Rediffusion Television: Early Cable TV Delivered Like Telephone

Recently I spent an enjoyable weekend in Canterbury, staying in my friend’s flat with a superb view across the rooftops to the city’s mediaeval cathedral. Bleary-eyed and in search of a coffee on the Sunday morning, my attention was immediately drawn to one of her abode’s original built-in features. There on the wall in the corner of the room was a mysterious switch.

Housed on a standard-sized British electrical fascia was a 12-position rotary switch, marked with letters A through L. An unexpected thing to see in the 21st century and one probably unfamiliar to most people under about 40, I’d found something I’d not seen since my university days in the early 1990s: a Rediffusion selector switch.

If you have cable TV, there is probably a co-axial cable coming into your home. It is likely to carry a VHF signal, either a series of traditional analogue channels or a set of digital multiplexes. “Cable ready” analogue TVs had wideband VHF tuners to allow the channels to be viewed, and on encrypted systems there would have been a set-top box with its own analogue tuner and decoder circuitry.

Your digital cable TV set-top box will do a similar thing, giving you the channels you have subscribed to as it decodes the multiplex. At the dawn of television transmission though, none of this would have been possible. Co-axial cable was expensive and not particularly high quality, and transistorised wideband VHF tuners were still a very long way away. Engineers designing the earliest cable TV systems were left with the technology of the day derived from that of the telephone networks, and in Britain at least that manifested itself in the Rediffusion system whose relics I’d found.

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Object Detection, With TensorFlow

Getting computers to recognize objects has been a historically difficult problem in computer science, but with the rise of machine learning it is becoming easier to solve. One of the tools that can be put to work in object recognition is an open source library called TensorFlow, which [Evan] aka [Edje Electronics] has put to work for exactly this purpose.

His object recognition software runs on a Raspberry Pi equipped with a webcam, and also makes use of Open CV. [Evan] notes that this opens up a lot of creative low-cost detection applications for the Pi, such as setting up a camera that detects when a pet is waiting at the door to be let inside or outside, counting the number of bees entering and exiting a beehive, or monitoring parking spaces at an office.

This project uses a number of other toolkits as well, including Protobuf. It also makes extensive use of Python scripts, but if you’re comfortable with that and you have an application for computer vision, [Evan]’s tutorial will get you started.

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Bringing Augmented Reality to the Workbench

[Ted Yapo] has big ideas for using Augmented Reality as a tool to enhance an electronics workbench. His concept uses a camera and projector system working together to detect objects on a workbench, and project information onto and around them. [Ted] envisions virtual displays from DMMs, oscilloscopes, logic analyzers, and other instruments projected onto a convenient place on the actual work area, removing the need to glance back and forth between tools and the instrument display. That’s only the beginning, however. A good camera and projector system could read barcodes on component bags to track inventory, guide manual PCB assembly by projecting which components go where, display reference data, and more.

An open-sourced, accessible machine vision system working in tandem with a projector would open a lot of doors. Fortunately [Ted] has prior experience in this area, having previously written the computer vision code for room-scale dynamic projection environments. That’s solid experience that he can apply to designing a workbench-scale system as his entry for The Hackaday Prize.

Twitch Stream Turned Infinity Mirror

Most Hackaday readers are likely to be familiar with the infinity mirror, a piece of home decor so awesome that Spock still has one up on the wall in 2285. The idea is simple: two parallel mirrors bounce and image back and forth, which creates a duplicate reflection that seems to recede away into infinity. A digital version of this effect can be observed if you point a webcam at the screen that’s displaying the camera’s output. The image will appear to go on forever, and the trick provided untold minutes of fun during that period in the late 1990’s where it seemed everyone had a softball-shaped camera perched on their CRT monitors.

Making use of that webcam in 2018.

While you might think you’ve already seen every possible variation of this classic visual trick, [Matt Nishi-Broach] recently wrote in to tell us about an infinity mirror effect he’s created using the popular streaming platform Twitch. The public is even invited to fiddle with the visuals through a set of commands that can be used in the chat window.

It works about how you’d expect: the stream is captured, manipulated through various filters, and then rebroadcast through Twitch. This leads to all sorts of weird visual effects, but in general gives the impression that everything is radiating from a central point in the distance.

While [Matt] acknowledges that there are probably not a lot of other people looking to setup their own Twitch feedback loops, he’s still made his Python code available for anyone who might be interested. There’s a special place in Hacker Valhalla for those who release niche software like this as open source. They’re the real MVPs.

If you’d like to get started on your infinite journey with something a bit more physical, we’ve covered traditional infinity mirror builds ranging from the simplistic to the gloriously over-engineered.

RGB Sensor’s New Job: Cryptocurrency Trade Advisor

[XenonJohn] dabbles in cryptocurrency trading, and when he saw an opportunity to buy an RGB color sensor, his immediate thought — which he admitted to us would probably not be the immediate thought of most normal people — was that he could point it to his laptop screen and have it analyze the ratio of green (buy) orders to red (sell) orders being made for crypto trading. In theory, if at a given moment there are more people looking to buy than there are people looking to sell, the value of a commodity could be expected to go up slightly in the short-term. The reverse is true if a lot of sell orders coming in relative to buy orders. Having this information and possibly acting on it could be useful, but then again it might not. Either way, as far as out-of-left-field project ideas go, promoting an RGB color sensor to Cryptocurrency Trading Advisor is a pretty good one.

Since the RGB sensor only sees what is directly in front of it, [XenonJohn] assembled a sort of simple light guide. By enclosing the area of the screen that contains orders in foil-lined cardboard, the sensor can get a general approximation of the amount of red (sell orders) versus green (buy orders). The data gets read by an Arduino which does a simple analysis and sends alerts when a threshold is crossed. He dubbed it the Crypto-Eye, and a video demo is embedded below.

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Vlogging With Vintage 1980s Equipment

[Dan Mace] decided to try vlogging 1980s style. To do this, he built Pram Cam — a one-man mobile video recording setup using vintage gear. [Dan] is a YouTuber from Cape Town, South Africa. His goal for this project was to motivate people to get out there and make videos. Smartphones, action cams, and modern video equipment all have made it incredibly easy to create content.

[Dan] reminds us of this by grabbing a vintage 1984 video camera – a Grundig vs150 VHS recorder. He couples the camera with a sturdy video tripod, blimp microphone, CRT TV as a monitor, and everything else needed for a period-accurate recording setup.

In a build sequence even the A-Team would appreciate, [Dan] tears down a rusty old three wheel pram, or baby carriage for the Americans out there. He then mounts the video setup to the pram frame using duct tape, zip ties, and a few odd pieces of wood. The result is a proper hacked off-road rolling video studio.

He then uses Pram Cam to film some of the great scenery in Cape Town — beaches, rocky cliffs, and even a helicopter ride. To say the pram was a bit more cumbersome than a cell phone would be the understatement of the year.

The video quality from the camera looks quite a bit worse than we would expect. Some of this may be due to Dan’s digitizing system though the chances are it’s from the camera itself. The Grundig captured video using a Saticon, which was Hitachi’s version of the video camera tube. That’s right, this is a tube based camera – no CMOS sensor, nor CCD. Tubes might not have Jello effect, but they do have all the blooming, motion blur, and other problems one might expect from a 34-year-old device.

What becomes of the Pram Cam? You’ll have to watch the video below to find out. Dan’s message is clear though: get out there and film something. Of course this is Hackaday, so if we’ll add that you should build something — then film it!

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