Update directories in preparing_inputs.md

object_detection/g3doc/preparing_inputs.md

@@ -8,38 +8,45 @@ TFRecords.
 ## Generating the PASCAL VOC TFRecord files.
 
 The raw 2012 PASCAL VOC data set can be downloaded
-[here](http://host.robots.ox.ac.uk/pascal/VOC/voc2012/VOCtrainval_11-May-2012.tar).
+[here](http://host.robots.ox.ac.uk/pascal/VOC/voc2012/VOCtrainval_11-May-2012.tar),
+or by using the command below.
 Extract the tar file and run the `create_pascal_tf_record` script:
 
 ```bash
-# From tensorflow/models/object_detection
+# From tensorflow/models
+wget http://host.robots.ox.ac.uk/pascal/VOC/voc2012/VOCtrainval_11-May-2012.tar
 tar -xvf VOCtrainval_11-May-2012.tar
-python create_pascal_tf_record.py --data_dir=VOCdevkit \
-    --year=VOC2012 --set=train --output_path=pascal_train.record
-python create_pascal_tf_record.py --data_dir=VOCdevkit \
-    --year=VOC2012 --set=val --output_path=pascal_val.record
+python object_detection/create_pascal_tf_record.py \
+    --label_map_path=object_detection/data/pascal_label_map.pbtxt \
+    --data_dir=VOCdevkit --year=VOC2012 --set=train \
+    --output_path=pascal_train.record
+python object_detection/create_pascal_tf_record.py \
+    --label_map_path=object_detection/data/pascal_label_map.pbtxt \
+    --data_dir=VOCdevkit --year=VOC2012 --set=val \
+    --output_path=pascal_val.record
 ```
 
 You should end up with two TFRecord files named `pascal_train.record` and
-`pascal_val.record` in the `tensorflow/models/object_detection` directory.
-
-The label map for the PASCAL VOC data set can be found at
-`data/pascal_label_map.pbtxt`.
+`pascal_val.record` in the `tensorflow/models` directory.
 
 ## Generating the Oxford-IIIT Pet TFRecord files.
 
 The Oxford-IIIT Pet data set can be downloaded from
-[their website](http://www.robots.ox.ac.uk/~vgg/data/pets/). Extract the tar
-file and run the `create_pet_tf_record` script to generate TFRecords.
+[their website](http://www.robots.ox.ac.uk/~vgg/data/pets/), or by using the
+command below. Extract the tar file and run the `create_pet_tf_record` script
+to generate TFRecords.
 
 ```bash
-# From tensorflow/models/object_detection
+# From tensorflow/models
+wget http://www.robots.ox.ac.uk/~vgg/data/pets/data/images.tar.gz
+wget http://www.robots.ox.ac.uk/~vgg/data/pets/data/annotations.tar.gz
 tar -xvf annotations.tar.gz
 tar -xvf images.tar.gz
-python create_pet_tf_record.py --data_dir=`pwd` --output_dir=`pwd`
+python object_detection/create_pet_tf_record.py \
+    --label_map_path=object_detection/data/pet_label_map.pbtxt \
+    --data_dir=`pwd` \
+    --output_dir=`pwd`
 ```
 
 You should end up with two TFRecord files named `pet_train.record` and
-`pet_val.record` in the `tensorflow/models/object_detection` directory.
-
-The label map for the Pet dataset can be found at `data/pet_label_map.pbtxt`.
+`pet_val.record` in the `tensorflow/models` directory.