Decid3D

Introduction to Machine Learning using Opencv and VTK for 3D visualisation

Load VTK and compile 9.4.1 from
https://vtk.org/download/

and Download compiled version of Opencv version 4.10 (file opencv_world4100.dll)
https://opencv.org/blog/opencv-4-10-0/

Or (at your own risk)

Load VTK and OPENCV4100 DLL files from this link
https://1drv.ms/u/c/e3cc9bf07901913a/ERJ1x21DXjRCltFea12UVqEBPsbI2w30c1NZB8vPzbkyFg?e=x78xDe
Unzip DLL in the same directory as Decid_3D_2025_mod.exe

Install Visual studio 2022 redistribuable
https://learn.microsoft.com/en-us/cpp/windows/latest-supported-vc-redist?view=msvc-170

Run Decid_3D_2025_mod.exe

Load csv file
Train and Test SVM, Multilayer perceptron (neural network), Knn, Random Forest, Boosting, EM (non supervised) etc
2D and 3D visualisation of data and classification boudary are available (data 2 features or 3 features)
For more features, only a 2D projection of data is available.
Application : classifiers : for image acquisition/segmentation, the first webcam is used.

This software is for teaching and testing purpose only. Used in Universite Bourgogne Europe
Master Traitement du Signal et des Images

CSV format : one sample = one line
class number, feature 1, feature 2
class number, feature 1, feature 2

Example 5 samples, 3 classes, in 2D

0,0.35,0.4
0,0.15,0.2
1,0.25,0.2
1,0.15,0.6
2,0.18,0.16

Example of Neural Network bundaries