Around the Hackaday secret bunker, we’ve been talking quite a bit about machine learning and neural networks. There’s been a lot of renewed interest in the topic recently because of the success of TensorFlow. If you are adept at Python and remember your high school algebra, you might enjoy [Oliver Holloway’s] tutorial on getting started with Tensorflow in Python.
[Oliver] gives links on how to do the setup with notes on Python versions. Then he shows some basic setup operations. From there, he has the software “learn” how to classify random points that either fall into a circle or don’t. Granted, this is easy enough to do with traditional programming, so it isn’t a great practical example, but it is illustrative for learning purposes.
Given that it is easy to algorithmically decide which points are in the circle and which are not, it is simple to develop training data. It is also easy to look at the result and see how close it is to the actual circle. You’ll see that it takes a lot of slow learning before the result space looks like a circle and not a triangle or some other odd shape.
Continue reading “Tensorflow Tutorial Uses Python”
What do we curious Hackaday scribes do when we want to learn about something? First port of call: search the web.
When that something is blockchain technology and we’re looking for an explanation that expands our cursory overview into a more fundamental understanding of the basic principles, there is a problem. It seems that to most people blockchains equate to one thing: cryptocurrencies, and since cryptocurrencies mean MONEY, they then descend into a cultish frenzy surrounded by a little cloud of flying dollar signs. Finding [Daniel van Flymen]’s explanation of the fundamentals of a blockchain in terms of the creation of a simple example chain using Python was thus a breath of fresh air, and provided the required education. Even if he does start the piece by assuming that the reader is yet another cryptocurrency wonk.
We start by creating a simple class to hold all the Python functions, then we are shown a single block. In his example it’s a JSON object, and it contains the payload in the form of a transaction record along with the required proof-of-work and hash. We’re then taken through a very simple proof-of-work algorithm, before being shown how the whole can be implemented as very simple endpoints.
You are not going to launch a cryptocurrency using this code, and indeed that wasn’t our purpose in seeking it out. But if you are curious about the mechanics of a blockchain and are equally tired of evangelists of The Blockchain who claim it will cure all ills but can’t explain it in layman’s terms, then this relatively simple example is for you.
The wrong way to build a blockchain image: Jenny List. #FarmLife.
Who wants warm drinks? Well, coffee drinkers, we guess. Other than them, who wants warm drinks? Tea drinkers, sure. How about room temperature drinks? No one, that’s who. It’s silly to buy a refrigerator to cool down a single drink, so what option are you left with? Ice cubes? They’ll dilute your drink. Ice packs and a cooler? Sure, they’ll keep your drinks cold, but they’re hardly cool are they? No, if you want a cold drink the cool way, you build a thermoelectric cooler. And if you want to build one, you’re in luck, because [John Park] has a tutorial to do just that up on AdaFruit.
The parts list includes an AdaFruit Trinket M0, a more powerful version of AdaFruit’s Trinket line. The Trinket is used to control the main part in this build, a Peltier thermoelectric cooler, as well as the temperature display and switches. The other part controlled by the microcontroller is a peristaltic pump, which is used to do the dispensing of the liquid. The code to control everything is written in Python as the Trinket M0 comes with AdaFruit’s CircuitPython by default. Also included in the tutorial are the files for the stand, should you want to 3D print it or cut it with a CNC or laser cutter.
After the break, you can watch as [John] goes over the project and builds it, or go to the AdaFruit website and follow the instructions to build your own. As [John] says, there might be better ways to chill your drinks, but this is “definitely one of the more science-y and interesting ones.” For more projects using the Peltier Effect, try this one that uses the effect in sous-vide cooking, or this one, a Peltier cooled micro-fridge!
Continue reading “Trinket Chills Your Drinks”
For better or worse, pets often serve as inspiration and test subjects for hardware hacks: smarten up that hamster wheel, tweet the squirrel hunting adventures from a dog’s point of view, or automate and remote control a reptile enclosure. [TheYOSH], a gecko breeder from the Netherlands, chose the latter and wrote TerrariumPi for the Raspberry Pi to control and monitor his exotic companion’s home through a convenient web interface.
The right ecosystem is crucial to the health and happiness of any animal that isn’t native to its involuntarily chosen surroundings. Simulating temperature, humidity and lighting of its natural habitat should therefore be the number one priority for any pet owner. The more that simulation process is reliably automated, the less anyone needs to worry.
