computer vision

117 Articles

Fish Drives Tank

March 1, 2026 by 12 Comments

Fish are popular animals to keep as pets, and for good reason. They’re relatively low maintenance, relaxing to watch, and have a high aesthetic appeal. But for all their upsides, they aren’t quite as companionable as a dog or a cat. Although some fish can do limited walking or flying, these aren’t generally kept as pets and would still need considerable help navigating the terrestrial world. To that end, [Everything is Hacked] built a fish tank that allows his fish to move around on their own. We presume he’s heard the old joke about two fish in a tank. One says, “Do you know how to drive this thing?”

The first prototype of this “fish tank” is actually built on a tracked vehicle with differential steering, on which the fish tank would sit. But after building a basic, driveable machine, the realities of fish ownership set in. The fish with the smallest tank needs is a betta fish, but even that sort of fish needs much more space than would easily fit on a robotics platform. So [Everything is Hacked] set up a complete ecosystem for his new pet, making the passenger vehicle a secondary tank.

The new fish’s name is [Carrot], named after the carrots that [Everything is Hacked] used to test the computer vision system that would track the fish’s movements and use them to control the mobile fish tank. There was some configuration needed to ensure that when this feisty fish swam in circles, the tank didn’t spin around uncontrollably, but eventually he was able to get it working in an “arena” where [Carrot] could drive towards some favorite items he might like to interact with. Mostly, though, he drove his tank to investigate the other fish in the area.

The ultimate goal was for [Everything is Hacked] to take his fish on a walk, though, so he set about training [Carrot] to respond to visual cues and swim towards them. In theory, this would have allowed him to be followed by his fish tank, but a test at a local grocery did not go as smoothly as hoped. Still, it’s an interesting project that pushes the boundaries of pet ownership much like other fish-driving projects we’ve seen.

Continue reading “Fish Drives Tank” →

A grey and blue coreXY 3D printer is shown, with a small camera in place of its hotend. On the print bed is a ChArUco pattern, a grid of square tiles containing alternating black fill and printed patterns.

Calibrating A Printer With Computer Vision And Precise Timing

December 22, 2025 by 17 Comments

[Dennis] of [Made by Dennis] has been building a Voron 0 for fun and education, and since this apparently wasn’t enough of a challenge, decided to add a number of scratch-built improvements and modifications along the way. In his latest video on the journey, he rigorously calibrated the printer’s motion system, including translation distances, the perpendicularity of the axes, and the bed’s position. The goal was to get better than 100-micrometer precision over a 100 mm range, and reaching this required detours into computer vision, clock synchronization, and linear algebra.

To correct for non-perpendicular or distorted axes, [Dennis] calculated a position correction matrix using a camera mounted to the toolhead and a ChArUco board on the print bed. Image recognition software can easily detect the corners of the ChArUco board tiles and identify their positions, and if the camera’s focal length is known, some simple trigonometry gives the camera’s position. By taking pictures at many different points, [Dennis] could calculate a correction matrix which maps the printhead’s reported position to its actual position.

Continue reading “Calibrating A Printer With Computer Vision And Precise Timing” →

A Bird Watching Assistant

November 25, 2025 by 21 Comments

When AI is being touted as the latest tool to replace writers, filmmakers, and other creative talent it can be a bit depressing staring down the barrel of a future dystopia — especially since most LLMs just parrot their training data and aren’t actually creative. But AI can have some legitimate strengths when it’s taken under wing as an assistant rather than an outright replacement.

For example [Aarav] is happy as a lark when birdwatching, but the birds aren’t always around and it can sometimes be a bit of a wild goose chase waiting hours for them to show up. To help him with that he built this machine learning tool to help alert him to the presence of birds.

The small device is based on a Raspberry Pi 5 with an AI hat nested on top, and uses a wide-angle camera to keep an eagle-eyed lookout of a space like a garden or forest. It runs a few scripts in Python leveraging the OpenCV library, which is a widely available machine learning tool that allows users to easily interact with image recognition. When perched to view an outdoor area, it sends out an email notification to the user’s phone when it detects bird activity so that they can join the action swiftly if they happen to be doing other things at the time. The system also logs hourly bird-counts and creates a daily graph, helping users identify peak bird-watching times.

Right now the system can only detect the presence of birds in general, but he hopes to build future versions that can identify birds with more specificity, perhaps down to the species. Identifying birds by vision is certainly one viable way of going about this process, but one of our other favorite bird-watching tools was demonstrated by [Benn Jordan] which uses similar hardware but listens for bird calls rather than looking for the birds with a vision-based system.

Continue reading “A Bird Watching Assistant” →

A man holds a license plate in front of a black pickup (F-150 Lightning) tailgate. It is a novelty Georgia plate with the designation P00-5000. There are specks of black superimposed over the plate with a transparent sticker, giving it the appearance of digital mud in black.

A Deep Dive On Creepy Cameras

September 18, 2025 by 33 Comments

George Orwell might’ve predicted the surveillance state, but it’s still surprising how many entities took 1984 as a how-to manual instead of a cautionary tale. [Benn Jordan] decided to take a closer look at the creepy cameras invading our public spaces and how to circumvent them.

