digital cameras hacks

1045 Articles

Pi-Powered Camera Turns Heads And Lenses In Equal Measure

November 7, 2025 by 11 Comments

Have you ever seen photos of retro movie sets where the cameras seem to be bedazzled with lenses? Of course you can only film via one lens at a time, but mounting multiple lenses on a turret as was done in those days has certain advantages –particularly when working with tiny M12 lenses, like our own [Jenny List] recently did with this three-lens, Pi-zero based camera.

Given that it’s [Jenny], the hardware is truly open source, with not just the Python code to drive the Pi but the OpenSCAD code used to generate the STLs for the turret and the camera body all available via GitHub under a generous CC-BY-SA-4.0 license. Even using a cheap sensor and lenses from AliExpress, [Jenny] gets good results, as you can see from the demo video embedded below. (Jump to 1:20 if you just want to see images from the camera.)

The lenses are mounted to a 3D printed ring with detents to lock each quickly in place, held in place by a self-tapping screw, proving we at Hackaday practice what we preach. (Or that [Jenny] does, at least when it comes to fasteners.) Swapping lenses becomes a moment’s twist, as opposed to fiddling with tiny lenses hoping you don’t drop one. We imagine the same convenience is what drove turret cameras to be used in the movie industry, once upon a time.

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Broken Phone To Cinema Camera With A Lens Upgrade

October 18, 2025 by 8 Comments

The advent of the mobile phone camera has caused a revolution in film making over the last couple of decades, lowering the barrier to entry significantly, and as the cameras have improved, delivering near-professional-grade quality in some cases. Mobile phone manufacturers hire film makers to promote their new flagship models and the results are very impressive, but there is still a limitation when it comes to the lenses. [Evan Monsma] has broken through that barrier, modifying an iPhone to take C-mount cinema lenses.

It’s likely many of us have one or two broken mobile phones around, and even if they aren’t flagship models they’ll still have surprisingly good camera sensors. This one is an iPhone that’s seen better days, with a severely cracked glass back and a dislodged lens cover on one of its cameras. Removing the back and the lens cover reveals the sensor. The video below the break has a lot of woodwork and filing away of the phone, as he modifies a C-to-CS ring to serve as a C-mount. In reality the flange distance makes it a CS mount so his C-mount lenses need an adapter, but as anyone who’s used a Raspberry Pi camera will tell you, that’s no hardship.

The final camera has a thick plywood back with a tripod mount installed, the other two cameras work with their Apple lenses, and the C-mount gives great results with a cinema lens. We’re concerned that the Super Glue he uses to fix it all together might not hold up to the weight of bigger lenses, but we’re here for this project and we love it.

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A photo of the camera.

F/0.38 Camera Lens Made With Oil Immersion Microscope Objective

October 17, 2025 by 15 Comments

Over on YouTube [Applied Science] shows us how to make an f/0.38 camera lens using an oil immersion microscope objective.

The f-number of a lens indicates how well it will perform in low-light. To calculate the f-number you divide the focal length by the diameter of the aperture. A common f-number is f/1.4 which is generally considered “fast”.

We are told the fastest commercial lens ever used had f/0.7 and was used by Stanley Kubrick to shoot the film Barry Lyndon which was recorded only with candle light.

A microscope objective is a crucial lens that gathers and magnifies light to form an image. It plays a key role in determining the quality and clarity of the final magnified image produced by a microscope.

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DIY 35mm Film Scanning

October 12, 2025 by 26 Comments

If you are sitting on a horde of negatives, waiting for the digital photography fad to die off, it may be time to think about digitizing your old film. [Kinpro1024] can help with the PiDigitzier, an open-source film scanning solution. The build centers around a Pi Zero 2, a Pi HQ camera, and a diffusing  LED lighting fixture. Of course, there’s also some miscellaneous hardware and a camera lens; the example used a Pentax 50 mm f1.8 lens.

Half of the project is mechanical. An MDF tower provides a stable 250 mm workspace and decks that can slide up and down using threaded rods and curtain rods. Apparently, leveling the platforms is important not only for the optics but also to allow the MDF to move along the rods without binding.

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Detecting Surveillance Cameras With The ESP32

September 26, 2025 by 44 Comments

These days, surveillance cameras are all around us, and they’re smarter than ever. In particular, many of them are running advanced algorithms to recognize faces and scan license plates, compiling ever-greater databases on the movements and lives of individuals. Flock You is a project that aims to, at the very least, catalogue this part of the surveillance state, by detecting these cameras out in the wild.

The system is most specifically set up to detect surveillance cameras from Flock Safety, though it’s worth noting a wide range of companies produce plate-reading cameras and associated surveillance systems these days. The device uses an ESP32 microcontroller to detect these devices, relying on the in-built wireless hardware to do the job. The project can be built on a Oui-Spy device from Colonel Panic, or just by using a standard Xiao ESP32 S3 if so desired. By looking at Wi-Fi probe requests and beacon frames, as well as Bluetooth advertisements, it’s possible for the device to pick up telltale transmissions from a range of these cameras, with various pattern-matching techniques and MAC addresses used to filter results in this regard. When the device finds a camera, it sounds a buzzer notifying the user of this fact.

Meanwhile, if you’re interested in just how prevalent plate-reading cameras really are, you might also find deflock.me interesting. It’s a map of ALPR camera locations all over the world,  and you can submit your own findings if so desired. The techniques used by in the Flock You project are based on learnings from the DeFlock project. Meanwhile, if you want to join the surveillance state on your own terms, you can always build your own license plate reader instead!

[Thanks to Eric for the tip!]

Build Your Own 6K Camera

September 23, 2025 by 17 Comments

[Curious Scientist] has been working with some image sensors. The latest project around it is a 6K camera. Of course, the sensor gives you a lot of it, but it also requires some off-the-shelf parts and, of course, some 3D printed components.

An off-the-shelf part of a case provides a reliable C mount. There’s also an IR filter in a 3D-printed bracket.

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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 36 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?

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