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QTAI is a personal C++ windows project I've started back in 2023 for school.
It is a Qt application to visualize the prediction results of both KNN and KMC on the MNIST database.
It features asynchronous usage of both algorithms once their common data and labels files are drag and dropped by displaying dataset infos, the current number's guess with visualization (KNN, for each number and each k so takes a while) and the current k accuracy (KMC).
Having already worked with the Win32 API, I wanted to try Qt as a more modern UI library while exploring a new subject such as from-scratch machine learning.
Thanks to Gerard TAYLOR for the tutorial.
You will need:
- Visual Studio 2022
- Qt
Configure Qt to be detected by Visual Studio, their extension helps.
Launch the Visual Studio project from QTAI.vcxproj and start it using the top "Local Windows Debugger" button.
Drag and drop the data file train-images-idx3-ubyte first and then the labels file train-labels-idx1-ubyte to be able to start the algorithms with their respective buttons.