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Vihanga Anuththara
Vihanga Anuththara

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Visual Recognition with Pygame

#python #visualrecognition #programming #ai

Visual Recognition with Pygame

In this post, I will teach you how to build a simple car game that uses visual recognition in Python. This project is a great introduction to visual recognition concepts with Python, and it’s based on a simple game that demonstrates how to track hand movements using the camera.

I will use a few Python libraries for this project. These are the libraries I use:

  • OpenCV (cv2)

  • Pygame

  • MediaPipe

  • Random

You can customize or enhance this project however you want. You can also apply the concepts from this project to various other ideas. I hope this helps you grow your Python projects!

Project Structure 

- Car Game
    - main.py
    - requirements.txt
    - Assets
        - car.png
        - barrier.png
- venv
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Let's move on to the code for the project

  • First, you’ll need a Python virtual environment. Create one by running:

python3 -m venv venv

  • Then activate it: 
 source venv/bin/activate  # On MacOS/Linux
 venv\Scripts\activate     # On Windows
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  • Next, install the necessary libraries. You can either use pip install package for each one, or install all dependencies from the requirements.txt file with:

pip install -r requirements.txt

1. Import the required libraries 

 import cv2
 import mediapipe as mp
 import pygame
 import sys
 import random
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2. Set up MediaPipe for hand tracking

  • In this step, we initialize MediaPipe for hand tracking and set up the camera feed. 
 p_hands = mp.solutions.hands
 hands = p_hands.Hands(max_num_hands=1)
 mp_draw = mp.solutions.drawing_utils
 cap = cv2.VideoCapture(0)  # Access the webcam
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3. Set up the Pygame window

  • Now, we set up the game window using Pygame. 
 pygame.init()
 WIDTH, HEIGHT = 640, 480
 screen = pygame.display.set_mode((WIDTH, HEIGHT))
 pygame.display.set_caption("Car Game")
 clock = pygame.time.Clock()
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4. Define the game elements

  • You’ll need to define the game elements such as the car and the barriers. Here we specify their images and other properties, like position and speed. 
 car_img = pygame.image.load("Assets/car.png")
 car_rect = car_img.get_rect(center=(WIDTH // 2, HEIGHT - 50))
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 barrier_img = pygame.image.load("Assets/barrier.png")
 barriers = []
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5. Define functions

  • Define functions to update the game elements, such as the car’s movement and barrier spawning. You can also create a function for hand tracking to control the car’s movement.

6. The Game Loop

  • This is where everything comes together. The main loop constantly updates the screen, processes hand tracking, and updates the game elements.
    • You can use your own game loop as you like.

7. Running the game

  • Finally, call the game_loop() function to start the game. 
 if __name__ == "__main__":
     game_loop()
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This project gives you a basic understanding of how to implement visual recognition in Python and integrate it into an object-oriented project. It also demonstrates how you can control or automate tasks with visual recognition. In today’s tech landscape, automation is a significant field, and many industries are using visual recognition to improve their products and processes for the future.

Building this project has given me a new perspective on how to think outside the box when tackling different problems.

Thank you for reading this post! Do you have any experience with visual recognition or any project ideas that use visual recognition? Feel free to share your thoughts in the comments below.

Check out my GitHub portfolio here: vanu888

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