It’s Magic: Uses an IR camera and raspberry pie to scan an invisible card deck during a magic performance

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The card technique would be much easier if the magician knew the location of each card. Paul Nettle And Jeroen Van Goey Create a Github project, ‘Nettle Magic Project‘Which uses special symbols and a camera to locate and identify each card on a deck.

Each card on the deck is marked with a unique barcode. Of course, if the cards are marked in traditional ink, it will disrupt the illusion, so the cards are marked with visible ink only under certain IR conditions. Nettle and Van Goey designed a Raspberry Pi device with a NoIR camera to view the marked cards.

The device runs a scanning server, and is connected to an iOS client application, Abrar, which shows the server’s camera key and decoded deck. With the help of technology, magicians can find out the ordered list of each card on the deck, which cards (s) are missing, and even which cards the deck is facing. The device can be run while performing because it can scan / decode a 1080p image with an ordered call ‘less than 4ms’.

The paid testbed applications are written for macOS and iOS, although there is also support for the Linux and Raspberry Pi platforms. There is currently no Windows or Android version. Full Documentation Detailed outline of testbed application.

There is also a high-level overview of how the device works. Although speed is important, accurate results are important. An error occurred during a live performance. When scanning results To be able to To be wrong, it is very unlikely. Performance is improved by scanning multiple video frames instead of a single frame. The results of multiple frames are analyzed and combined. However, skill concerns are important, as the device will probably be hidden on a magician’s person and may not run out of too much heat or energy.

A high-level overview of the Nettel Magic Project system and its steps

There is an input video frame extended by configuration parameters and a deck definition. The deck is searched, decoded, resolved, and analyzed before a report is created for the user. Each of these primary steps involves secondary and even third processes, which are extensively outlined. Here.

Each playing card is about 0.3 mm thick, and they are scanned in low light conditions using a narrow-band IR camera. Plus, the cards get worn out, and some cards get caught in someone’s hand, so the scanning process isn’t perfect. However, it is ‘generally’ reliable. The ‘Analysis’ episode tries to overcome the lack of confidence by combining the scan results with the ‘most’ accurate scans to create a single ‘confident’ result that can ‘actually be’.

Abra shows the complete results of the client scan. We can see that this scan has created a high confidence value (98).

Creates failures in a variety of situations, including not having the deck framed or too small, failing the readability test because the scanned video is not sharp, having too few cards, or some other common failure. There are various success conditions, including low and high confidence results. When all the steps are completed, the final result is sent to the Abra client.

One of these decks has been marked. Can you tell which one?

The documentation also shows how to create marks using a Sharpie or a custom-printed stamp. The UV Responsive Ink section is not yet complete, but there are some interesting details about creating a marked deck that looks normal to the naked eye.

If you like card tricks, you can try the Netal Magic project for yourself. All packages, tools and documentation are available Github.


Image Credit: Nettle Magic Project / Paul Nettle and Jeroen Van Gogh / Github



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