TerrariumPi supports all the common temperature/humidity sensors and relay boards you will find for the Raspberry Pi out of the box, and can utilize heating and cooling, watering and spraying, as well as lighting based on fixed time intervals or sensor feedback. It even supports location based sunrise and sunset simulation — your critter might just think it never left Madagascar, New Caledonia or Brazil. All the configuration and monitoring happens in the browser, as demonstrated in [TheYOSH]’s live system with public read access (in Dutch).
It only seems natural that Python was the language of choice for a reptile-related system. On the other hand, it doesn’t have to be strictly used for reptiles or even terrariums; TerrariumPi will take care of aquariums and any other type of vivarium equally well. After all, we have seen the Raspberry Pi handling greenhouses and automating mushroom cultivation before.
In July of 2016 a game was released that quickly spread to every corner of the planet. Pokemon Go was an Augmented Reality game that used a smart phone’s GPS location and camera to place virtual creatures into the person’s real location. The game was praised for its creativity and was one of the most popular and profitable apps in 2016. It’s been download over 500 million times since.
Most of its users were probably unaware that they were flirting with a new and upcoming technology called Augmented Reality. A few day ago, [floz] submitted to us a blog from a student who is clearly very aware of what this technology is and what it can do. So aware in fact that they made their own Augmented Reality system with Python and OpenCV.
In the first part of a multi-part series – the student (we don’t know their name) walks you through the basic structure of making a virtual object appear on a real world object through a camera. He 0r she gets into some fairly dense math, so you might want to wait until you have a spare hour or two before digging into this one.
Thanks to [floz] for the tip!
While it is often said that “necessity is the mother of invention”, we can’t say that’s always been our experience here at Hackaday. You won’t need to search too long before you find a project or hack on this site that definitely falls out of the realm of strict necessity. But that’s part of the fun, there’s a reason this site isn’t called AppropriateUseOfTime.com
But when [Sam Storino] couldn’t seem to stop his cats from howling for their supper at 3:00 AM, he had the perfect opportunity to fulfill that age-old wisdom. Not only did he manage to turn a trip to the plumbing isle of his local home improvement store into a very Steampunk-looking automatic cat feeder, but he also found the time to write up an exceptionally detailed series of blog posts on what he learned during the process.
The heart of the machine is everyone’s favorite Linux board, the Raspberry Pi. You might be thinking the Pi is overkill for a simple timer, and you’d be right. Rather than just dump the food out on a set schedule, [Sam] decided to get a little fancy and come up with some Python scripts that will monitor a GMail inbox and activate the feeder hardware when it receives an email with the title “feed cats”. He then uses IFTTT to send the appropriately named email to the GMail account of his cat feeder on a specific schedule. Hey, nobody said necessity was the mother of straightforward invention.
In the final post of the series, [Sam] goes over the hardware side of the device. Copper pipe makes up the frame, which holds a commercial off-the-shelf dry food dispenser. The feeder was designed for manual operation, but by attaching a continuous rotation servo [Sam] can spin it up and dump a pre-measured amount of food via the Pi’s GPIO pins. The addition of some PVC pipe and fittings takes the food and (at least in theory) divides it equally between the two cat bowls below.
If you think [Sam] may have put a bit more thought than was necessary into something as simple as feeding his pets, keep in mind that he’s in exceptionally good company. Paging through the archives, it seems the intersection of felines and hackers is littered with gloriously complex contraptions.
The Ursa Major Space Station SST282 is a dinosaur of a digital reverb. Okay, so maybe 1978 isn’t ancient yet, but it is getting to the point where one has to worry about the possibility of component failure. At least that’s what [Obsoletetechnology] thought when they created a backup of its memory contents.
As can be seen from some of Hackaday’s previous articles, a part does not have to be an older one to fail. However, there is no such thing as being too paranoid when it comes to older parts reaching their lifetime. Especially when there is valuable memory involved. Each bit of PROM memory is locked by a fuse on its location grid to store permanent data. To be able to read this and collect the respective data, a Raspberry Pi 3 PROM reader was created.
The SST282 uses 3 TTL-level 74xx series Schottky PROM memories on board that hold RAM lookup tables. In the case that these failed, all of the subsequent information would be lost since there are no surviving memory dumps online. Fortunately we are interested only in gathering their contents, so the PROM reader schematic is fairly rudimentary. The chip’s address and data buses connect to a Pi’s GPIO header, and the only other thing to note is a 74LS541 TTL level shifter that converts the Pi’s 3.3V output to the PROM’s 5V TTL level.
Continue reading “Blast From the Past with Space Station PROM Reader”