remove default params

Author: taigw

segmentation/JSRT2/config/train_test.cfg

@@ -10,7 +10,6 @@ test_csv  = ../JSRT/config/jsrt_test.csv
 
 train_batch_size = 4
 
-load_pixelwise_weight = False
 # modality number
 modal_num = 1
 
@@ -20,24 +19,13 @@ valid_transform = [NormalizeWithMeanStd, LabelConvert, LabelToProbability]
 test_transform  = [NormalizeWithMeanStd]
 
 NormalizeWithMeanStd_channels = [0]
-NormalizeWithMeanStd_mean = None
-NormalizeWithMeanStd_std  = None
-NormalizeWithMeanStd_mask = False
-NormalizeWithMeanStd_random_fill = False
-NormalizeWithMeanStd_inverse     = False
 
 LabelConvert_source_list = [0, 255]
 LabelConvert_target_list = [0, 1]
-LabelConvert_inverse = False
 
 RandomCrop_output_size = [240, 240]
-RandomCrop_foreground_focus = False
-RandomCrop_foreground_ratio = None
-RandomCrop_mask_label       = None
-RandomCrop_inverse     = False
 
 LabelToProbability_class_num = 2
-LabelToProbability_inverse   = False
 
 [network]
 # this section gives parameters for network
@@ -50,7 +38,7 @@ net_type = MyUNet2D
 class_num     = 2
 in_chns       = 1
 feature_chns  = [4, 16, 24, 32, 48]
-dropout       = [0.0, 0.0, 0.3, 0.3, 0.4, 0.5]
+dropout       = [0.0, 0.0, 0.3, 0.4, 0.5]
 bilinear      = True
 
 [training]
@@ -64,9 +52,6 @@ MyFocalDiceLoss_Enable_Class_Weight = True
 MyFocalDiceLoss_beta = 1.5
 class_weight = [0.2, 1.0]
 
-CrossEntropyLoss_Enable_Pixel_Weight = False
-CrossEntropyLoss_Enable_Class_Weight = False
-
 # for optimizers
 optimizer     = Adam
 learning_rate = 1e-3
@@ -94,12 +79,6 @@ gpus       = [0]
 # checkpoint mode can be [0-latest, 1-best, 2-specified]
 ckpt_mode         = 0
 output_dir        = result
-evaluation_mode   = True
-test_time_dropout = False
-
-# use test time augmentation
-tta_mode              = 0
-infer_sliding_window  = False
 
 # convert the label of prediction output
 label_source = [0, 1]

segmentation/prostate/config/train_test.cfg

@@ -10,7 +10,6 @@ test_csv  = config/data/image_test.csv
 
 train_batch_size = 4
 
-load_pixelwise_weight = False
 # modality number
 modal_num = 1
 
@@ -21,29 +20,20 @@ test_transform  = [NormalizeWithMeanStd, Pad]
 
 
 NormalizeWithMeanStd_channels = [0]
-NormalizeWithMeanStd_mean = None
-NormalizeWithMeanStd_std  = None
-NormalizeWithMeanStd_mask = False
-NormalizeWithMeanStd_random_fill = False
-NormalizeWithMeanStd_inverse     = False
 
 RandomFlip_flip_depth  = False
 RandomFlip_flip_height = True
 RandomFlip_flip_width  = True
-RandomFlip_inverse     = False
 
 RandomCrop_output_size = [48, 48, 48]
 RandomCrop_foreground_focus = True
 RandomCrop_foreground_ratio = 0.5
 Randomcrop_mask_label       = [1]
-RandomCrop_inverse     = False
 
 LabelToProbability_class_num = 2
-LabelToProbability_inverse   = False
 
 Pad_output_size = [8, 8, 8]
 Pad_ceil_mode   = True
-Pad_inverse     = True
 
 [network]
 # this section gives parameters for network
@@ -64,8 +54,6 @@ trilinear     = True
 gpus       = [0]
 
 loss_type     = DiceLoss
-DiceLoss_enable_pixel_weight = False
-DiceLoss_enable_class_weight = False
 
 # for optimizers
 optimizer     = Adam
@@ -93,15 +81,8 @@ gpus       = [0]
 # checkpoint mode can be [0-latest, 1-best, 2-specified]
 ckpt_mode         = 0
 output_dir        = result
-evaluation_mode   = True
-test_time_dropout = False
-
-# use test time augmentation
-tta_mode = 0
 
 sliding_window_enable = True
 sliding_window_size   = [96, 96, 96]
 sliding_window_stride = [96, 96, 96]
 
-
-