Hi @Hagen_Hagen
Take a look at those notebooks for showing confusion matrix with sklearn and matplotlib:
  

      github.com
  

  
    farmaker47/Yamnet_Speech_commands/blob/main/Yamnet_Speech_commands.ipynb 4


    {
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Yamnet_Speech_commands.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {



  This file has been truncated. show original

  

  
    
    
  

  


and
  

      github.com
  

  
    farmaker47/Yamnet_Speech_commands/blob/main/Yamnet_Plain_Speech_commands.ipynb 2


    {
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Yamnet_Plain_Speech_commands.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {



  This file has been truncated. show original

  

  
    
    
  

  


Finally this one with Model maker classes:
  

      github.com
  

  
    farmaker47/Yamnet_Speech_commands/blob/main/Model_Maker_Speech_commands.ipynb


    {
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Model_Maker_Speech_commands.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {



  This file has been truncated. show original

  

  
    
    
  

  


I think by combining you can print confusion matrix also for Image Classification task.
Best