Tag Archives: camera board

Camera board comparisons: Pi NoIR v1 vs Pi NoIR v2

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The new 8 megapixel Raspberry Pi camera board has been out for just over a month, and we’ve been seeing some really impressive work being done with it. As many of you know, we also make a version of the camera board with no infrared (IR) filter: the Pi NoIR. Version 2 of the Pi NoIR has also been upgraded to use an 8 megapixel Sony sensor. People use the Pi NoIR to see in the dark (especially useful for wildlife camera traps and for security cams), to achieve some wacky camera effects, and to work on hyperspectral imaging.

What we haven’t seen so far is any comparison of the output from the Pi NoIR v1 and the Pi NoIR v2. So we were really pleased to find this video from Andr.oid Eric which demonstrates the cameras’ raw output side by side, alongside output from both cameras with a selection of IR and UV filters.

Compare Pi Camera NoIR v1 vs V2

Compare Pi Camera NoIR v1 vs V2 http://helloraspberrypi.blogspot.com/2016/05/compare-pi-camera-noir-v1-vs-v2.html

Let us know in the comments if you have your own comparison photos or video from v1 and v2 of either of the camera boards – we’d love to see more!

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Le Myope – a confused camera

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This is very silly indeed.

Salade Tomate Oignon in Paris seems to be making a bit of a habit of doing outlandish things with Raspberry Pi and other people’s photography. You might remember Layer Cam from a couple of years ago, which allows you to point a sandwich box pretending to be a camera at a landmark and serves up somebody else’s picture of the same thing, using GPS coordinates and Google Image Search.

His newest Raspberry Pi hack, Le Myope (for non-Francophones, that’s The Shortsighted), actually includes a camera – but the results are not what you’d expect. Here’s a bit of video to show you more.

Le myope: a similar images Raspberry Pi camera

Short-sighted camera based on a Raspberry Pi and Google similar images. Find instruction and code to build your own: http://saladetomateoignon.com/Wordpress/a-short-sighted-raspberry-pi-camera/ Music: Samuel Belay – Qeresh Endewaza Logo: Alice www.alicesawicki.com Images: Charly www.nnprod.com

Salade Tomate Oignon says:

Even more imprecise than a blurry polaroid picture, or than a filter-abused instagram shot.
Using the most advanced algorithms based on machine learning and computer vision, here is ‘Le myope’, a short-sighted camera.
The new iteration of the layercam ‘Why are you taking this picture? It’s already on the Internet!’ is a Raspberry Pi based camera, that takes a picture and returns a similar one from Google similar image search.
Use it in a popular place and chances are that you will get the same picture taken by someone else. (That happened with the mural during one of the tests)
Use it in a remote place and get random roughly similar pictures from all over the internet!

This is an extremely daft project which pleased us out of all proportion. You can find code and instructions to build your own at Salade Tomate Oignon’s website. Go forth and take other people’s photographs.

 

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Learn all about the new Raspberry Pi Camera Module v2 in The MagPi 45

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Earlier this week, the brand new Raspberry Pi Camera Module v2 was revealed to the world, its headline feature being an 8-megapixel sensor. It’s been a few years since the original came out and the new camera is an excellent little upgrade to the existing model; you can find out all the details in our complete breakdown in Issue 45 of The MagPi magazine, which is out today.

Picture perfect, the new Pi Camera Module v2

Picture perfect, the new Pi Camera Module v2

As well as covering the camera and giving you some projects to start you off with it, we also have a look at the ten best Pi-powered arcade machines, which should give you some ideas for a retro games system of your own. There are also tutorials on creating lighting effects for costumes with a Pi and some NeoPixels, making an Asteroids clone in Basic, and building an IoT thermometer. We also have Astro Pi news, excellent projects, reviews, and everything else you’d expect from your monthly MagPi.

