Augmentation, titan script

config/default.ini

@@ -25,12 +25,20 @@ batch_size_train: 1
 batch_size_validation: 2
 n_epochs: 200
 
+[preprocessing]
+erode_segmentation: 3
+
 [normalization]
 zero_center: True
 mean_pixel: 0.66200809792889126
 
-[preprocessing]
-erode_segmentation: 3
+[augmentation]
+augment: True
+flip: True
+zoom: 0.08 ;Not working yet
+rotation: 16
+translation: 3
+
 
 [misc]
 multiprocess_load_augmentation: False

config/small_subset.ini

@@ -1,2 +1,2 @@
 [dataset]
-subset: 100
+subset: 2

config/titan_x_default.ini

@@ -0,0 +1,12 @@
+[info]
+experiment: U-net large batch size (14), 0.00005 LR
+
+[updates]
+learning_rate: 0.00005
+momentum: 0.94
+batch_size_train: 14
+batch_size_validation: 28
+
+[misc]
+multiprocess_load_augmentation: True
+save_every_n_epoch: 3

src/dataset.py

@@ -7,6 +7,7 @@
 import cPickle as pickle
 import loss_weighting
 import skimage.morphology
+from augment import augment
 
 from params import params as P
 
@@ -19,14 +20,8 @@ def get_image(filename):
     with gzip.open(filename.replace('lung','nodule'),'rb') as f:
         truth = pickle.load(f)
 
-    #Random flips
-    #if np.random.randint(2)==0:
-    #    lung = lung.transpose(1,0)
-    #    truth = truth.transpose(1,0)
-    #    lung[:,:] = lung[::-1,:]
-    #    truth[:,:] = truth[::-1,:]
-    #    lung = lung.transpose(1,0)
-    #    truth = truth.transpose(1,0)
+    if P.AUGMENT:
+        lung, truth = augment([lung,truth])
 
     #We do not care about the outside
     outside = np.where(lung==0,True,False)

src/learn.py

@@ -38,7 +38,6 @@
     initialize_logger(os.path.join(model_folder, 'log.txt').format(model_name))
 
     P.write_to_file(os.path.join(model_folder, 'config.ini'))
-    logging.info("MODEL NAME {}".format(model_name))
     logging.info(P.to_string())
 
 
@@ -139,7 +138,7 @@
 
         # Then we print the results for this epoch:
         logging.info("Epoch {} of {} took {:.3f}s".format(
-            epoch + 1, num_epochs, time.time() - start_time))
+            epoch + 1, P.N_EPOCHS, time.time() - start_time))
 
         for name, train_metric, val_metric in zip(metric_names, train_metrics, val_metrics):
             name = name.rjust(10," ") #Pad the name until 10 characters long

src/params.py

@@ -8,7 +8,7 @@ def __init__(self, config_file_path):
         cf = ConfigParser()
         read_from = cf.read(config_file_path)
 
-        print "Loaded configuration from (in order)", read_from
+        print "Loaded configurations from (in order)", read_from
 
         self.CONFIG = cf
         cf.set('info','config_file', config_file_path)
@@ -54,6 +54,16 @@ def __init__(self, config_file_path):
         self.ZERO_CENTER = cf.getboolean('normalization', 'zero_center')
         self.MEAN_PIXEL = cf.getfloat('normalization', 'mean_pixel')
 
+
+        # Augmentation
+        self.AUGMENT = cf.getboolean('augmentation', 'augment')
+        self.AUGMENTATION_PARAMS = {
+            'flip': cf.getboolean('augmentation', 'flip'),
+            'zoom_range': (1.-cf.getfloat('augmentation', 'zoom'),1.+cf.getfloat('augmentation', 'zoom')),
+            'rotation_range': (-cf.getfloat('augmentation', 'rotation'),cf.getfloat('augmentation', 'rotation')),
+            'translation_range': (-cf.getfloat('augmentation', 'translation'),cf.getfloat('augmentation', 'translation'))
+        }
+
         # Misc
         self.MULTIPROCESS_LOAD_AUGMENTATION = cf.getboolean('misc', 'multiprocess_load_augmentation')
         self.SAVE_EVERY_N_EPOCH = cf.getint('misc', 'save_every_n_epoch')