small changes

StephanieLarocque · notoraptor · commit 762da4bdd1b5 · 2017-12-14T11:52:45.000-05:00
diff --git a/code/Unet_lasagne_recipes.py b/code/Unet_lasagne_recipes.py
@@ -40,10 +40,9 @@ def build_UNet(n_input_channels=1, BATCH_SIZE=None, num_output_classes=2, pad='s
 
     net['encode_1'] = batch_norm(ConvLayer(l, base_n_filters*16, 3, nonlinearity=nonlinearity, pad=pad, W=HeNormal(gain="relu")))
     net['encode_2'] = batch_norm(ConvLayer(net['encode_1'], base_n_filters*16, 3, nonlinearity=nonlinearity, pad=pad, W=HeNormal(gain="relu")))
-
    	# end-snippet-bottleneck
-	# start-snippet-upsampling
 
+    # start-snippet-upsampling
     net['upscale1'] = batch_norm(Deconv2DLayer(net['encode_2'], base_n_filters*16, 2, 2, crop="valid", nonlinearity=nonlinearity, W=HeNormal(gain="relu")))
     net['concat1'] = ConcatLayer([net['upscale1'], net['contr_4_2']], cropping=(None, None, "center", "center"))
     net['expand_1_1'] = batch_norm(ConvLayer(net['concat1'], base_n_filters*8, 3, nonlinearity=nonlinearity, pad=pad, W=HeNormal(gain="relu")))
diff --git a/code/fcn_2D_segm/train_fcn8.py b/code/fcn_2D_segm/train_fcn8.py
@@ -331,9 +331,9 @@ def train(dataset, learn_step=0.005,
 
 
 def main():
-    parser = argparse.ArgumentParser(description='Unet model training')
+    parser = argparse.ArgumentParser(description='FCN8 model training')
     parser.add_argument('-dataset',
-                        default='camvid',
+                        default='polyps',
                         help='Dataset.')
     parser.add_argument('-learning_rate',
                         default=0.0001,
