settings.ini 1.83 KB
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[DATA]
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data_folder_name = "datasets"
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use_data_file = False
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data_directory = "../well/win-biobank/projects/imaging/data/data3/subjectsAll/"
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data_file = "../well/win-biobank/projects/imaging/data/data3/subjectsAll/subj_22k.txt"
k_fold = None
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data_split_flag = False
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test_percentage = 5
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subject_number = None
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train_list = "train.txt"
validation_list = "validation.txt"
test_list = "test.txt"
train_data_file = "dMRI/autoptx_preproc/tractsNormSummed.nii.gz"
train_output_targets = "fMRI/rfMRI_25.dr/dr_stage2.nii.gz"
validation_data_file = "dMRI/autoptx_preproc/tractsNormSummed.nii.gz"
validation_target_file = "fMRI/rfMRI_25.dr/dr_stage2.nii.gz"
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[TRAINING]
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training_batch_size = 2
validation_batch_size = 2
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use_pre_trained = False
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pre_trained_path = "saved_models/finetuned_alldata.pth.tar"
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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
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use_last_checkpoint = False
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final_model_output_file = "finetuned_alldata.pth.tar"

[NETWORK]
kernel_heigth = 5
kernel_width = 5
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kernel_depth = 5
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kernel_classification = 1
input_channels = 1
output_channels = 64
convolution_stride = 1
dropout = 0.2
pool_kernel_size = 2
pool_stride = 2
up_mode = "upconv"
number_of_classes = 1

[MISC]
save_model_directory = "saved_models"
model_name = "BrainMapper"
logs_directory = "logs"
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device = 0
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experiments_directory = "experiments"

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[EVALUATION]
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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"
orientation = "coronal"
saved_predictions_directory = "predictions"
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