Teach TOK

A Collaborative System for Interactive Machine Teaching

Train your Image Classifier as a team and inspect its performance both on your side or with your team !

With this web application, you and your team can collectively teach an image classifier using individual interfaces. Each team member will have access to different features organized into pages:

  • Homepage - Here, you can view your model's performance as a team, including charts showing the evolution of classes and accuracy rate.
  • Navbar - This feature helps you track the model's training progress with a status bar, and allows you to reload it or access settings.
  • Teach - This section enables you to input images, view the model's predictions, and add them to your dataset, with the option to correct associated labels.
  • Share - Here, you can access the images you've personally added and assess the impact of these additions on the model's training by recalculating its performance with the collective dataset.
  • Dataset - This section provides access to all instances contained in the collective dataset, organized by label.

Additionally, you can access more advanced features to analyze the model's decisions on the collective dataset:

  • Inspector - Utilizing a confusion matrix, you can gain insight into how the collective dataset is labeled by the model. By clicking on specific categories, you can further inspect True and Predicted labels, along with confidence plots for selected images.
  • Chat - Here, you have the embedded possibility to exchange information about your personal data and send custom messages to debate or discuss aspects of the model's decisions or the progression of your teaching as a group.
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