diff --git a/examples/classification/convert_from_caffe.py b/examples/classification/convert_from_caffe.py
deleted file mode 100644
index 9f6ddb3926..0000000000
--- a/examples/classification/convert_from_caffe.py
+++ /dev/null
@@ -1,33 +0,0 @@
-from chainer.links import VGG16Layers as VGG16Layers_chainer
-import chainer
-
-from chainercv.links import VGG16Layers as VGG16Layers_cv
-
-
-if __name__ == '__main__':
-    chainer_model = VGG16Layers_chainer()
-    cv_model = VGG16Layers_cv()
-
-    cv_model.conv1_1.copyparams(chainer_model.conv1_1)
-
-    # The pretrained weights are trained to accept BGR images.
-    # Convert weights so that they accept RGB images.
-    cv_model.conv1_1.W.data[:] = cv_model.conv1_1.W.data[:, ::-1]
-
-    cv_model.conv1_2.copyparams(chainer_model.conv1_2)
-    cv_model.conv2_1.copyparams(chainer_model.conv2_1)
-    cv_model.conv2_2.copyparams(chainer_model.conv2_2)
-    cv_model.conv3_1.copyparams(chainer_model.conv3_1)
-    cv_model.conv3_2.copyparams(chainer_model.conv3_2)
-    cv_model.conv3_3.copyparams(chainer_model.conv3_3)
-    cv_model.conv4_1.copyparams(chainer_model.conv4_1)
-    cv_model.conv4_2.copyparams(chainer_model.conv4_2)
-    cv_model.conv4_3.copyparams(chainer_model.conv4_3)
-    cv_model.conv5_1.copyparams(chainer_model.conv5_1)
-    cv_model.conv5_2.copyparams(chainer_model.conv5_2)
-    cv_model.conv5_3.copyparams(chainer_model.conv5_3)
-    cv_model.fc6.copyparams(chainer_model.fc6)
-    cv_model.fc7.copyparams(chainer_model.fc7)
-    cv_model.fc8.copyparams(chainer_model.fc8)
-
-    chainer.serializers.save_npz('vgg_from_caffe.npz', cv_model)
diff --git a/examples/classification/eval_imagenet.py b/examples/classification/eval_imagenet.py
index 8548ac1d38..7ecb81cd1c 100644
--- a/examples/classification/eval_imagenet.py
+++ b/examples/classification/eval_imagenet.py
@@ -5,6 +5,7 @@
 
 import chainer
 import chainer.links as L
+import chainer.functions as F
 from chainer import iterators
 from chainer import training
 from chainer.training import extensions
@@ -12,6 +13,8 @@
 from chainercv.datasets import ImageFolderDataset
 from chainercv.links import VGG16Layers
 
+from chainercv.utils import apply_prediction_to_iterator
+
 
 def main():
     parser = argparse.ArgumentParser(
@@ -26,15 +29,21 @@ def main():
         dataset, args.batchsize, repeat=False, shuffle=False,
         n_processes=4)
 
-    model = L.Classifier(VGG16Layers())
+    model = VGG16Layers()
 
     if args.gpu >= 0:
         chainer.cuda.get_device(args.gpu).use()
         model.to_gpu()
 
-    
-    result = extensions.Evaluator(iterator, model)
-    print result
+    imgs, pred_values, gt_values = apply_prediction_to_iterator(model.predict, iterator)
+    del imgs
+
+    pred_labels, = pred_values
+    gt_labels, = gt_values
+
+    accuracy = F.accuracy(
+        np.array(list(pred_labels)), np.array(list(gt_labels))).data
+    print accuracy
 
 
 if __name__ == '__main__':