improve eval_imagenet

chainer · Jun 14, 2017 · 33f46db · 33f46db
1 parent 2d4c45e
commit 33f46db
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Showing 2 changed files with 13 additions and 37 deletions.
diff --git a/examples/classification/convert_from_caffe.py b/examples/classification/convert_from_caffe.py
diff --git a/examples/classification/eval_imagenet.py b/examples/classification/eval_imagenet.py
@@ -5,13 +5,16 @@
 
 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
 
 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__':