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Project Friday 2.2: let’s fly!

A little while ago we started with our second Project Friday; once a month (or so) we’ll lock some colleagues in a room with a couple of beers and a fun project. This project: give a drone a brain and an eye, so we can call itand make it do stuff for us. Why do we do this? Well, because it’s fun. and we learn a lot.

During our first session we mostly discovered how difficult it was to maneuver the drone around inside our office building. This didn’t put us off even a tiny little bit, we love a good challenge!

We’ve spend most of this session on thinking of a way we can use the camera on the bottom of the drone to make it follow a path we’ve laid out for it. If we put it simply: we want to make the drone to be able to follow a line on the floor. The first thing we did was create a line made out of white adhesive tape on our dark carpet. After that we held the drone above this line to take pictures. And then the thinking started… We had to make sure we took every possible deviation into account and thought of the best way to correct the drone if that deviation occured. Believe it or not, but this drawing helped us do that.

deviationsWhile thinking of every possible deviation and the correction that had to be applied for that deviation, we immediately programmed it into our Python script for the drone. As soon as this script was done, it was time for our first test flight. Which you can see in this video:

Ok… Not succesful yet. Enough work left for some more friday afternoons. As far as we’re concerned: bring it on!

 

Read more about what we did before

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Project Friday 2.1: let’s fly!

After all the fun we had, while also learning a lot, during our first Project Friday “Artificial Intelligence meets Coffee” project We felt it was time for a second project. So this time, instead of giving an eye and a brain to a coffeemachine, why not try to do the same to a drone?! What if we could make a drone come fly up to us when we call for it and tell it what to do after it recognizes who we are…

Our second Project Friday was born!

You might wonder what Project Friday actually is… Well, that’s an easy one; once a month(or so) we’ll lock some colleagues in a room with a couple of beers and a fun project. Why do we do this? Well, because it’s fun and we also learn a lot.

To get started with this Project Friday, we first needed a drone! We chose for the Parrot AR 2.0 Drone, because you can easily connect this drone to your computer to take over the command.

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Most of this first afternoon was spend on trying to fly the drone inside. Which, we found out the hard way, isn’t so easy! A few walls were hit and we did see some people running for their lives, but in the end of the day everbody, including the drone, survived. All is good!

We even managed do give a few commands to the drone from the computer. Although the effect of the commands weren’t as succesful as we had hoped…

 

What we’ve learned so far:

  • flying a drone inside is difficult,
  • connecting to the drone from the computer is easy,
  • giving the right commands isn’t easy at all,
  • we love being pilots!

DroneFun

 

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“We crunch(ed) Artificial Intelligence” Meetup

On December 13 we had our very first The Analytics Lab Meetup at our Headquarters in Amersfoort. Despite the traffic jams around Amersfoort and a broken train that blocked the track between Utrecht and Amersfoort we could welcome around thirty people on this cold Wednesday. Unfortunately one of our expected speakers, Thomas Stalman from welkrestaurant.nl wasn’t one of them, the broken train made it impossible for him to get to Amersfoort on time. But on the bright side, this means we already have an amazing speaker planned for our next meetup!

After some simple but nice dinner, our other three speakers made grateful use of the space that Thomas left for them and brought their story full of enthusiasm to the bedazzled attendees of the meetup. Our first speaker was Klaas Tjepkema who told us about the Advanced Data Sampler and about the plans he has to evolve this. A story about dreaming big and starting small, a perfect example of putting AI to practice. Our second speakers were Joost van der Leegte and Willem van der Geest who told us about their Project Friday Project: AI and Coffee. This project is part of our The Analytics Lab Playground, where we can play around, have fun and learn a lot of new skills! In their presentation Joost and Willem told us more about the coffee machine that was extended with facial recognition. We even got a live demonstration of this coffee machine.

All in all it was a really interesting and fun evening, which gave a nice opportunity to learn more about artificial intelligence in general and data sampling and facial recognition more particular.

Thanks to everybody who was there at our very first meetup, we definitely enjoyed it and hope you did as well!

If you want to know more, or you want to be informed about our next meetup, please sign up at meetup.com and join our The Analytics Lab group. We’d love to see you there!

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Does your coffee machine know who you are? Ours does!

