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This code is a Python script that demonstrates the use of the MediaPipe library to capture video from a webcam and perform pose detection, facial detection, and hand detection in real-time.

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Body-Language-Decoder

This code is a Python script that demonstrates the use of the MediaPipe library to capture video from a webcam and perform pose detection, facial detection, and hand detection in real-time. The project also allows capturing the detected landmarks and exporting them to a CSV file for further analysis.

Installation

To run this code, you need to install the following dependencies:

mediapipe opencv-python pandas scikit-learn You can install these dependencies using pip: code !pip install mediapipe opencv-python pandas scikit-learn

Usage

To use this code, simply run the Python script. The code will capture the webcam stream and start detecting the facial landmarks, hand gestures, and body poses in real-time. The detected landmarks will be displayed on the video stream as different colored dots connected by lines to form a skeleton.

To exit the code, press the "q" key.

The detected landmarks can also be captured and exported to a CSV file for further analysis. The exported CSV file will contain the x, y, and z coordinates of each detected landmark, as well as a visibility score.

License

This code is licensed under the MIT

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This code is a Python script that demonstrates the use of the MediaPipe library to capture video from a webcam and perform pose detection, facial detection, and hand detection in real-time.

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