BlackJack AI

Computer Vision-Powered Blackjack Strategy Advisor using YOLO object detection

BlackJack AI Demo - Card Detection and Strategy

Computer Vision-Powered Blackjack Strategy

BlackJack AI is an intelligent web application that combines computer vision and optimal blackjack strategy to provide real-time decision-making assistance. Simply upload an image of your blackjack hand, and the AI will analyze the cards using YOLO object detection, calculate hand values, and recommend the statistically optimal move based on professional blackjack strategy.

The system uses a trained YOLO model to detect and identify all 52 playing cards, implements mathematically proven basic strategy, and provides instant recommendations with confidence percentages through a modern Flask web interface.

YOLO Object Detection
Flask
Computer Vision
Machine Learning
Basic Strategy
Tailwind CSS

How It Works

Upload an image of your blackjack table and get instant strategy recommendations:

1. Upload Your Hand

Take a photo of your blackjack table or upload an existing image. The application accepts various image formats and automatically resizes for optimal processing.

Card Detection Input
2. AI Card Detection

Our trained YOLO model detects and identifies all visible playing cards, distinguishing between dealer and player hands based on position.

Strategy Output
3. Strategy Calculation

The system calculates hand values, considers soft/hard aces, and references the optimal basic strategy table to provide the best statistical move with confidence percentage.

✊
Stand

Keep current hand

👆
Hit

Take another card

⏫
Double

Double bet, one card

Key Features

🎯
Real-time Card Detection

Advanced YOLO object detection identifies playing cards in uploaded images with high accuracy across all 52 cards.

🧠
Optimal Strategy Engine

Implements mathematically proven blackjack basic strategy for maximum winning probability.

💻
Web-based Interface

Clean, responsive Flask web application with intuitive drag-and-drop image upload.

📊
Visual Feedback

Annotated images showing detected cards, hand values, and strategy recommendations.

⚡
Fast Processing

Optimized YOLO model provides near-instant card recognition and strategy calculation.

🎨
Modern UI/UX

Dark theme with matrix-style animations creating an engaging user experience.

Technical Implementation

🤖 Machine Learning Stack
  • • YOLO (You Only Look Once): Real-time object detection
  • • Ultralytics: Modern YOLO implementation
  • • Custom Training: 52-card deck recognition
  • • PIL/Pillow: Image manipulation and annotation
🌐 Web Framework
  • • Flask: Lightweight Python web framework
  • • JavaScript/jQuery: Interactive frontend
  • • Tailwind CSS: Modern responsive styling
  • • Base64 Encoding: Web-optimized image transfer

Quick Start

1. Clone the Repository
git clone https://github.com/nitheesh-cpu/BlackJack-AI.git
cd BlackJack-AI
2. Install Dependencies
pip install -r requirements.txt
3. Run the Application
python main.py
4. Access the Web Interface
Open browser to: http://localhost:5000