheeeeellll") action Jump("credits") init -1 style about_label is gui_label init -1 style about_label_text is label_text init -1 style about_text is gui_text init -1 style about_label_text: size gui.label_text_size

You can also check https://www.renpy.org/

I can't speak for in-game stuff, but I encourage anyone who wants to to try making a visual novel! It's way easier than you'd think it is. The only tools I really used were Ren'Py (the engine), CSP and Paint.net (for the art), and KKT (for the models).

If you want full creative control, I would suggest going your own way and making indie games. The visual novel engine, Ren'py, is free to use and fairly easy to learn. They have a lot of helpful resources including Lemmasoft Forums, which is a great place to ask questions and find talent such as artists (we found our sprite/CG artist, BG artist, and GUI artist here, along with one of our voice actors).

Make your text game, but not "within ChatGPT". Instead, make a game. You could use Ren'Py or really anything.

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.