Face Recognition with MTCNN and OpenCV
Welcome to this tutorial where we explore real-time face recognition using the MTCNN (Multi-task Cascaded Convolutional Networks) algorithm and OpenCV in Python.
Project Overview
In this project, we use the MTCNN library to detect faces in a live video stream captured from a webcam. The detected faces are then outlined with rectangles, providing a simple yet effective real-time face recognition demonstration.
Dependencies
Python: [https://www.python.org/downloads/](https://www.python.org/downloads/)
OpenCV: [https://pypi.org/project/opencv-python/](https://pypi.org/project/opencv-python/)
MTCNN: [https://pypi.org/project/mtcnn/](https://pypi.org/project/mtcnn/)
How to Run the Project
1. Install Python, OpenCV, and MTCNN using the provided links.
2. Copy and paste the Python code from the GitHub repository (link below) into your preferred Python environment.
3. Run the script to start real-time face recognition.
Code Repository
Find the complete code on GitHub: [https://github.com/prakash-2001/face-detec...]
Adjusting Frame Rate
To adjust the frame rate of the video, modify the `target_fps` variable in the code. Be mindful of system performance when setting higher frame rates.
Credits
MTCNN Library: [https://github.com/ipazc/mtcnn](https://github.com/ipazc/mtcnn)
OpenCV Library: [https://opencv.org/]
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GitHub: [https://github.com/prakash-2001/]
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Thanks for watching! Happy coding! 👩💻🚀
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