AI-Powered Blackjack Card Detection and Decision Recommendation System
Project Description
This project uses an advanced AI-based computer vision model to automatically detect and recognize playing cards for both the player and the dealer (bot) in a Blackjack game. The system identifies each card, extracts its numerical value, and continuously calculates the total hand value for both sides in real time.
Based on Blackjack rules and probability analysis, the AI then provides intelligent recommendations to the player, such as whether to hit, stand, or play more cautiously, helping improve decision-making and reduce risk. The system also tracks the number of players and evaluates the dealer’s visible cards to enhance strategic accuracy.
This solution demonstrates the integration of machine learning, image recognition, and game strategy logic to create a smart, automated Blackjack assistant.
Key Features
- AI-based playing card detection and recognition
- Real-time card value calculation for player and dealer
- Automatic Blackjack hand total computation
- Intelligent gameplay recommendations (Hit / Stand / Continue)
- Player vs dealer (bot) comparison analysis
- Scalable design for real-time or video-based input
Technologies Used
- Computer Vision (CNN / YOLO / OpenCV)
- Machine Learning & AI Models
- Python for backend logic and analysis
- Game strategy and probability rules