I have been moving forward on my testing but I keep returning to a question that I cant answer. I may just be the one confused here but I am going to try and reword my question. Although I think I may be close to the solution based previous responses.
– So, when using a convolutional neural network (CNN) it is my understanding that its not possible to discard/ignore some pixels since those would leave behind holes. This may be dealt with by eo-learn I am not sure. If we include NO_DATA labeled pixels then that will potentially create training problems in the CNN because it would learn to associate pixel values to a label which is not actually a proper label. I see you say that these pixels are disregarded and not used for training/testing, but I dont understand if this creates some sort of issue. In my code we have a lot of pixels with no-data labels and we are basically trying to come up with the best way to deal with them. This is where we got confused about NaN values vs No-data labels.
I hope I worded this in a way others can understand, I am still confused myself but I am getting there!