Blackjack Game Plays With The Limits Of PyPortal

It’s that time of year again, when fall is quickly ushered out to make room for all things holiday-related. For many of us, this means going on trips to visit relatives, which, depending on the relatives, can mean soul-crushing boredom. [Andy] has fun relatives who frequent the casino tables, and they inspired him to brush up on his blackjack game.

Some people would just find a virtual blackjack table or bust out an actual deck of cards to practice, but this is Hackaday. [Andy] busted out his PyPortal and tried his hand at making a blackjack game. The PyPortal is an Adafruit IoT box that makes it easy to scrape and display all kinds of JSON goodness from around the web, like NASA’s image of the day. GUI building is already baked in, so he just needed some oome open source playing card images and he was off.

The real gamble here might be the code he wrote; at 500+ lines, [Andy]’s probably pushing his luck with the PyPortal. But you know what they say — you can’t win if you don’t play. And if you want to improve your odds of winning, teach a robot to count cards for you.

Thanks for the tip, [foamyguy].

Let The Cards Fall Where They May, With A Robotic Rain Man

Finally,  a useful application for machine vision! Forget all that self-driving nonsense and facial recognition stuff – we’ve finally got an AI that can count cards at the blackjack table.

The system that [Edje Electronics] has built, dubbed “Rain Man 2.0” in homage to the classic title character created by [Dustin Hoffman] for the 1988 film, aims to tilt the odds at the blackjack table away from the house by counting cards. He explains one such strategy, a hi-low count, in the video below, which Rain Man 2.0 implements with the help of a webcam and YOLO for real-time object detection. Cards are detected in any orientation based on their suit and rank thanks to an extensive training set of card images, which [Edje] generated synthetically via some trickery with OpenCV. A script automated the process and yielded a rich training set of 50,000 images for YOLO. A Python program implements the trained model into a real-time card counting application.

Rain Man 2.0 is an improvement over [Edje]’s earlier Tensor Flow card counter, but it still has limitations. It can’t count into a six-deck shoe as the fictional [Rain Man] could, at least not yet. And even though cheater’s justice probably isn’t all cattle prods and hammers these days, the hardware needed for this hack is not likely to slip past casino security. So [Edje] has wisely limited its use to practicing his card counting skills. Eventually, he wants to turn Rain Man into a complete AI blackjack player, and explore its potential for other games and to help the visually impaired.

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