I am trying to create a model that can clean pictures of noise, blur, high luminosity etc, but I do not know how to do that. I have tried to search for it a lot, and I couldn't find anything that could properly teach me, as I am very new in this.
At first, I download a file containing 5000+ clean pictures and their degraded version. Then, I load a training set of 500 pictures in two
ndarray datasets called
shape=(500, 576, 720, 3).
Then, I do not know what to do with these two datasets, I do not know how to train a model. I vaguely have an idea, which is giving the
clean_dataset to the model as the
label_dataset, however I am not sure it is the good way of doing it.
Thank you for helping me.