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OK, I'm done! I think that in terms of the system of work it is an automated system, but still, it's unusual. Your card detector works amazingly well! If my blackjack robot is going to work, it needs to be able to count cards even when they're overlapping. I'll have to implement a state machine that brings him through different phases of a round of blackjack: reading initial deal, making play decisions, and resolving the hand. Yes, delete it Cancel. Choose more interests. Also, I only have the detector trained to recognize card ranks nine, ten, jack, queen, king, and ace. But if I deal some actual blackjack hands in front of the camera, the way it would be done in a casino, it isn't able to detect all the cards. Become a Hackaday. Low cost and open source.{/INSERTKEYS}{/PARAGRAPH} So far, I've made a card detector program that uses a trained machine learning object detection model YOLO v3 that works extremely well at identifying cards. Evan Juras. Official Hackaday Prize Entry. About Us Contact Hackaday. I'm creating the perfect Blackjack player! Similar Projects The Hackaday Prize. For the cards overlapping, just focus the training on the card corners. My next step is to train the detector to recognize ALL cards, not just nine through ace. Remember me. Are you sure? Someone told me that I might be able to train an object detection classifier a type of neural network to recognize the cards even if they're partially obscured or overlapping. Right now, it isn't trained well enough to distinguish that there are two cards in each hand. Following Follow project. Join this project. To make the experience fit your profile, pick a username and tell us what interests you. Description Almost two years since I started this project page It's time for a touch-up on this! However, there are some other problems. However, I'm still going to try! Similar projects worth following. I want to run my blackjack robot on a Raspberry Pi, which has limited processing power. I played in a regular online casino and there also was a similar automated system. Log In. More foods to come. Already have an account? Your profile's URL: hackaday. I am trying to sort the playing cards into 4 baskets of the 4 suits using a simple 2 motor mechanism. This is actually a very cool idea with a blackjack robot. Also, it is still a little inaccurate and sometimes incorrectly identifies cards. The perfect Blackjack player! Forgot your password? This is just an initial list! I wonder how much is it different from a live dealer. View Gallery. Not a member? Modular design, small footprint Pi Zero Supercomputer. It works very well, at least on a gpu. Object detection classifiers recognize patterns to identify objects, so they only need to see a portion of the object to detect it. Svavar Konradsson. I think the solution will involve a combination of machine learning and some image processing with OpenCV. The cards are too overlapped for it to see all the cards. Please let me know if you have any ideas! Unfortunately, blackjack is always dealt with the cards overlapping. Then, I'll run it on a Raspberry Pi and see if it's still able to detect cards fast enough, and make a YouTube video about it. Sign up. I'll see if I can re-create your wonderful work. Create an account to leave a comment. Become a member to follow this project and never miss any updates. You should Sign Up. It's possible that if I fed the trainer hundreds more clearly labeled pictures of overlapping cards, it might be able to see both the cards. I've already given it training pictures, but maybe it will work better if I give it 1, more. I need to find a way to keep the processing requirements low while still having good accuracy. This Raspberry Pi-powered robot will identify the cards in its hand and the dealer's upcard, and use a Hit or Stand lookup table to determine the best play to make. I tried using the lower-power MobileNet-SSD model, but it doesn't work very well at identifying individual cards. To solve the occlusion accuracy problem have you considered training and recognizing just card corners, their left sides, or just the text rather than the entire card? You should persist on the path of machine learning. I'm still trying to think of how I might be able to get it to work with the cards overlapping. Learn More. An educational system designed to bring AI and complex robotics into the home and school on a budget. {PARAGRAPH}{INSERTKEYS}A Raspberry Pi-powered robot that plays Blackjack and counts cards. I work in Vegas, in surveillance, the program it's self would be awesome to have to run down players with. I wish I had seen this comment when you posted it two months ago. As the project develops, I will undoubtedly find more things I need to do. It only sees the top card. Just one more thing To make the experience fit your profile, pick a username and tell us what interests you. Liked Like project. Max 25 alphanumeric characters. For the most part, it works great when it has a clear view of the cards so does my OpenCV algorithm : And it even works if the cards are overlapping: But if I deal some actual blackjack hands in front of the camera, the way it would be done in a casino, it isn't able to detect all the cards. View project log. More training data might help with this, too. And you are right about the training data: you need lots more. Pick an awesome username. I decided to use Google's TensorFlow machine learning framework to train a playing card detection classifier. The trained playing card detector just doesn't work very well. Over the past couple months, I've been tinkering with machine learning to try and train an object detection neural network that can detect playing cards. The OpenCV algorithm I used described in this video works great at detecting cards, but it doesn't work if the cards are overlapping even the slightest bit. It will take lots more training pictures to get it to work with every card rank. Hack a Day Menu Projects. If you could get it to spit the count out on to a spread sheet that an agent could add the rest of the needed info to I think you'd have a million dollar product. For the most part, it works great when it has a clear view of the cards so does my OpenCV algorithm :. We found and based on your interests. Is it possible to perform the detection on the computer and use a raspberry pi as a controller for motors? Makes doughnuts, fries and onion rings. It will also be able to count cards and implement card counting strategies like the "Illustrious 18". I have a sneaking suspicion that it won't work as well on the lower numbers four is very similar to five, etc. Here's a video showing how the machine learning-based card detector works! I've spent lots of time learning about machine learning enough to make a tutorial showing how to train your own and I've taken hundreds of pictures of playing cards to feed to the training API. Unfortunately, it's starting to seem like machine learning isn't going to be the silver bullet I hoped it would be.