I have a dataset with medical images int16. I have tried to calculate mean and std to use Normalize.
Like this
mean_tr = (train_x.float().mean()/10209)
std_tr = (train_x.float().std()/10209)
mean_te = (test_x.float().mean()/11108)
std_te = (test_x.float().std()/11108)
Where 10209 is the value of the biggest pixel in train, and 11108 in test.
I have something like this :
mean_tr = tensor(0.0439) std_tr = tensor(0.0616)
mean_te = tensor(0.0425) std_te = tensor(0.0586)
I then used this values to Normalize data, with tranform, and I print some values to see what happened. I saw values like 60000, after this step, very big values, and smalest was -0.7. Why? Can you help me with some ideas how to deal with this images?
Thanks