[Jordan] starts us off with an overview of how machine learning “AI” is used Automated License Plate Reader (ALPR) cameras and some of the history behind their usage in the United States. Basically, when you drive by one of these cameras, an ” image segmentation model or something similar” detects the license plate and then runs optical character recognition (OCR) on the plate contents. It will also catalog any bumper stickers with the make and model of the car for a pretty good guess of it being your vehicle, even if the OCR isn’t 100% on the exact plate sequence.

Where the video gets really interesting is when [Jordan] starts disassembling, building, and designing countermeasures to these systems. We get a teardown of a Motorola ALPR for in-vehicle use that is better at being closed hardware than it is at reading license plates, and [Jordan] uses a Raspberry Pi 5, a Halo AI board, and You Only Look Once (YOLO) recognition software to build a “computer vision system that’s much more accurate than anything on the market for law enforcement” for $250.

[Jordan] was able to develop a transparent sticker that renders a license plate unreadable to the ALPR but still plainly visible to a human observer. What’s interesting is that depending on the pattern, the system could read it as either an incorrect alphanumeric sequence or miss detecting the license plate entirely. It turns out, filtering all the rectangles in the world to find just license plates is a tricky problem if you’re a computer. You can find the code on his Github, if you want to take a gander.

You’ve probably heard about using IR LEDs to confuse security cameras, but what about yarn? If you’re looking for more artistic uses for AI image processing, how about this camera that only takes nudes or this one that generates a picture based on geographic data?

Continue reading “A Deep Dive On Creepy Cameras” →

A black and white device sits on a beige table. A white rotary knob projects out near the base of it's rectangular shape nearest the camera. Near it is a black rectangular section of the enclosure with six white dots protruding through holes to form a braille display. A ribbon cable snakes out of the top of the enclosure and over the furthest edge of the device, presumably connecting to a camera on the other side of the device.

This Polaroid-esque OCR Machine Turns Text To Braille In The Wild

August 15, 2025 by 2 Comments

One of the practical upsides of improved computer vision systems and machine learning has been the ability of computers to translate text from one language or format to another. [Jchen] used this to develop Braille Vision which can turn inaccessible text into braille on the go.

Using a headless Raspberry Pi 4 or 5 running Tesseract OCR, the device has a microswitch shutter to take a picture of a poster or other object. The device processes any text it finds and gives the user an audible cue when it is finished. A rotary knob on the back of the device then moves the braille display pad through each character. When the end of the message is reached, it then cycles back to the beginning.

Development involved breadboarding an Arduino hooked up to some MOSFETs to drive the solenoids for the braille display until the system worked well enough to solder together with wires and perfboard. Everything is housed in a 3D printed shell that appears similar in size to an old Polaroid instant camera.

We’ve seen a vibrating braille output prototype for smartphones, how blind makers are using 3D printing, and are wondering what ever happened with “tixel” displays? If you’re new to braille, try 3D printing your own trainer out of TPU.

Continue reading “This Polaroid-esque OCR Machine Turns Text To Braille In The Wild” →

Homebrew Traffic Monitor Keeps Eyes On The Streets

March 11, 2025 by 62 Comments

How many cars go down your street each day? How fast were they going? What about folks out on a walk or people riding bikes? It’s not an easy question to answer, as most of us have better things to do than watch the street all day and keep a tally. But at the same time, this is critically important data from an urban planning perspective.

Of course, you could just leave it to City Hall to figure out this sort of thing. But what if you want to get a speed bump or a traffic light added to your neighborhood? Being able to collect your own localized traffic data could certainly come in handy, which is where TrafficMonitor.ai from [glossyio] comes in.

Continue reading “Homebrew Traffic Monitor Keeps Eyes On The Streets” →

Custom Drone Software Searches, Rescues

October 24, 2024 by 17 Comments

When a new technology first arrives in people’s hands, it often takes a bit of time before the full capabilities of that technology are realized. In much the same way that many early Internet users simply used it to replace snail mail, or early smartphones were used as more convenient methods for messaging and calling than their flip-phone cousins, autonomous drones also took a little bit of time before their capabilities became fully realized. While some initially used them as a drop-in replacement for things like aerial photography, a group of mountain rescue volunteers in the United Kingdom realized that they could be put to work in more efficient ways suited to their unique abilities and have been behind a bit of a revolution in the search-and-rescue community.

The first search-and-rescue groups using drones to help in their efforts generally used them to search in the same way a helicopter would have been used in the past, only with less expense. But the effort involved is still the same; a human still needed to do the searching themselves. The group in the UK devised an improved system to take the human effort out of the equation by sending a drone to fly autonomously over piece of mountainous terrain and take images of the ground in such a way that any one thing would be present in many individual images. From there, the drone would fly back to its base station where an operator could download the images and run them through a computer program which would analyse the images and look for outliers in the colors of the individual pixels. Generally, humans tend to stand out against their backgrounds in ways that computers are good at spotting while humans themselves might not notice at all, and in the group’s first efforts to locate a missing person they were able to locate them almost immediately using this technology.

Although the system is built on a mapping system somewhat unique to the UK, the group has not attempted to commercialize the system. MR Maps, the software underpinning this new feature, has been free to use for anyone who wants to use it. And for those just starting out in this field, it’s also worth pointing out that location services offered by modern technologies in rugged terrain like this can often be misleading, and won’t be as straightforward of a solution to the problem as one might think.