Merge pull request #7 from google/update_readme

Update README.rst

- Explicitly install nazoru-input from PyPi.
- Remove unnecessary indents
- Use apt install for necessary packages (tested on a fresh Debian 9 image on GCE).
- Other misc updates

mozc-nazoru/README.rst

@@ -12,15 +12,31 @@ character.
 Software Usage
 --------------
 
-Input Characters
+Install and Try
 ~~~~~~~~~~~~~~~~
 
+Please make sure your local environemnt has packages as follows.
+
+For Ubuntu/Debian:
+
 .. code:: shell
 
-     $ pip install .
+  $ sudo apt install libffi-dev libcairo2 # For Ubuntu/Debian
+
+For macOS:
+
+.. code:: shell
+
+  $ brew install cairo  # For macOS
+
+After that, you can try nazoru-input after installing it from pip.
+
+.. code:: shell
+
+   $ pip install nazoru-input
    $ nazoru-input
 
-By running the commands above, you can make your own machine into an
+Using ``nazoru-input``, You can make your own machine into an
 input device which accepts scribbles on the connected keyboard and send
 characters via bluetooth. At the beginning, this script scans
 connected keyboards and starts listening to inputs from one of the
@@ -28,10 +44,14 @@ keyboards. Then it translates a sequence of keydowns into a predicted
 character considering pressed timings, and send the character to the
 target device paired by bluetooth.
 
-If you want to try it for development, you can use ``-e`` option.
+If you want to try it for development, you can download the source from
+github and use ``-e`` option.
 
 .. code:: shell
 
+   $ sudo apt install libffi-dev libcairo2 # For Ubuntu/Debian
+   $ git clone https://github.com/google/mozc-devices.git
+   $ cd mozc-devices/mozc-nazoru
    $ pip install -e .
    $ nazoru-input
 
@@ -40,8 +60,8 @@ Training Model
 
 .. code:: shell
 
-     $ pip install .
-     $ nazoru-training ./data/strokes.zip
+   $ curl -LO https://github.com/google/mozc-devices/raw/master/mozc-nazoru/data/strokes.zip
+   $ nazoru-training ./strokes.zip
 
 We have a script to generate a trained model which recognizes input
 characters from scribbles. This script renders input stroke data into
@@ -51,7 +71,7 @@ neural network model and the optimizer tunes the model to fit the data.
 Once the training is done, the script outputs the trained graph, which
 you can use for your own device. In the case where you install
 ``nazoru-training`` from pip, you can find ``strokes.zip`` at here:
-https://github.com/google/mozc-devices/mozc-nazoru/data/strokes.zip
+https://github.com/google/mozc-devices/blob/master/mozc-nazoru/data/strokes.zip
 
 You can change some configurations by passing command line flags (e.g.
 path to the input/output files, hyper-parameters). Run
@@ -138,7 +158,8 @@ Raspberry Pi Setup
   $ sudo pip install http://ci.tensorflow.org/view/Nightly/job/nightly-pi-zero/219/artifact/output-artifacts/tensorflow-1.6.0-cp27-none-any.whl
   $ git clone https://github.com/google/mozc-devices
   $ cd mozc-devices/mozc-nazoru
-    $ sudo pip install . # If you want to develop nazoru-input, please use 'pip install -e .' instead.
+  $ vi setup.py  # Remove '#' for data_files to install nazoru.service.
+  $ sudo pip install . # If you want to develop nazoru-input, please use 'sudo pip install -e .' instead.
 
 **Step 4 - Enjoy!**
 
@@ -233,11 +254,9 @@ Authors
 -------
 
 Machine Learning:
-
 Shuhei Iitsuka <tushuhei@google.com>
 
 Hardwares, system setups:
-
 Makoto Shimazu <shimazu@google.com>
 
 License

mozc-nazoru/setup.py

@@ -24,7 +24,7 @@ def read_file(name):
 
 setup(
     name='nazoru-input',
-    version='0.1.1',
+    version='0.1.2',
     author='Makoto Shimazu',
     author_email='shimazu@google.com',
     url='https://landing.google.com/tegaki',