19–22) and draw the circle to detected key points.This is a Computer vision package that makes its easy to run Image processing and AI functions. We loop over the hand landmarks (line no. If yes then we have to capture the landmarks of a user’s hands. We check if a user is showing his/her hand on a webcam or not (line no. 14) Once the hands get detected we move further with locating the key points (figure 1) and then highlighting the dots in the key point. Next, we detect hands in a frame with the help of a hand.process() method (line no. Over the years, the standard has now become RGB but OpenCV still maintains this “legacy” BGR order to ensure no existing code breaks.
The reason why we do this is that when OpenCV was first being developed many years ago the standard for reading an image was BGR order. Wait Jiten why do we convert our image to an RGB image? I have seen most of the tutorials and read most of the articles but no one really explains why we do this? But don’t worry I will explain you. We will convert the image (frame) captured by our webcam into RGB. 12 by cap.read() method provided by class VideoCapture(). We are reading the frames from our webcam on line no.
In this project, we are going to use Mediapipe’s Hands Landmark Model. Mediapipe offers lots of ML solutions APIs such as face detection, face mesh, iris, hands, pose, and there are a lot of them. Mediapipe is a machine learning framework developed by Google.
For hand and landmarks estimation we will use Mediapipe. Don’t worry if you don’t know how to work with the OpenCV library. OpenCV will help us to access the webcam. Guess what? we are going to use this library in our project. Let’s get startedīelieve me or not, if you’re working in the field of computer vision you have definitely used the OpenCV library or if you’re a beginner you’ve at least come across this library. In this article, we will create our real-time hand tracking module to detect our hands and estimate the landmarks. Well, tracking your hand is the first step you need to take to build one. Wouldn’t be great if you create one for yourself? How great would it be to make different things happen just by waving your hand in the air? This magic power can be compared to having your network of devices, just like Iron Man commanding his network of AI-enabled systems. How to make a Hand tracking module using Python
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