configuration.txt

[data paths]
path_local =  ./DRIVE_datasets_training_testing/
train_imgs_original = DRIVE_imgs_train.hdf5
train_groundTruth = DRIVE_groundTruth_train.hdf5
train_border_masks = DRIVE_borderMasks_train.hdf5
test_imgs_original = DRIVE_imgs_test.hdf5
test_groundTruth = DRIVE_groundTruth_test.hdf5
test_border_masks = DRIVE_borderMasks_test.hdf5
model_path=./models/

[experiment name]

name=Select_Dense_Transfomer_unet_double_decoder



[data attributes]
#Dimensions of the patches extracted from the full images
patch_height = 48
patch_width = 48
channels = 3

dataset= DRIVE

[training settings]
#number of total patches:
N_subimgs_positive = 150000
N_subimgs_negative = 150000
N_subimgs = 300000
#if patches are extracted only inside the field of view:
inside_FOV = False
#Number of training epochs
N_epochs = 30
batch_size = 64

[testing settings]
N_group_visual = 1
#Compute average in the prediction, improve results but require more patches to be predicted
average_mode = True
# stride_height=5 old version
stride_height = 5
stride_width = 5
#if running with nohup
nohup = False