However I tried to train it to recognize some images of characters from an anime (so a little different than facial recognition), and I managed to break the model: achieving 64% error with significant number of examples per class. I think one downside is Lobe doesn't expose how potentially overconfident the model is. I would love the ability to take the existing model and test it on a new image that I can import into the app.
EDIT: I would love to see the following in a future version:
1. What are the percentages associated with each image per class. I see that an image was misclassified, but did it at least include my desired class in its top 5 predicted classes?
2. Test the model on unlabeled inputs directly in the app to see how well the model might generalize. I would like to see a "Test" tab on the left once training is complete.
3. View other metrics of model goodness like F-1 score and training details like CV partitions in the app somehow.
Again, this is a really cool idea :)