Minor fixes to match git repo.

PiperOrigin-RevId: 192166224

research/object_detection/dataset_tools/create_pascal_tf_record.py

@@ -104,21 +104,22 @@ def dict_to_tf_example(data,
   truncated = []
   poses = []
   difficult_obj = []
-  for obj in data['object']:
-    difficult = bool(int(obj['difficult']))
-    if ignore_difficult_instances and difficult:
-      continue
-
-    difficult_obj.append(int(difficult))
-
-    xmin.append(float(obj['bndbox']['xmin']) / width)
-    ymin.append(float(obj['bndbox']['ymin']) / height)
-    xmax.append(float(obj['bndbox']['xmax']) / width)
-    ymax.append(float(obj['bndbox']['ymax']) / height)
-    classes_text.append(obj['name'].encode('utf8'))
-    classes.append(label_map_dict[obj['name']])
-    truncated.append(int(obj['truncated']))
-    poses.append(obj['pose'].encode('utf8'))
+  if data.has_key('object'):
+    for obj in data['object']:
+      difficult = bool(int(obj['difficult']))
+      if ignore_difficult_instances and difficult:
+        continue
+
+      difficult_obj.append(int(difficult))
+
+      xmin.append(float(obj['bndbox']['xmin']) / width)
+      ymin.append(float(obj['bndbox']['ymin']) / height)
+      xmax.append(float(obj['bndbox']['xmax']) / width)
+      ymax.append(float(obj['bndbox']['ymax']) / height)
+      classes_text.append(obj['name'].encode('utf8'))
+      classes.append(label_map_dict[obj['name']])
+      truncated.append(int(obj['truncated']))
+      poses.append(obj['pose'].encode('utf8'))
 
   example = tf.train.Example(features=tf.train.Features(feature={
       'image/height': dataset_util.int64_feature(height),

research/object_detection/g3doc/evaluation_protocols.md

@@ -31,7 +31,7 @@ while for the Weighted PASCAL VOC metric the final mAP value will be influenced
 Similar to pascal voc 2007 detection metric, but computes the intersection over
 union based on the object masks instead of object boxes.
 
-## Weighted PASCAL VOC detection metric
+## Weighted PASCAL VOC instance segmentation metric
 
 `EvalConfig.metrics_set='weighted_pascal_voc_instance_segmentation_metrics'`