In this video, we will build a Python script I created that uses OpenCV, a powerful computer vision library, to detect when I take a drink of coffee from my mug in real-time. The script harnesses the capabilities of computer vision to analyze video frames captured from my camera.
Throughout the video, you'll see how the script detects my face in each frame and focuses specifically on the mouth region. By counting the number of white pixels in the mouth area and comparing it to a predefined threshold, the script can determine if I am drinking coffee at any given moment.
Whenever the script detects that I am taking a sip of coffee, it instantly prints a message to the console and plays an audible sound notification to alert me. This real-time feedback allows me to keep track of my coffee consumption habits effortlessly.
The script remains active, continuously monitoring my actions until I press the 'q' key to quit the program. This video showcases the power of combining Python programming with computer vision techniques to create practical and interactive applications.
If you're interested in learning how to develop similar computer vision projects or want to explore the capabilities of OpenCV, this video is a great starting point. I provide step-by-step explanations of the code and demonstrate how you can adapt it to suit your own needs.
So, grab a mug of your favorite coffee, sit back, and join me as we dive into the world of real-time coffee drinking detection using Python and OpenCV!
Don't forget to like, share, and subscribe to my channel for more exciting videos on tech, future tech, AI and more. Leave a comment below if you have any questions or suggestions for future projects.
Automating My Life with Python | Using Computer Vision to detect how often I Drink Coffee
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