CNC machines are an essential part of the hacker’s toolset. These computer-controlled cutters of wood, metal and other materials can translate a design into a prototype in short order, making the process of iterating a project much easier. However, the software to create these designs can be expensive, so [Franklin Wei] decided to write his own. In particular, he decided to write his own program to engrave images, converting a photo into a toolpath that can be cut. The result is RasterCarve, a web app that converts an image into a GCode that can be fed into a CNC machine.
A canceled project left [Craig] with six Raspberry Pi based devices he calls “Minions”. A minion is a Raspberry Pi model A in a small enclosure with an Adafruit 2.2″ 320×240 SPI LCD. The LCD lives in a lollipop style circular housing above the base. [Craig] has found a use for one of his minions as a desktop raytracer.
The Raspberry Pi is quite capable of running Persistance Of Vision Raytracer, or POV-Ray. POV-Ray started life as an early PC based raytracer. Created as a port of an Amiga program called DKBTrace, which was itself a port of a Unix raytracer, POV-Ray first was released in 1987. For the uninitiated, raytracers like POV-Ray literally trace rays from a light source to an image plane. As one would imagine, the Raspberry Pi’s little ARM processor would take quite a bit of time to raytrace a high resolution image. However, when targeting a 320×240 LCD, it’s not half bad.
[Craig’s] minion is running his own software which he calls ArtRays. Based upon a setup file, ArtRays can render images from several sources, including the internet via a WiFi dongle, or a local SD card. Rather than walk through the setup and software install, [Craig] has provided a link to download a full SD card image to build your own Minion. It might be worth experimenting on your own first though, rather than killing his server with a 1GB download.
We’re glad [Craig] has found use for one of his minions, now we have to see what he’s done with the other five!
Here’s a hack with more of a survivalist flair to it. [Ligament] and some friends used the fat from butchering a deer to make soap, candles, and toiletries.
It’s hunting season and [Ligament’s] dad is processing the deer which he harvested. Wild game doesn’t have the amount of fat you’d find on a domesticated animal, but there is still a fair amount. The group cut off as much as they could before cutting up the rest of the meat. The trimmings are put in a pot with water and boiled until the fat starts to rise. It is ladled off and strained through some cheese cloth. The fat hardens overnight and can be picked up out of the container as a big disk. It is reheated and strained through a mesh coffee filter to achieve the final product. From there the fat was used as an ingredient in the recipes for candles, soap, and things like lip balm. For details on that heck out the comments for each image in the gallery linked above.
It’s a good thing to waste as little as possible. But this skill will be indispensable once the Zombie Apocalypse comes. You might also want to know how to chlorinate your own water.
Look at it. Just look at it! This board is a lie. It doesn’t exist (at least not what’s seen in the image here). Instead this is a lifelike rendering made from Eagle CAD files.
We’ve already seen that it is rather easy to pull Eagle CAD files into Google SketchUp thanks to the EagleUp package. You’ll get a 3D model that looks quite nice but it’s hardly photo-realistic. This process starts exactly the same way. But you’re going to want to process the SketchUp file one more time.
A program called Kerkythea does this for you. It’s an open source project aimed at producing realistic renderings. It has a plugin which will process any SketchUp model and apply the textures and shadings that look so wonderful in the image above. It’s not a one-click process, but reminds us of the mountain of options you’d find in a program like Blender3D. You’ll need to map out settings for each different material you’d like to map, but the guides found at the link above do a good job of showing how it’s done.
[Oliver Kreylos] is using an Xbox Kinect to render 3D environments from real-time video. In other words, he takes the video feed from the Kinect and runs it through some C++ software he wrote to index the pixels in a 3D space that can be manipulated as it plays back. The image above is the result of the Kinect recording video by looking at [Oliver] from his right side. He’s moved the viewer’s playback perspective to be above and in front of him. Part of his body is missing and there is a black shadow because the camera cannot see these areas from its perspective. This is very similar to the real-time 3D scanning we’ve seen in the past, but the hardware and software combination make this a snap to reproduce. Get the source code from his page linked at the top and don’t miss his demo video after the break.
The Blender Foundation has just received a new render farm. It came in the form of a four-drawer file cabinet something akin to the popular Ikea clusters. Each draw holds four motherboards, power supplies, and hard drives and the whole cabinet will eventually add up to a 16-node cluster. Join in on the geeky excitement by watching the delivery and unpacking video after the break. We love it when organizations share the details on the hardware they use. Continue reading “Rendering And Blendering In A File Cabinet”
Building a render cluster doesn’t mean you have to spend a lot of money, even if you’re buying brand new hardware. [Janne] built this 6 unit cluster inside of a 6 drawer IKEA Helmer cabinet. He wanted the cluster to be low power and low cost. After finding a good price on 6 65nm Intel Core 2 CPUs, he found 6 cheap Gigabyte motherboards. The memory on each board was maxed at 8GB. With 24 2.4GHz cores consuming 400W, the power consumption and cost isn’t much more than a high end PC. Each board is running Fedora 8 and mounts an NFS share. Dr Queue is used to manage the render farm’s processes. [Janne] says jobs that previously took all night now only require about 10-12 minutes. The estimated capacity is 186Gflops, but plans are already in motion for a12Tflop version.
[UPDATE: yep, we duped ourselves]