Merge pull request #1918 from korrawat/g3doc-dir

Update directories in preparing_inputs.md

object_detection/g3doc/preparing_inputs.md

@@ -7,39 +7,52 @@ TFRecords.
 
 ## Generating the PASCAL VOC TFRecord files.
 
-The raw 2012 PASCAL VOC data set can be downloaded
+The raw 2012 PASCAL VOC data set is located
 [here](http://host.robots.ox.ac.uk/pascal/VOC/voc2012/VOCtrainval_11-May-2012.tar).
-Extract the tar file and run the `create_pascal_tf_record` script:
+To download, extract and convert it to TFRecords, run the following commands
+below:
 
 ```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.
+`pascal_val.record` in the `tensorflow/models` directory.
 
 The label map for the PASCAL VOC data set can be found at
-`data/pascal_label_map.pbtxt`.
+`object_detection/data/pascal_label_map.pbtxt`.
 
 ## 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.
+The Oxford-IIIT Pet data set is located on
+[their website](http://www.robots.ox.ac.uk/~vgg/data/pets/).
+To download, extract and convert it to TFRecrods, run the following commands
+below:
 
 ```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.
+`pet_val.record` in the `tensorflow/models` directory.
 
-The label map for the Pet dataset can be found at `data/pet_label_map.pbtxt`.
+The label map for the Pet dataset can be found at
+`object_detection/data/pet_label_map.pbtxt`.

object_detection/g3doc/running_locally.md

@@ -77,5 +77,5 @@ tensorboard --logdir=${PATH_TO_MODEL_DIRECTORY}
 ```
 
 where `${PATH_TO_MODEL_DIRECTORY}` points to the directory that contains the
-train and eval directories. Please note it make take Tensorboard a couple
+train and eval directories. Please note it may take Tensorboard a couple
 minutes to populate with data.