Scanner for decks of cards with bar codes printed on card edges

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Image swift magic computer-vision
Overview

The Nettle Magic Project

This deck of cards has a bar code printed on the edge of each card. Scanning these bar codes would reveal where every card is (or isn't - if cards are missing.)

Think card magic.

A deck of cards with digital marks printed on the edge of each card.

This wouldn't be a very good magic trick if you could see the marks. We need invisible marks.

One of these decks is unmarked, the other is marked with this special ink that is only visible under specific IR conditions.

Two decks of cards - each viewed from the same end. Both decks appear normal.

This device (a Raspberry Pi Zero W with a NoIR camera) can see these marks. The shiny circle is a special IR filter.

A scanning server runs on this small device.

A small computer module, about the size of a thumb. It has a small camera attached. The lens of the camera is covered with what looks like s small round mirror.

This is Abra, the iOS client application running on my iPad. It shows what the server's camera sees along with the decoded deck. As you can see, the IR marks are quite visible to the camera.

A screenshot of an app containing an array of playing cards in suit and numerical order, with a black-and-white image of a deck of playing cards with edge-marks clearly visible.

Your iDevices can also be a server, but they can't see those infrared marks, even with special filters. However, they can see black ink marks and marks made using a different type of invisible ink - ultraviolet fluorescing ink.

A deck of cards with marks on the edges of cards that are glowing brightly under the light of a UV pen light. Next to the deck is an iPad showing the deck from it's camera's perspective.

For hard core developers, I've included the testbed, which has a bunch of visualization tools to understand how things work.

A screenshot of an app that shows a deck of cards in a viewport with marks outlined digitally, and various statistics listed below.

The testbed only runs on Mac. However, the server app is a generic Linux console app and it includes a text-based GUI mode.

A text-based console app with an image of a deck of cards printed using alphanumeric characters. Statistics appear below this text-based viewport.

Performance is critical.

The statistical model requires a full 30Hz of data. Also, this can be strapped to a person's body during a performance. Efficiency means longer battery, less heat.

It can scan/decode a 1080p image to an ordered deck in as little as 4ms. On a rPI.

Get started

Full documentation is available here.

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Comments
  • Compilation error

    Compilation error

    I tried to run steve but I encountered a problem. Screenshot 2022-07-01 at 15 32 12 It is written that there are files missing in the directory where there are the demonstration videos. So I manually added fake videos to see if the code compiles and I got this (My fake videos are simply videos that I renamed with the missing file names in the error message ): Screenshot 2022-07-01 at 15 37 25 The code compiles but I still have a problem. Even when I drag and drop a video it does not work, could you help me pls?

    opened by Chtwin 8
  • Pre-built binaries?

    Pre-built binaries?

    I think it would be a good idea to provide some pre-built binaries for people who don't have a Mac. I do have a Mac, but it's old and I can't even fit Xcode on the amount of space I have left. I'm gonna try a macOS VM in a few minutes, but it'd still be nice to have the binaries. Especially for Abra, packaged as an IPA file.

    opened by KoolenDasheppi 5
  • Swift Compile Error

    Swift Compile Error

    I just try to run Steve on my mac in Xcode, it says Swift Compiler Error 'aalib.h' file not found (cheader.h) Could not build Objective-C module 'C_AAlib' (TextUI.swift)

    167501656656913_ pic )

    opened by caichunjian520 1
Releases(whisper-v29@main+video-rpi)

  • whisper-v29@main+video-rpi(Jul 6, 2022)

    Build of whisper for Raspberry Pi devices running Raspbian Bullseye on armv7 or better hardware. This was built/tested on a rPI model 4.

    ✅ This build includes video capture support ✅

    Prerequisites

    In order to run, you will need to install some dependencies and setup a few files. Do this in a terminal on your Raspberry Pi.

    Your best bet is to clone the repo and drop the pre-built whisper binary into the root of that directory.

    Then, from within that directory, do these things:

    # First, install the repository for the Swift language (see https://github.com/futurejones/swift-arm64)
$ curl -s https://archive.swiftlang.xyz/install.sh | sudo bash

# Next install the dependencies
$ sudo apt install libpng-dev libncurses5-dev libaa1-dev libavcodec-dev libavformat-dev swiftlang

# Next, setup your config files
$ ln -s decks.json ~/.decks.json
$ ln -s whisper.conf ~/.whisper.conf

$ Finally, run a test
$ ./whisper -6 Sources/Steve/Steve/Reference/inter6.quick-random-movements.mp4

    If all goes well, that last command should produce a text-based GUI showing you the playback of the video along with stats of the scanning process.

    Source code(tar.gz)
    Source code(zip)
    whisper.tgz(790.36 KB)

  • v1.0-fixed-deps(Jul 5, 2022)

  • whisper-v29@main-rpi(Jul 5, 2022)

    Build of whisper for Raspberry Pi devices running Raspbian Bullseye on armv7 or better hardware. This was built/tested on a rPI model 4.

    ❌ This build does not include video capture support ❌

    Prerequisites

    In order to run, you will need to install some dependencies and setup a few files. Do this in a terminal on your Raspberry Pi.

    Your best bet is to clone the repo and drop the pre-built whisper binary into the root of that directory.

    Then, from within that directory, do these things:

    # First, install the repository for the Swift language (see https://github.com/futurejones/swift-arm64)
$ curl -s https://archive.swiftlang.xyz/install.sh | sudo bash

# Next install the dependencies
$ sudo apt install libpng-dev libncurses5-dev libaa1-dev libavcodec-dev libavformat-dev swiftlang

# Next, setup your config files
$ ln -s decks.json ~/.decks.json
$ ln -s whisper.conf ~/.whisper.conf

$ Finally, run a test
$ ./whisper -6 Sources/Steve/Steve/Reference/inter6.quick-random-movements.mp4

    If all goes well, that last command should produce a text-based GUI showing you the playback of the video along with stats of the scanning process.

    Source code(tar.gz)
    Source code(zip)
    whisper.tgz(771.02 KB)

  • v1.0(Jul 4, 2022)

Owner
Paul Nettle
By day I work at Gearbox Software. By night, I work on whatever interests me.
Paul Nettle
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