The provided code leverages the mediapipe library to detect and track body poses in real-time, either from camera feeds or video files.
This real-time pose detection extracts key landmarks on the body and visualizes them on the video feed. The program also calculates and displays the frames per second (FPS) to monitor performance.
Pose Detector Class
Organized for reusability and easier integration into other projects.
Detects body poses and visualizes the landmarks and their connections.
Real-time FPS Calculation
Allows for performance and processing speed monitoring.
Simple Script
A standalone version that reads a video feed and estimates body poses without the need for a class structure.
Prerequisites
Install the required libraries:
pip install opencv-python mediapipe
Execution
Run the scripts using:
python pose-module.py
or
python pose.py
Ensure you have a working camera or a valid video file path.
Adjust the cv2.VideoCapture('PoseVideos/3.mp4') parameter depending on which source you want to use.
Check for the availability of the video file before processing to avoid runtime errors.
This script is open-source and is licensed under the MIT License. For more information, consult the LICENSE file.