improvment ideas from 2022 edition

[neptunes5thmoon]

Timing

CARE notebook: ~90 min till we went over questions (cause it was lunchtime) ca. 10:30-12:00
N2N notebook: ~90 min (ca. 15:30-17:00) for students to work on, ca. 30 min to discuss in the group (3 students had finished the notebook at that point)
N2V notebook: ~30 min (ca.17:30-18:00), then discuss solutions in ca 5 min

Problems/Ideas for improvement:

• Small bug: logdir needs to exist for tensorboard to work
• some students had other notebooks from previous exercises running and then got cryptic OOM errors
• for N2N: students struggled with understanding that the SEM data comes as one tiff stack of several images and then should be resaved as single images for training
• N2N: clarify difference between model.predict and model.keras_model.predict (model.predict under the hood splits the image into patches to predict on, maybe more)
• N2V: in addition to the assert that the training/test data is there, check that the folders do not contain other tif files - or switch implementation to load_imgs
• useful addition would be a task to look at patch size vs receptive field size