In fact, if you’re interested in pursuing this further, you could actually try some experiments here. Once you finish this assignment, you could take the dataset and convert it to grayscale images. Then try the training again using the 4 layer network that we use in the second assignment here in Week 4. How does the accuracy compare? Of course there are lots of other variables to tweak here, so getting complete and convincing results may not be so straightforward. But it would be pretty easy to just do a basic experiment for curiousity and see if there is any noticeable difference. If you do get motivated to try this, please let us know what you discover one way or the other! You always learn something interesting even if the results turn out not to be as good. That’s useful information as well …
In terms of the idea of experimenting with variations on the test case here in Week 4 Assignment 2, here’s a thread about some experiments with modifying the balance of positive and negative samples in the train and test datasets.