When we tell  our friends or family we were adding face recognition to a coffee machine, often the first question was ‘Why?’. A valid question, which is actually quite easy to answer: because we want to know whether we can, it’s fun and it’s another, just not your ordinary, reason to drink some beers on a Friday afternoon. This project is part of an ongoing idea, which we call Project Friday: doing stuff we’re excited about, which don’t necessary generate revenue. When we answer our friends and family that we do this just for fun, you can deduct from their facial expressions that the words ‘Nerd-Alert’ are going through their minds. The question that often follows is ‘does it actually work?’, well check out this video.

Credits video: Jan Persoon

So, how does it work. We placed a small camera on top of the coffee machine, which captures everything and sends the images to a small computer (a Raspberry PI). An algorithm looks real-time at these images and tries to detect faces. Once it has detected a face, it tries to recognize the face by comparing it with photos of colleagues. After recognizing the face, the computer can determine the favorite drink by using a database filled with these preferences. It then sends a signal to an Arduino board which we’ve soldered to the motherboard of the coffee machine. When the signal is sent, the coffee machine knows whether to brew coffee, espresso or cappuccino for example. When you want to differ from your preferences, you can just say “Stop”; the computer also has a microphone attached, which is able to recognize some basic commands. And we’ve even made the time you have to wair for your coffee a bit more fun, by making sure the computer plays a part of a song that you like.

Still not convinced? Just drop by (but send a photo beforehand)! You can reach us at info@theanalyticslab.nl

The code is on Github, check it out if you’re interested.

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Read more about what happened before during our friday afternoons we were working on this cool project!

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Project Friday 1.3: Artificial Intelligence meets coffee

Last Friday the third afternoon of Project Friday took place. In Project Friday we spent about once a month  an afternoon on something completely useless. Why do we do this? Because we can, it’s fun and interesting and it’s a good reason to grab a couple of beers. This Project Friday is all about mixing Espresso Machines with Artificial Intelligence: adding facial recognition to the machine so that you don’t need to push the button to get your favorite coffee.

In the previous afternoons (day 1 and day 2), we’ve installed everything on the Raspberry PI (which was quite a hassle), learned what relays were and how to use them, soldered the first buttons and were able to control these buttons via the computer. This Friday we set ourselves the goal to real time face detection on the PI cam.

As the weather was warm and sunny, we decided it was better to leave the office and reach our goal in a more suitable environment, somewhere we the Raspberry PI (and us) wouldn’t overheat. So we drove to my place and settled ourselves in the garden, brought a television outside, hooked up the Raspberry PI and off coding we went. An additional benefit was the BBQ!

Astonishingly enough, not only the Raspberry PI had trouble with the warm weather, so did your cognitive capabilities. The move didn’t make us more productive (but was still the right choice with this kind of weather). So progress was slow, and we were on half the strength as three team members were on holiday. We did had some success, we did manage to implement the pre-trained HAAR-cascades for detecting faces and our trained cascade for detecting your middle finger when you flip it. But didn’t get so far to get default face recognition in place. So we’ll leave that for the next afternoon!

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Read more about what happened before or read more about what happened next

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Project Friday 1.1: Artificial Intelligence meets coffee

This Friday we started with our first ‘Project Friday’. About once a month, on a Friday, we’ll lock ourselves away for the afternoon with a couple of beers and a fun project. The project doesn’t need to bring money to table, it needs to bring fun, challenges, knowledge and inspiration to the table.

Our first project is definitely an awesome one; Artificial Intelligence meets Coffee! Douwe Egberts was kind enough to provide us with a full automatic coffee machine, well almost full automatic, you still need to push the button to let the machine know whether you want a normal coffee, a cappuccino, an espresso or whatever grinds your gears. Our objective: create an actual full automatic coffee machine. The goal is to add face recognition to the coffee machine: Stand in front of the machine, the machine recognizes who you are and knows which coffee you want.

We started by prepping a Raspberry Pi and installing OpenCV. Dismantling the machine and figuring out how circuit board works using the well proven method of trial and error. Since we’re not engineers, the biggest challenge is probably going to be to hack the coffee machine: within 15 minutes, one colleague managed to short circuit the Arduino board. Great start!

 

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