Rock Paper Scissors Game with Mediapipe and OpenCV

This is a real-time Rock Paper Scissors game implemented using Python, OpenCV, and Mediapipe. The game allows players to compete against the computer by making hand gestures (Rock, Paper, Scissors) captured via a webcam. The system detects the player's gesture, generates a random move for the computer, and determines the winner based on classic Rock Paper Scissors rules.

How It Works

1. Technology Stack

• Python: The primary programming language for the project.
• OpenCV: Used for capturing and processing video frames from the webcam.
• Mediapipe: Utilizes the Hands module to detect and track hand landmarks in real-time, enabling gesture recognition.
• Random: Generates random moves for the computer.

2. Game Mechanics

• The game captures video input from the webcam and processes each frame to detect hand gestures.
• Mediapipe's Hand Landmarker identifies 21 key landmarks on the hand, which are analyzed to classify the gesture as "Rock" (closed fist), "Paper" (open hand), or "Scissors" (index and middle fingers extended).
• The computer randomly selects its move from the three options.
• The result is displayed on the screen, and the score is updated accordingly:
  • Rock beats Scissors
  • Scissors beats Paper
  • Paper beats Rock
  • Same gestures result in a tie.

3. Implementation Steps

1. Setup:

   • Initialize the webcam using OpenCV (cv2.VideoCapture).
   • Configure Mediapipe's Hands model to detect hand landmarks with a minimum detection confidence.

2. Hand Gesture Detection:

   • Convert each frame from BGR (OpenCV format) to RGB for Mediapipe processing.
   • Use Mediapipe to detect hand landmarks and draw them on the frame for visualization.
   • Analyze landmark positions (e.g., finger tips vs. joints) to determine the gesture:
     • Rock: All fingers closed.
     • Paper: All fingers extended.
     • Scissors: Index and middle fingers extended, others closed.

3. Game Logic:

   • Compare the player's gesture with the computer's random move.
   • Display the result (Win, Lose, or Tie) and update the score on the screen using OpenCV's text rendering.

4. User Interaction:

   • Press 'q' to quit the game.
   • Move your hand in and out of the frame to start a new round.

4. Requirements

• Python 3.x
• OpenCV (pip install opencv-python)
• Mediapipe (pip install mediapipe)
• NumPy (pip install numpy)

5. Installation

1. Clone the repository:

   git clone https://github.com/phamkiet000/Rock_Paper_Scissor.git
   cd Rock_Paper_Scissor