# Dedicated file to store global variables
# This file can help to reduce hard_coding and to change only once variables in different files and functions.
# In particular for this project the tasks share the following information.

base_dir = './Datasets'

# Datasets urls
dataset_url = 'https://data.vision.ee.ethz.ch/cvl/DIV2K/'
set5_url = 'https://uofi.box.com/shared/static/kfahv87nfe8ax910l85dksyl2q212voc.zip'
set14_url = 'https://uofi.box.com/shared/static/igsnfieh4lz68l926l8xbklwsnnk8we9.zip'
bsd100_url = 'https://uofi.box.com/shared/static/qgctsplb8txrksm9to9x01zfa4m61ngq.zip'
# urban100_url = 'https://uofi.box.com/shared/static/65upg43jjd0a4cwsiqgl6o6ixube6klm.zip'

# Important parameters
# Although not compulsory, a good choice could be setting the value of batch_dim and test_dim so that:
# (number of training images - test_dim ) / batch_dim returns an integer
# and, number of validation images / batch_dim returns an integer
# and, number of test images / batch_dim returns an integer
batch_dim = 10
patch_size = 56
test_dim = 30

# Channel-wise Mean computed on the entire training DIV2K dataset. The mean is computed via the compute_dataset_mean()
# function within the module called utilities.
RGB_MEAN_A = [114.3569244, 111.5630249, 103.15689794]
RGB_MEAN_B = [114.33866302, 111.52755002, 103.09925148]
RGB_MEAN_HR = [114.35629928, 111.561547, 103.1545782]