A model railway, in-part powered by Pi Zero

A model railway, powered in-part by Pi Zero

Highlights from issue 45:

  • Replicate an Astro Pi experiment
    Create a humidity sensor, similar to the Sweaty Astronaut code
  • Hacking with dinosaurs
    The MagPi heads to the Isle of Wight to see how some animatronic dinos are being hacked with Pi
  • Original games on the Pi
    Play three brand-new games on your Pi thanks to YoYo and GameMaker Studio
  • Moon pictures
    Find out how to use the camera board to take amazing photos of the moon
  • And much, much more!

How to buy
As usual, you can get The MagPi in store from WH Smith, Tesco, Sainsbury’s, and Asda as well as buying copies online from our store. It’s also available digitally via our app on Android and iOS. If you fancy subscribing to the magazine to make sure you never miss an issue, you can do that to on our subscription site.

Free Creative Commons download
As always, you can download your copy of The MagPi completely free. Grab it straight from the issue page for The MagPi 45.

Don’t forget, though, that like sales of the Raspberry Pi itself, all proceeds from the print and digital editions of the magazine go to help the Foundation achieve its charitable goals. Help us democratise computing!

We hope you enjoy this month’s issue! Before anyone asks, no, the magazine unfortunately does not come with a free camera. Sorry!

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New 8-megapixel camera board on sale at $25

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The 5-megapixel visible-light camera board was our first official accessory back in 2013, and it remains one of your favourite add-ons. They’ve found their way into a bunch of fun projects, including telescopes, kites, science lessons and of course the Naturebytes camera trap. It was soon joined by the Pi NoIR infrared-sensitive version, which not only let you see in the dark, but also opened the door to hyperspectral imaging hacks.

As many of you know, the OmniVision OV5647 sensor used in both boards was end-of-lifed at the end of 2014. Our partners both bought up large stockpiles, but these are now almost completely depleted, so we needed to do something new. Fortunately, we’d already struck up conversation with Sony’s image sensor division, and so in the nick of time we’re able to announce the immediate availability of both visible-light and infrared cameras based on the Sony IMX219 8-megapixel sensor, at the same low price of $25. They’re available today from our partners RS Components and element14, and should make their way to your favourite reseller soon.

Visible light camera v2

The visible light camera…

...and its infrared cousin

…and its infrared cousin

In our testing, IMX219 has proven to be a fantastic choice. You can read all the gory details about IMX219 and the Exmor R back-illuminated sensor architecture on Sony’s website, but suffice to say this is more than just a resolution upgrade: it’s a leap forward in image quality, colour fidelity and low-light performance.

VideoCore IV includes a sophisticated image sensor pipeline (ISP). This converts “raw” Bayer-format RGB input images from the sensor into YUV-format output images, while correcting for sensor and module artefacts such as thermal and shot noise, defective pixels, lens shading and image distortion. Tuning the ISP to work with a particular sensor is a time-consuming, specialist activity: there are only a handful of people with the necessary skills, and we’re very lucky that Naush Patuck, formerly of Broadcom’s imaging team, volunteered to take this on for IMX219.

Naush says:

Regarding the tuning process, I guess you could say the bulk of the effort went into the lens shading and AWB tuning. Apart from the fixed shading correction, our auto lens shading algorithm takes care of module to module manufacturing variations. AWB is tricky because we must ensure correct results over a large section of the colour temperature curve; in the case of the IMX219, we used images illuminated by light sources from 1800K [very “cool” reddish light] all the way up to 16000K [very “hot” bluish light].

The goal of auto white balance (AWB) is to recover the “true” colours in a scene regardless of the colour temperature of the light illuminating it: filming a white object should result in white pixels in sunlight, or under LED, fluorescent or incandescent lights. You can see from these pairs of before and after images that Naush’s tune does a great job under very challenging conditions.

AWB with high colour temperature

AWB at higher colour temperature

AWB at lower colour temperature

AWB at lower colour temperature

As always, we’re indebted to a host of people for their help getting these products out of the door. Dave Stevenson and James Hughes (hope you and Elaine are having a great honeymoon, James!) wrote most of our camera platform code. Mike Stimson designed the board (his second Raspberry Pi product after Zero). Phil Holden, Shinichi Goseki, Qiang Li and many others at Sony went out of their way to help us get access to the information Naush needed to tune the ISP.

