Although the market for hand-drawn portraits largely collapsed following the invention of photography, there’s something magical about watching an artist create a lifelike image using nothing but a pencil, some paper, and their fine motor skills. Watching a machine do the same is a similarly captivating experience, though often the end result is not so great. Trying to fix this deficiency, [Joris Wegner] and [Felix Fisgus] created the Pankraz Piktograph which seems to do a pretty good job at capturing faces. They were inspired by classic picture-drawing automatons, and made a 21st-century version to be used in museums or at events like trade shows.
The operation of the Piktograph is very simple: you stand in front of the machine, look into the camera and take a selfie. If you like what you see, the robot will then begin to draw your portrait on a piece of paper. It does this using two human-like arms which are made from aluminium and driven by two stepper motors. An ordinary ballpoint pen is held in a spring-loaded carrier, which provides just enough pen-to-paper pressure to reliably draw lines without lifting off or scratching the paper. We can’t help but be impressed with the overall look of the machine: with a sleek, powder-coated aluminium case and a stainless steel stand it’s a work of art by itself.
Inside, the Piktograph is powered by a Raspberry Pi 3, which runs a rather sophisticated algorithm to generate a vector image which doesn’t take too long to draw, but still results in a recognizable image of the subject. The makers’ thesis goes into quite some detail to explain the process, which uses Canny edge detection to create an outline drawing, then fills in the empty bits to create bright and dark areas. A certain amount of noise and wigglyness is added to the lines to give it a more “handmade” feel, and the resulting drawing is divided into continuous lines for efficient drawing by the plotter.
Over the years, artists have been creating art depicting weapons of mass destruction, war and human conflict. But the weapons of war, and the theatres of operation are changing in the 21st century. The outcome of many future conflicts will surely depend on digital warriors, huddled over their computer screens, punching on their keyboards and maneuvering joysticks, or using devious methods to infect computers to disable or destroy infrastructure. How does an artist give physical form to an unseen, virtual digital weapon? That is the question which inspired [Mac Pierce] to create his latest Portrait of a Digital Weapon.
[Mac]’s art piece is a physical depiction of a virtual digital weapon, a nation-state cyber attack. When activated, this piece displays the full code of the Stuxnet virus, a worm that partially disabled Iran’s nuclear fuel production facility at Natanz around 2008. Continue reading “Portrait Of A Digital Weapon”→
We’ve all been there — through the magic of the internet, you see someone else’s stunning project and you just have to replicate it. For [Jenny Ma], that project was computer-generated string art, as in the computer figures out the best nail order to replicate a given image, and you lay out the thread yourself.
So, how does it work? Although a few algorithms are out there already, [Jenny] wanted to make her own using Python. Essentially it crops the image into a circle and then lays out evenly-spaced software nails around the circumference. The algorithm starts from a random nail and then determines the best next nail to wrap around by drawing a line from that nail to every other nail and choosing the darkest one based on the darkness of the image underneath that little line. It repeats this one chord at a time, subtracting from the original image until every pixel has been replaced with a thread or lack thereof, and then it spits out an ordered list of nail numbers.
Once the software was ready, [Jenny] made a wood canvas that’s 80 cm (31.5″) in diameter and started laying out the nail hole locations. There wasn’t quite enough room for 300 nails, so instead of starting over, [Jenny] changed the algorithm to use 298 nails and re-ran it.
[Jenny] does a great job of discussing the many variables at play in this hardware representation of software-created art. The most obvious of course is that the more nails used, the higher the resolution would be, but she determined that 300 is the sweet spot — more than that, and the resolution doesn’t really improve. We have to wonder if 360 nails would make things any easier. Check out the build video after the break.
[Jose’s] portrait painter relies on a Cartesian CNC setup, with an X-Y gantry fitted with a retractable brush carrier. The carrier holds four brushes, allowing the device to paint with different sized strokes as per the artistic requirements. An algorithm is used to turn images into a series of brushstrokes, which are then turned into G-code to drive the system. Colors are mixed just like a human painter would, with the brush dipping into a series of paint pots. Using the hue-saturation-brightness (HSB) color system makes this easy.
While it’s much slower than your average printer, the goal here isn’t to create photorealistic images, but to create something with artistic appeal. The artworks painted by the ‘bot have a remarkable likeness to oil paintings by human artists, thanks to using similar techniques. We’re sure [Jose’s] experience as an oil painter helped out here, too.
It’s a standard science trivia question: Who discovered the structure of DNA? With the basic concepts of molecular biology now taught at a fairly detailed level in grade school, and with DNA being so easy to isolate that it makes a good demonstration project for school or home, everyone knows the names of Watson and Crick. But not many people know the story behind one of the greatest scientific achievements of the 20th century, or the name of the scientist without whose data Watson and Crick were working blind: Rosalind Franklin.
Modern 16:9 aspect ratio monitors may be great for watching a widescreen movie on Netflix, but for most PDFs, Word documents, and certain web pages, landscape just won’t do. But if you’re not writing the next great American novel and aren’t willing to commit to portrait mode, don’t — build an auto-rotating monitor to switch your aspect ratio on the fly.
Like many of us, [Bob] finds certain content less than suitable for the cinematic format that’s become the standard for monitors. His fix is simple in concept, but a little challenging to engineer. Using a lazy susan as a giant bearing, [Bob] built a swivel that can be powered by a NEMA 23 stepper and a 3D-printed sector of a ring gear. Due to the narrow clearance between the top and bottom of the lazy susan, [Bob] had to do considerable finagling to get through holes for the mounting hardware located, but in the end the whole thing worked great.
Our only quibble would be welding galvanized pipe for the stand, which always gives us the willies. But we will admit the tube notching turned out great with just a paper template. We doubt it would have been much better if he used an amped-up plasma-powered tubing notcher.
[Brandon’s] recreation uses a Raspi loaded with a Video Looper SD image that cycles through a clip of the aging man image. He fabricated a box to hold a 19″ LCD monitor and mounted an inexpensive IKEA frame to the front. The magic is hidden with window film applied to turn the frame’s glass into a two-way mirror: a technique [Brandon] borrowed from this Halloween Instructable.
For a step-by-step tutorial, you’ll want to head over to [Brandon’s] writeup on MAKE, but stick around for a quick video demonstration after the break and check out another Haunted Mansion hack: the Singing Heads.