Update create_pascal_tf_record.py

when creat a tf record using purely negative images which have no 'object' in their xmls ,the script gets a key error : for obj in data['object']:  Key Error : 'object'
In order to fix this , add a 'if ' judegement before it .

research/object_detection/dataset_tools/create_pascal_tf_record.py

@@ -104,21 +104,23 @@ 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),