a b/settings.ini 

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[COMMON]





  
  

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save_model_dir = "saved_models"





  
  

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model_name = "quicknat"





  
  

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log_dir = "logs"





  
  

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device = 1





  
  

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exp_dir = "experiments"





  
  

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[DATA]





  
  

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data_dir = "datasets/COMBINED/axial"





  
  

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train_data_file = "Data_train.h5"





  
  

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train_label_file = "Label_train.h5"





  
  

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train_class_weights_file = "Class_Weight_train.h5"





  
  

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train_weights_file = "Weight_train.h5"





  
  

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test_data_file = "Data_test.h5"





  
  

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test_label_file = "Label_test.h5"





  
  

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test_class_weights_file = "Class_Weight_test.h5"





  
  

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test_weights_file = "Weight_test.h5"





  
  

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labels = ["Background", "Left WM", "Left Cortex", "Left Lateral ventricle", "Left Inf LatVentricle", "Left Cerebellum WM", "Left Cerebellum Cortex", "Left Thalamus", "Left Caudate", "Left Putamen", "Left Pallidum", "3rd Ventricle", "4th Ventricle", "Brain Stem", "Left Hippocampus", "Left Amygdala", "CSF (Cranial)", "Left Accumbens", "Left Ventral DC", "Right WM", "Right Cortex", "Right Lateral Ventricle", "Right Inf LatVentricle", "Right Cerebellum WM", "Right Cerebellum Cortex", "Right Thalamus", "Right Caudate", "Right Putamen", "Right Pallidum", "Right Hippocampus", "Right Amygdala", "Right Accumbens", "Right Ventral DC"]





  
  

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[NETWORK]





  
  

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num_class = 33





  
  

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num_channels = 1





  
  

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num_filters = 64





  
  

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kernel_h = 5





  
  

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kernel_w = 5





  
  

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kernel_c = 1





  
  

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stride_conv = 1





  
  

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pool = 2





  
  

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stride_pool = 2





  
  

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#Valid options : NONE, CSE, SSE, CSSE





  
  

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se_block = "CSSE"





  
  

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drop_out = 0.2





  
  

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[TRAINING]





  
  

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exp_name = "finetuned_alldata_axial"





  
  

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final_model_file = "finetuned_alldata_axial.pth.tar"





  
  

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learning_rate = 1e-4





  
  

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train_batch_size = 5





  
  

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val_batch_size = 5





  
  

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log_nth = 50





  
  

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num_epochs = 10





  
  

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optim_betas = (0.9, 0.999)





  
  

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optim_eps = 1e-8





  
  

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optim_weight_decay = 0.00001





  
  

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lr_scheduler_step_size = 3





  
  

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lr_scheduler_gamma = 0.1





  
  

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#Uses the last checkpoint file from the exp_dir_name folder





  
  

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use_last_checkpoint = True





  
  

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use_pre_trained = False





  
  

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pre_trained_path = "saved_models/IXI_fsNet_axial.pth.tar"





  
  

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[EVAL]





  
  

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eval_model_path = "saved_models/quicknat_finetuned_1.pth.tar"





  
  

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data_dir = "/home/masterthesis/shayan/nas_drive/Data_Neuro/OASISchallenge/FS"





  
  

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label_dir = "/home/masterthesis/shayan/nas_drive/Data_Neuro/OASISchallenge"





  
  

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volumes_txt_file = "datasets/MALC/test_volumes.txt"





  
  

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#Valid options : Neo, FS





  
  

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remap_config = "Neo"





  
  

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#Valid options : COR, AXI, SAG





  
  

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orientation = "COR"





  
  

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save_predictions_dir = "predictions"





  
  

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data_id = "MALC"