Mediapipe hand landmarks detection
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mediapipe is an open-source framework for building multimodal applied machine learning pipelines. one of the popular features of mediapipe is its hand tracking and hand landmarks detection functionality, which can be used to accurately detect and track hand landmarks in real-time. hand landmarks detection can be useful in applications such as gesture recognition, sign language translation, and virtual reality interactions.
here is a step-by-step tutorial on how to use mediapipe for hand landmarks detection:
1. install mediapipe:
you can install mediapipe using pip:
2. import necessary libraries:
3. create a `hand` object from the `mp.solutions` module:
4. read an image or video frame and convert it to rgb:
5. process the image using the `hands` object to detect hand landmarks:
6. iterate over the detected hands and landmarks to extract the coordinates:
7. display the image with the detected hand landmarks:
8. release the `hands` object after use:
this is a basic example of using mediapipe for hand landmarks detection. you can further customize the code to suit your specific application needs, such as integrating it into a real-time video stream or adding additional processing steps.
remember to refer to the official mediapipe documentation for more advanced features and customization options.
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