We’re really happy with the way the new camera board has turned out, and we can’t wait to see what you do with it. Head over to RS Components or element14 to pick one up today.

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Weather, security and temperature cam

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We see a lot of Raspberry Pis being used as security cameras – check out this fine example that we blogged back in 2013 – they’re a cheap and effective solution for people who want to deter burglars and vandals.

This very serious-looking camera housing is only £5.49 on Amazon - click the image to buy.

This very serious-looking fake camera housing is only £5.49 on Amazon – click the image to buy, and then stick a camera board inside.

The good folks at Adafruit had one of those ideas that makes you slap yourself in the forehead for not coming up with it yourself. They’ve made a camera system which can upload images to the cloud, so you can check on it from wherever you are – but it also uploads other sensor data of your choosing (in this example, temperature) and graphs it using matplotlib. A sort of proto-Nest, if you will.

camera_monitor_picam_and_temp_on_pitft v1

We’re using Adafruit’s adafruit.io here: it’s their new Internet of Things API. It’s still in Beta, but pretty solid; we’d be interested to hear how you get on with it.

You can find an exhaustive how-to here. Jeremy Blythe from Adafruit says:

This project uses two Raspberry PIs – a sender and a receiver. The sender has a Raspberry Pi Camera and an MCP9808 temperature sensor to publish data to adafruit.io. The receiver, a dashboard somewhere else in the world, subscribes to this data feed and displays it.

This dashboard Raspberry Pi has a PiTFT and displays the image whenever it’s sent to the feed (every 5 minutes), the current temperature is overlaid on the image using pygame. The final cherry on the cake here is that if you tap the screen you flip to the graph view. This takes the data from the feed using the io-client-python data method, pulls out the last 24 hours and uses matplotlib to draw a graph of temp/time. Of course, you can see the feeds in the adafruit.io online dashboard too!

There’s a lot you can do in terms of feature-creep here; we’re thinking about what other sensors you could usefully add, and what else you might be able to do with a big dataset of images. Go wild – and tell us if you make one yourselves!

 

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Cat exercise wheel

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This is not a hamster.

(I could stare at that all day.)

Cat owners among you with hard floor coverings will recognise the eldritch skittering of tiny paws at the witching hour, when all cats believe they have become rally cars. The owner of Jasper and Ruben (who, when researching this post, I thought was called Jasper Ruben; he remains anonymous for now – please leave a comment with your name if you’d like to!) has mechanised the problem. With a Raspberry Pi, natch.

C2OcUcW

This is the web interface for Jasper and Ruben’s wheel. Cat-propelled, and Raspberry Pi-monitored, it logs distance travelled, average speed, duration of feline whirring, and all that good stuff, and displays the statistics in real time.

Here’s the back, where the clever happens. (And the top of Ruben’s head.)

UASTvwa

The Pi’s GPIO is hooked up to a coil sensor behind the wheel, which is housed in an old DSL splitter box, held as close as possible to the wheel without actually touching it. A coil sensor detects magnetic field, so the wheel itself has some modifications to make it detectable and measurable: six small ferrous nails hidden in the lining.

d19gBcu

The Pi drives a camera board and interprets the feedback from the sensor, so it can display live statistics as the cat runs. It also enables the user to record any particularly nifty bits of cat-sprinting.

Being human, you want to see more video of the setup in action. Here’s Jasper, being taunted by a laser dot, with real-time stats at the top of the video.

And here’s proof that the cats will use the wheel spontaneously:

You can see a comprehensive photo how-to on Imgur; Jasper and Ruben’s owner is also answering questions about the build over on Reddit.

We want to see someone modify this to use the wheel’s rotation to charge a battery. What would you use it to power? (I’m thinking kibble dispenser…)

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