set training batch size

Author: taigw

segmentation/JSRT/config/train_test.cfg

@@ -8,6 +8,8 @@ train_csv = config/jsrt_train.csv
 valid_csv = config/jsrt_valid.csv
 test_csv  = config/jsrt_test.csv
 
+train_batch_size = 4
+
 load_pixelwise_weight = False
 # modality number
 modal_num = 1
@@ -55,7 +57,6 @@ bilinear      = False
 # list of gpus
 gpus = [0]
 
-batch_size    = 4
 loss_type     = DiceLoss
 DiceLoss_enable_pixel_weight = False
 DiceLoss_enable_class_weight = False
@@ -82,7 +83,6 @@ iter_save  = 2000
 [testing]
 # list of gpus
 gpus       = [0]
-batch_size = 4
 
 # checkpoint mode can be [0-latest, 1-best, 2-specified]
 ckpt_mode         = 0

segmentation/JSRT/image_convert.py

@@ -57,7 +57,7 @@ def convert_JCRT_labels(input_dir, output_dir):
             label.save(output_full_name)
 
 if __name__ == "__main__":
-    JSRT_root  = "data/JSRT"
+    JSRT_root  = "/home/guotai/disk2t/data/JSRT"
     input_image_dir  = JSRT_root + "/All247images"
     output_image_dir = JSRT_root + "/image"
     convert_JCRT_images(input_image_dir, output_image_dir)

segmentation/JSRT2/config/train_test.cfg

@@ -8,6 +8,8 @@ train_csv = ../JSRT/config/jsrt_train.csv
 valid_csv = ../JSRT/config/jsrt_valid.csv
 test_csv  = ../JSRT/config/jsrt_test.csv
 
+train_batch_size = 4
+
 load_pixelwise_weight = False
 # modality number
 modal_num = 1
@@ -53,7 +55,7 @@ bilinear     = True
 [training]
 # list of gpus
 gpus          = [0]
-batch_size    = 4
+
 loss_type     = MyFocalDiceLoss
 MyFocalDiceLoss_Enable_Pixel_Weight = False
 MyFocalDiceLoss_Enable_Class_Weight = True
@@ -83,7 +85,6 @@ iter_save  = 2000
 [testing]
 # list of gpus
 gpus       = [0]
-batch_size = 4
 
 # checkpoint mode can be [0-latest, 1-best, 2-specified]
 ckpt_mode         = 0

segmentation/fetal_hc/config/train_test.cfg

@@ -8,6 +8,8 @@ train_csv = config/fetal_hc_train.csv
 valid_csv = config/fetal_hc_valid.csv
 test_csv  = config/fetal_hc_test.csv
 
+train_batch_size = 4
+
 load_pixelwise_weight = False
 # modality number
 modal_num = 1
@@ -63,7 +65,6 @@ bilinear      = True
 # list of gpus
 gpus = [0]
 
-batch_size    = 4
 loss_type     = DiceLoss
 DiceLoss_enable_pixel_weight = False
 DiceLoss_enable_class_weight = False
@@ -91,9 +92,6 @@ iter_save  = 5000
 # list of gpus
 gpus       = [0]
 
-# note that the images have different sizes, batch size for inference should be 1
-batch_size = 1   
-
 # checkpoint mode can be [0-latest, 1-best, 2-specified]
 ckpt_mode         = 1
 output_dir        = result

segmentation/prostate/config/train_test.cfg

@@ -8,6 +8,8 @@ train_csv = config/data/image_train.csv
 valid_csv = config/data/image_valid.csv
 test_csv  = config/data/image_test.csv
 
+train_batch_size = 4
+
 load_pixelwise_weight = False
 # modality number
 modal_num = 1
@@ -60,7 +62,6 @@ trilinear     = True
 # list of gpus
 gpus       = [0]
 
-batch_size  = 4
 loss_type     = DiceLoss
 DiceLoss_enable_pixel_weight = False
 DiceLoss_enable_class_weight = False
@@ -87,11 +88,19 @@ iter_save  = 3000
 [testing]
 # list of gpus
 gpus       = [0]
-batch_size = 1
 
 # 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 = 1
+
+infer_sliding_window  = 1
+sliding_window_size   = [272, 480]
+sliding_window_stride = [272, 480]
+
+
+