Wide resnet

config/default_resnet.ini

@@ -0,0 +1,53 @@
+[info]
+experiment: ResNet default settings
+name: resnet
+
+[dataset]
+pixels: 64
+n_classes: 2
+channels: 1
+subset: None
+filenames_train: ./../../data/cadV2_0.5mm_64x64_xy_xz_yz/subset[0-7]/*/*.pkl.gz
+filenames_validation:./../../data/cadV2_0.5mm_64x64_xy_xz_yz/subset[8]/*/*.pkl.gz
+data_folder: None ;not used
+
+[network]
+architecture: resnet
+input_size: 64
+depth: 2
+branching_factor: 1
+batch_normalization: False
+batch_normalization_alpha: 0.3
+dropout: 0.25
+spatial_dropout: 0.5
+gaussian_noise: 0.05
+
+[updates] ;Not used
+optimization: adam
+learning_rate: 0.0001
+momentum: 0.99
+l2_lambda: 1e-5
+batch_size_train: 64
+batch_size_validation: 128
+n_epochs: 200
+
+[preprocessing] ;Not used
+random_crop: 0 ;no cropping
+erode_segmentation: 11
+
+[normalization]
+zero_center: True
+mean_pixel: 0.2606236106512
+
+[augmentation] ;Not used
+augment: True
+flip: True
+zoom: 0.08 ;Only if OpenCV2 is available
+rotation: 20
+translation: 3
+
+
+[misc]
+multiprocess_load_augmentation: False
+save_every_n_epoch: 2
+n_workers_load_augmentation: 4

config/wide_resnet.ini

@@ -0,0 +1,51 @@
+[info]
+experiment: Wide Residual Network default settings
+name: resnet
+
+[dataset]
+pixels: 224
+n_classes: 3
+channels: 3
+data_level: 0
+subset: None
+subset_train: 1352 670 832 ;
+subset_validation: 316 135 305 ;
+filenames_train: None ;NOT USED
+filenames_validation: None :NOT USED
+data_folder: /mnt/rdstorage1/Userdata/Guido/BreastDataset
+
+
+[network]
+architecture: resnet
+input_size: 224
+depth: 5
+branching_factor: 4
+batch_normalization: True
+
+[updates]
+optimization: nesterov
+learning_rate: 0 ;Schedule is used instead
+momentum: 0.9 ;Not used yet
+l2_lambda: 0.0001 ;Not used yet
+batch_size_train: 6
+batch_size_validation: 12
+n_epochs: 200
+epoch_samples_train: 600
+epoch_samples_validation: 600
+
+[normalization]
+zero_center: True
+mean_pixel: 0.79704494411170501 0.61885510553571943 0.71202771615037175
+
+[augmentation]
+augment: False ;All augmentation to be implemented
+flip: True
+zoom: 0.08
+rotation: 16
+translation: 3
+
+
+[misc]
+multiprocess_load_augmentation: True
+n_workers_load_augmentation: 6
+save_every_n_epoch: 2

src/deep/dataset_2D.py

@@ -8,15 +8,20 @@
 def load_images (image_paths):
     X = []
 
+    labels = []
+
     for image_path in image_paths:
         with gzip.open(image_path) as file:
-        	X.append(pickle.load(file))
+        	X.append(pickle.load(file)[0])
+
+        label = [0,1] if "True" in image_path else [1,0]
+        labels.append(label)
 
     X = np.array(X)
 
     X = normalize(X)
-    
+
     if P.ZERO_CENTER:
         X -= P.MEAN_PIXEL
 
-    return X
+    return np.array(X, dtype=np.float32), np.array(labels)