Art

456 Articles

Art Generated From The Dubious Comments Section

July 30, 2020 by 5 Comments

[8BitsAndAByte] are back, and this time they’re taking on the comments section with art. They wondered whether or not they can take something as dubious as the comments section and redeem it into something more appealing like art.

They started by using remo.tv, a tool they’ve used in other projects, to read comments from their video live feeds and extract random phrases. The phrases are then analyzed by text to speech, and a publicly available artificial intelligence algorithm that generates an image from a text description. They can then specify art styles like modern, abstract, cubism, etc to give their image a unique appeal. They then send the image back to the original commenter, crediting them for their comment, ensuring some level of transparency.

We were a bit surprised that the phrase dog with a funny hat generated an image of a cat, so I think it’s fair to say that their AI engine could use a bit of work. But really, we could probably say that about AI as a whole.

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Filmmaking From Home With Projection Mapping

July 6, 2020 by 10 Comments

Stuck at home in self-quarantine, artist and filmmaker [Kira Bursky] had fewer options than normal for her latest film project. While a normal weekend film sprint would have involved collaborating with actors, set designers, and cinematographers in a frenzied attempt to finish in less than 48 hours, she instead chose to indulge in her curiosity for projection mapping, a technique that involves projecting visuals onto three-dimensional or flat surfaces.

In order for the images to properly map onto a surface, the surface first has to be mapped so that the projection is able to properly transform the flat image in order to produce the illusion of the light wrapping around the object. The technique is done in layers, in software similar to Photoshop, making it easier for the designer to organize the different interacting components in their animation.

[Kira] used a tool called Lightform to design her projections, which relies on a camera to calibrate the location of the surface and a projector to display the visuals. Her animated figures are drawn with loose lines and characterized by their slow gradients and ethereal movements. In the background of her film, a rhythmic sound plays while she brings the figures closer to view. Their outlines come into greater focus until the figures transform into her physical body, which also dances with the meandering lights.

Check out the short film below.

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Elegant Shoji Lamps From Your 3D Printer

July 6, 2020 by 12 Comments

The gorgeous Shoji-style lamps you’re seeing here aren’t made of wood or paper. Beyond the LEDs illuminating them from within, the lamps are completely 3D printed. There aren’t any fasteners or glue holding them together either, as creator [Dheera Venkatraman] used authentic Japanese wood joinery techniques to make their components fit together like a puzzle.

While we’re usually more taken with the electronic components of the projects that get sent our way, we have to admit that in this case, the enclosure is really the star of the show. [Dheera] has included a versatile mounting point where you could put anything from a cheap LED candle to a few WS2812B modules, but otherwise leaves the integration of electronic components as an exercise for the reader.

All of the components were designed in OpenSCAD, which means it should be relatively easy to add your own designs to the list of included panel types. Despite the colorful details, you won’t need a multi-material printer to run them off either. Everything you see here was printed on a Prusa i3 MK3S in PETG. Filament swaps and careful design were used to achieve the multiple colors visible on some of the more intricate panels.

If the timeless style of these Japanese lanterns has caught your eye, you’ll love this beautiful sunrise clock we covered last year.

Recreating Paintings By Teaching An AI To Paint

June 27, 2020 by 9 Comments

The Timecraft project by [Amy Zhao] and team members uses machine learning to figure out a way how an existing painting may have been originally been painted, stroke by stroke. In their paper titled ‘Painting Many Pasts: Synthesizing Time Lapse Videos of Paintings’, they describe how they trained a ML algorithm using existing time lapse videos of new paintings being created, allowing it to probabilistically generate the steps needed to recreate an already finished painting.

The probabilistic model is implemented using a convolutional neural network (CNN), with as output a time lapse video, spanning many minutes. In the paper they reference how they were inspired by artistic style transfer, where neural networks are used to generate works of art in a specific artist’s style, or to create mix-ups of different artists.

A lot of the complexity comes from the large variety of techniques and materials that are used in the creation of a painting, such as the exact brush used, the type of paint. Some existing approaches have focused on the the fine details here, including physics-based simulation of the paints and brush strokes. These come with significant caveats that Timecraft tried to avoid by going for a more high-level approach.

The time lapse videos that were generated during the experiment were evaluated through a survey performed via Amazon Mechanical Turk, with the 158 people who participated asked to compare the realism of the Timecraft videos versus that of the real time lapse videos. The results were that participants preferred the real videos, but would confuse the Timecraft videos for the real time lapse videos half the time.

Although perhaps not perfect yet, it does show how ML can be used to deduce how a work of art was constructed, and figure out the individual steps with some degree of accuracy.

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3D-Printed Tools Make Circuit Sculpture A Little Easier

June 24, 2020 by 7 Comments

Having the tools needed to do a job is a powerful thing. Having the tools needed to make more tools for doing cool things is even better, though, and that’s where [Jiří Praus] took things with this 3D-printed jig for making his blooming tulip circuit sculpture.

If you haven’t seen [Jiří]’s tulip, check out our coverage from back when he first built it. The brass wire and tube mechanism and some clever linkages let a single servo open the Neopixel-adorned petals at a touch. But what started as a one-off romantic gesture for his wife on Valentine’s Day became something more, and what was a labor of love turned into just labor very quickly. [Jiří]’s solution, explained in the brief video below, is a 3D-printed jig that holds all the wires that form the tulip petals locked into position. The wire that defines the spine of the petal goes into a groove and gets held down with removable clips. The edge wires are held by rotating clips, and the veins of the petals just lay in place in grooves. The area around each joint is hollowed out so [Jiří] can solder easily without melting the plastic jig.

The best part comes at the end, when it’s time to release the completed petal. For that, a tool with pins that looks a little like a hedgehog is inserted from below, and pins that fit into each joint’s hole pop the finished petal off. We can see how this tool would greatly increase the production of his tulips, so if that’s his goal, he’s on track.

If you’re into circuit sculpture, you’re in the right place. Check out [Mohit Bhoite]’s Supercon talk on the subject, or some more of the tools [Jiří] has come up with to improve his art.

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Plot And Visualise Brain Data In An Artwork

June 15, 2020 by 1 Comment

One of the most interesting streams through which we receive new projects to write about here at Hackaday comes from the intersection between technologists and artists. Those artists who straddle both disciplines bring creativity that those of us without their backgrounds can only dream of. The artist [Rosa Francesca] produced a piece called Cinematica, in which she monitored her brain waves with an EEG and from them produced on-paper visualizations with a pen plotter.

The hardware in use is an Interaxon Muse EEG headband read through the Muse Monitor app, and some code to drive an Evil Mad Scientist AxiDraw V3 plotter via its serial port. The write-up goes in some depth into the different types of brain waves, explaining her choice of monitoring gamma and theta waves for her source data. The result is a series of repeating shapes that vary with the brain waves of the wearer, creating drawings that are both pleasing and unique.

If you’re interested by the Muse headset used in this artwork, you might find a teardown we covered a few years ago to be of interest. And if you’re tempted by the plotter, you can always try making your own.

Thanks, @tanurai for the tip!