settings.ini 1.63 KB
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[DATA]
data_directory = "/well/win-biobank/projects/imaging/data/data3/subjectsAll/"
data_split_flag = True
train_percentage = 90
validation_percentage = 5
train_data_file = "/dMRI/autoptx_preproc/tractsNormSummed.nii.gz"
train_output_targets = "/fMRI/rfMRI_25.dr/dr_stage2.nii.gz"
test_data_file = "/dMRI/autoptx_preproc/tractsNormSummed.nii.gz"
test_target_file = "/fMRI/rfMRI_25.dr/dr_stage2.nii.gz"

[TRAINING]
training_batch_size = 5
test_batch_size = 5
use_pre_trained = False
pre_trained_path = "saved_models/preTrained.pth.tar"
experiment_name = "experiment_name"
learning_rate = 1e-4
optimizer_beta = (0.9, 0.999)
optimizer_epsilon = 1e-8
optimizer_weigth_decay = 1e-5
number_of_epochs = 10
loss_log_period = 50
learning_rate_scheduler_step_size = 3
learning_rate_scheduler_gamma = 1e-1
use_last_checkpoint = True
final_model_output_file = "finetuned_alldata.pth.tar"

[NETWORK]
kernel_heigth = 5
kernel_width = 5
kernel_classification = 1
input_channels = 1
output_channels = 64
convolution_stride = 1
dropout = 0.2
pool_kernel_size = 2
pool_stride = 2
#Valid options: upconv, upsample, unpool
up_mode = "upconv"
number_of_classes = 1

[MISC]
save_model_directory = "saved_models"
model_name = "BrainMapper"
logs_directory = "logs"
device = 1
experiments_directory = "experiments"

[EVAL]
trained_model_path = "saved_models/model.pth.tar"
data_directory = "/well/win-biobank/projects/imaging/data/data3/subjectsAll/"
data_file = "/dMRI/autoptx_preproc/tractsNormSummed.nii.gz"
output_targets = "/fMRI/rfMRI_25.dr/dr_stage2.nii.gz"
data_list = "test.txt"
#Valid options: coronal, sagittal, axial
orientation = "coronal"
saved_predictions_directory = "predictions"