Python Computer Vision - AI Gaming Health Bar Monitor Tutorial: Part 2 Processes & Threading

Introduction

In this tutorial, you'll learn how to enhance your AI gaming health bar monitor by implementing processes and threading in Python. This guide will help you encapsulate your code in a class, create a command-line interface (CLI) for controlling image capture, and display frames per second (FPS) in real-time. These improvements will not only optimize your application's performance but also add a polished look with colorful terminal output.

Step 1: Create a Class for Your Application

Encapsulating your code in a class helps organize functionality and promotes reusability.

1. Define the Class:

   • Create a class named HealthBarMonitor.
   • Initialize necessary attributes such as FPS and the status of the image capture process.

   class HealthBarMonitor:
       def __init__(self):
           self.fps = 0
           self.is_capturing = False
   

2. Implement Methods:

   • Create methods for starting and stopping image capture.
   • Include a method for processing images.

Step 2: Set Up Processes for Parallel Execution

Using processes allows your application to perform multiple tasks simultaneously, improving efficiency.

1. Import Required Libraries:

   • Use the multiprocessing library to manage processes.

   from multiprocessing import Process
   

2. Define the Image Capture Process:

   • Implement a method that starts a new process for image capture.

   def start_capture(self):
       self.is_capturing = True
       process = Process(target=self.capture_images)
       process.start()
   

3. Handle Process Termination:

   • Ensure that your program can gracefully stop the image capture process.

   def stop_capture(self):
       self.is_capturing = False
       # Add logic to terminate the process if necessary
   

Step 3: Create a Command-Line Interface

A CLI will allow users to control the image capture process easily.

1. Set Up Basic CLI:

   • Use the argparse library to manage command-line arguments.

   import argparse
   
   parser = argparse.ArgumentParser(description="Health Bar Monitor CLI")
   parser.add_argument('--start', action='store_true', help='Start image capture')
   parser.add_argument('--stop', action='store_true', help='Stop image capture')
   args = parser.parse_args()
   

2. Link CLI Commands to Class Methods:

   • Based on user input, call the appropriate methods to start or stop the capture.

   if args.start:
       monitor.start_capture()
   elif args.stop:
       monitor.stop_capture()
   

Step 4: Display FPS in Real-Time

Monitoring the FPS helps you understand the performance of your application.

1. Calculate and Display FPS:

   • Implement a method to calculate FPS based on the time taken for image processing.

   import time
   
   def calculate_fps(self):
       start_time = time.time()
       frame_count = 0
   
       while self.is_capturing:
           frame_count += 1
           elapsed_time = time.time() - start_time
           if elapsed_time > 1:
               self.fps = frame_count / elapsed_time
               print(f"FPS: {self.fps}")
               start_time = time.time()
               frame_count = 0
   

Step 5: Add Color to Terminal Output

Enhancing your terminal output with color can provide a better user experience.

1. Use ANSI Escape Codes:

   • Implement basic color formatting for terminal messages.

   class Colors:
       HEADER = '\033[95m'
       OKBLUE = '\033[94m'
       OKGREEN = '\033[92m'
       WARNING = '\033[93m'
       FAIL = '\033[91m'
       ENDC = '\033[0m'
   
   print(f"{Colors.OKGREEN}Capture started...{Colors.ENDC}")
   

Conclusion

In this tutorial, you learned how to structure your Python code for a health bar monitor using class encapsulation, processes, and threading. You also created a CLI for user interaction and implemented real-time FPS monitoring along with colorful terminal output. As a next step, consider refining your image processing methods or integrating additional features to enhance your application's functionality. Keep experimenting with Python's capabilities to further improve your projects!