####################################################
#### lOAD TEST ###
####################################################
vdata = h5py_mat2npy('valid_np/edited/valOb_Crop.mat')
vtruths = h5py_mat2npy('valid_np/edited/valGt_Crop.mat')
#vdata_mat = spio.loadmat('test_np_noise/obhatGausWeak{}Noise128.mat'.format(level), squeeze_me=True)
#vtruths_mat = spio.loadmat('valid_np/obGausN1S128val.mat', squeeze_me=True)
#vdata = vdata_mat['obhatGausWeak128']
#vdata = preprocess(vdata, data_channels)
#vtruths = preprocess(vtruths_mat['obGausN1S128val'], truth_channels)
valid_provider = image_util.SimpleDataProvider(vdata, vtruths)
####################################################
#### PREDICT ###
####################################################
predicts = []
valid_x, valid_y = valid_provider('full')
num = valid_x.shape[0]
for i in range(num):
print('')
print('')
print('************* {} *************'.format(i))
"""
#mat_loader.load_from_net(DS='elips')
#-- Training Data --#
train_data_path = 'data/train_elips.mat'
test_data_path = 'data/test_elips.mat'
download_elipse_dataset(train_data_path, test_data_path)
data_train, label_train = get_data_from_file(mat_file=train_data_path)
data_test, label_test = get_data_from_file(mat_file=test_data_path)
#data_channels = 1#data.shape[2]
#data = preprocess(data, data_channels) # 4 dimension -> 3 dimension if you do data[:,:,:,1]
#label = preprocess(label, truth_channels)
data_provider = image_util.SimpleDataProvider(data_train, label_train)
valid_provider = image_util.SimpleDataProvider(data_test, label_test)
#-- Validating Data --#
#vdata_mat = spio.loadmat('valid_np/obhatGausWeak128val_40.mat', squeeze_me=True)
#vtruths_mat = spio.loadmat('valid_np/obGausWeak128val_40.mat', squeeze_me=True)
# vdata = vdata_mat['obhatGausWeak128val']
# vdata = preprocess(vdata, data_channels)
# vtruths = preprocess(vtruths_mat['obGausWeak128val'], truth_channels)
####################################################
#### NETWORK ###
####################################################
"""
here we specify the neural network.