more improvements

m2dsupsdlclass · Feb 24, 2017 · 06640df · 06640df
1 parent 2f0dc81
commit 06640df
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Showing 2 changed files with 5 additions and 5 deletions.
diff --git a/labs/04_conv_nets_2/classif_and_loc.ipynb b/labs/04_conv_nets_2/classif_and_loc.ipynb
@@ -87,6 +87,7 @@
     "import numpy as np\n",
     "import xml.etree.ElementTree as etree\n",
     "import os\n",
+    "import os.path as op\n",
     "\n",
     "# Parse the xml annotation file and retrieve the path to each image,\n",
     "# its size and annotations\n",
@@ -246,8 +247,7 @@
     "            'when both img_size and crop_size are None, all images '\n",
     "            'in image_paths must have the same shapes.')\n",
     "\n",
-    "    batch = preprocess_input(img_batch)\n",
-    "    return model.predict(img_batch)"
+    "    return model.predict(preprocess_input(img_batch))"
    ]
   },
   {
@@ -916,7 +916,7 @@
     "\n",
     "history = model.fit(inputs, y=[out_cls, out_boxes], \n",
     "                    validation_data=(test_inputs, [test_cls, test_boxes]), \n",
-    "                    batch_size=batch_size, nb_epoch=10)"
+    "                    batch_size=batch_size, nb_epoch=10, verbose=2)"
    ]
   },
   {
@@ -986,7 +986,7 @@
     "\n",
     "history = model.fit(x = inputs, y=[out_cls, out_boxes], \n",
     "                    validation_data=(test_inputs, [test_cls, test_boxes]), \n",
-    "                    batch_size=batch_size, nb_epoch=30)\n",
+    "                    batch_size=batch_size, nb_epoch=30, verbose=2)\n",
     "\n",
     "compute_acc(train=True)\n",
     "compute_acc(train=False)"

diff --git a/labs/04_conv_nets_2/solutions/classif_and_loc.py b/labs/04_conv_nets_2/solutions/classif_and_loc.py
@@ -23,7 +23,7 @@ def classif_and_loc(num_classes):
 
 history = model.fit(x = inputs, y=[out_cls, out_boxes], 
                     validation_data=(test_inputs, [test_cls, test_boxes]), 
-                    batch_size=batch_size, nb_epoch=30)
+                    batch_size=batch_size, nb_epoch=30, verbose=2)
 
 compute_acc(train=True)
 compute_acc(train=False)