Posted in Blackjack Learn

RAIN MAN 2.0, Blackjack AI – Part 1 – Counting Cards Using Machine Learning and Python

Learn Blackjack Video Source & Info:

RAIN MAN 2.0 is a card counting AI that’s destined to be the ultimate blackjack player! Created using machine learning and Python, RAIN MAN 2.0 can easily count his way through a deck of playing cards. To identify cards, he uses a YOLO v3 detection model trained on 50,000 synthetically generated images.

This video explains how he works and what I plan to do with him. It’s the first video in a series of videos that I will be posting as I build out his functionality.

— Affiliate Links —
If you haven’t seen the movie Rain Man, you need to watch it!! https://amzn.to/2XL7bit
Logitech C920 1080p webcam used by RAIN MAN 2.0: https://amzn.to/2WULb7B

Twitter: https://twitter.com/EdjeElectronics
RAIN MAN 2.0 project page on Hackaday: https://hackaday.io/project/27639-rain-man-20-blackjack-robot

— Links mentioned in video —
geaxgx1’s playing card detection video:

Wizard of Odds website, great source of blackjack information and strategy:
https://wizardofodds.com/games/blackjack/card-counting/high-low/

— Music —
Summer Coffee by Barradeen:

Hidden camera blackjack footage taken from Blackjack Army YouTube channel: https://youtu.be/Ri2dS3GkzH0

Source: YouTube

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RAIN MAN 2.0, Blackjack AI – Part 1 – Counting Cards Using Machine Learning and Python

10 thoughts on “RAIN MAN 2.0, Blackjack AI – Part 1 – Counting Cards Using Machine Learning and Python”

  3. By now aren't there laws against using AI in casinos? Its like athletes using steroids..

  4. Ah ah I was wondering why I had a sudden spike in the count of my subscribers :-)) Thanks for the big shout out, bro ! Your project is really great, I am already impatient to watch the following parts and curious about the port on the raspberry ! Your video editing is excellent and you seem to have fun doing it (I know how time consuming this task is 😉

    FYI, since the post of my video one year ago, I had the opportunity to test the following: take only one good picture of each card (instead of a video under varying lighting conditions) and rely on the image augmentation library to simulate the lighting. That works as well as previously, but is much less cumbersome.

    And good guess, you pronounce my id correctly !

  6. It seems like eventually this will also be able to deviate from basic strategy and even the card counting published deviations because the data will be more granular than simple high lo count. Very cool video.

  7. Question: What are you using to live stream the video from OpenCV?
    Are you just outputting the video result into a html page or something? Or perhaps streaming it somewhere?
    Im asking because im now getting started with Node.js and OpenCV4Nodejs using the Raspberry pi zero (With the same webcam lol). Right now im just taking an image every 200 mili-seconds and sending it to a node server to be viewed remotely.
    Theres a 2 second lag/delay.
    Thanks in advanced.

  9. Any tips on how I would do a text based version of this? I want to start off with that before I work on my own counter using a camera or creating an oop simulator

  10. how do make the GUI window? i mean when u detect the number of cards how do u show it just like 9：25 in ur video. thanks

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