[Geyes30]’s Raspberry Pi project does one thing: it finds arbitrary text in the camera’s view and reads it out loud. Does it do so flawlessly? Not really. Was it at least effortless to put together? Also no, but it does wonderfully illustrate the process of gluing together different bits of functionality to make something new. Also, [geyes30]’s kids find it fascinating, and that’s a win all on its own.
The device is made from a Raspberry Pi and camera and works by sending a still image from the camera to an optical character recognition (OCR) program, which converts any visible text in the image to its ASCII representation. The recognized text is then piped to the espeak engine and spoken aloud. Getting all the tools to play nicely took a bit of work, but [geyes30] documented everything so well that even a novice should be able to get the project up and running in an afternoon.
Sometimes a function like text-to-speech is an end result in and of itself. This was also true of another similar project: Magic Mirror, whose purpose was to tirelessly indulge children’s curiosity about language.
Seeing other projects come to life and learning about new tools is a great way to get new ideas, and documenting them helps cross-pollinate among creative types. Did something inspire you recently, or have you documented your own project? We want to hear about it and so do others, so let us know via the tips line!
Continue reading “Raspberry Pi Reads What It Sees, Delights Children” →
It’s getting easier and easier to add machine intelligence to your hacks, even to the point where you sometimes don’t have to install any special software. In this case [Dexter Industries] has added the ability to read human emotions to their EmpathyBot robot by making use of Google Cloud Vision.
Press a button on the robot and it moves forward until it’s a certain distance from an object. It then takes a picture and sends it off to Google Cloud Vision along with a request to do face detection. The response that Google returns is in JSON format and, if it finds a face, includes the likelihood of the face being happy, sad, sorrowful or surprised. The robot parses that response and gives an appropriate canned speech using the text-to-speech software, eSpeak e.g. “You seem happy! Tell me why you are so happy!”.
[Dexter] has made the source code available on github. It’s written in python and is easy to read by anyone with even just a little programming experience. The video after the break gives a number of demonstrations, including some with non-human subjects.
Continue reading “Raspberry Pi Robot That Reads Your Emotions” →
[POTUSCamacho] listens to his @public_timeline rss feed. In part one of his project, he describes creating a bash script in which he uses cURL get his private feed, sed to clean it and eSpeak to output a WAV file. In parts two and three, he goes on to discuss how he created an audio stream (currently down, opens in a new window) of @public_timeline and how he plans on tweeting vocally.