Code

An implementation of smile detection using OpenCV, cv_bridge, ROS and Python is available in full at the bottom of this post.

I’ve been developing in ROS for awhile now, and I’ve settled into a pattern for creating nodes that I find works really well for me. It has three components:

1. Create a single class that encapsulates the entirety of what the node is supposed to do
2. All subscriber callbacks are restricted to saving the content of the message to a member variable to hold until ready to be processed
3. Have a run function in the code that is the main ROS loop, and calls the update functions to process data

Functionally, it looks like this:
(I’m using FaceFinder as an example)

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Second Title: Hiding Secret Messages in Cute Pictures of Dogs

I developed this activity to as an interesting way to introduce students taking the foundation level software class at Olin to image manipulation and binary math. Since I spent quite a bit of time working on it, I wanted to publish the entire thing as a blog post in case other people on the web are interested in steganography. This exercise was modified from a similar one found at Interactive Python, though this version encodes an image into another image instead of ASCII text.

Because I wrote this as a learning exercise, there’s a neat little repo that holds starter code and solution code. You can clone/fork it here. The starter code is in steganography.py and has some missing functions for you to fill out, while the full solution is in solution.py. There are two main functions to this code. The first is a decoding function that can extract secret information from an image file, while the second is a function that can encode secret messages into images.

This code uses the Python Pillow library. You can install it using pip if the package is missing from your computer by typing sudo pip install pillow into your terminal window.

If you don’t wanna learn about how to do steganography and just want a neat script that will hide messages in images for you, you can use the code in solution.py. It is also embedded at the end of this post.

What is steganography?
In a nutshell, the main goal of steganography is to hide information within data that doesn’t appear to be secret at a glance. For example, this sentence:

Since everyone can read, encoding text in neutral sentences is definitely effective

turns into

Secret inside

if you take the first letter of every word. Steganography is really handy to use, because people won’t even suspect that they’re looking at a secret message–making it less likely that they’ll want to try to crack your code. In the past, you may have tried to accomplish this kind of subterfuge using invisible inks or using special keywords with your friends. However, as fearless coders we have access to fancier ways to sneak data around. *evil laughter here*
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[*disclaimer: not really 5 mins. Downloading ROS will probably take longer than that lol]

ROS is a really great library for robotics research. It might even be good for not robotic applications, I don’t know, but my general feel is that I like ROS about as much as I like nutella. (read: a lot). The ROS install tutorial is really good at explaining the process, but it’s spread over too many pages and requires too much scrolling. I’ve consolidated the information here in one page for ease of use. Our robotics lab only uses ROS Indigo, so I’m writing install instructions with that in mind. Also, ROS only works well with Ubuntu, so I’m assuming you’re also using the correct OS.

Everything that follows, unless explicitly stated, should be typed in a terminal window. Okay, so the steps:

1. Set up sources.list
We need to add the ROS package sources to our sources list so we can actually find the ROS packages using the apt package manager. Open up a terminal window and paste the following:
sudo sh -c ‘echo “deb http://packages.ros.org/ros/ubuntu $(lsb_release -sc) main” > /etc/apt/sources.list.d/ros-latest.list’

2. Set up your keys
Next we need to set up keys so Ubuntu will actually allow us to download + install the packages.
sudo apt-key adv –keyserver hkp://ha.pool.sks-keyservers.net –recv-key 0xB01FA116
If you get a gpg: keyserver timed out error, use this instead:
sudo apt-key adv –keyserver hkp://ha.pool.sks-keyservers.net:80 –recv-key 0xB01FA116

3. Install ROS via apt-get
Make sure the apt package index is up to date from when we added those new sources at step 1.
sudo apt-get update
Then install ROS!
sudo apt-get install ros-indigo-desktop-full
There are a couple of flavors of ROS that you can install, but for most applications, you might as well do the full install to make sure you get all the packages you’ll ever need.
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I’ve wanted to use speech detection in my personal projects for the longest time, but the Google API has gradually gotten more and more restrictive as time passes. In order to ensure that my projects could work even without an internet connection, I looked for another speech recognition package that would preferably be easier to use. I found the Sphinx voice recognition suite of CMU to be a really great speech to text package. However, documentation and sample code is non-existent, so it took me forever to get anything done. Finally, I’ve figured it out! The example code is at the bottom of this post, but you can directly download it from Github here.

Here are the steps to take to get this working:

1. Download SphinxBase and follow the install instructions
2. Download PocketSphinx and follow the install instructions
3. Download PocketSphinx-python and follow the install instructions
4. Run the code below

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