Unlock the world of facial recognition! In this comprehensive tutorial, I guide you through the process of building a "Python Face Detective" tool. We'll be using two industry-standard libraries: OpenCV for real-time detection and Face_Recognition for identifying and comparing individuals.
I walk you through the entire coding process in Jupyter Lab, starting from basic installations to advanced techniques like face encoding and calculating "face match percentages" using Euclidean distance. You'll learn how to handle color space conversions (BGR to RGB), draw bounding boxes around faces, and troubleshoot common issues like accessory interference (hijabs or glasses) and side-view detection limits.
Check the script on my Patreon:
https://www.patreon.com/posts/158217968
Original YouTube Tutorial: https://youtu.be/SycAW1ScYAE
Connected Videos in this Series:
* How to Install Python & Set Environment Variables:
https://www.dailymotion.com/video/xa8ony2
* How to Install Jupyter Lab (Jupyter Notebook) :
https://www.dailymotion.com/video/xa9nxf8
Source/Model Resources:
* Face_Recognition Library (Dlib-based): https://github.com/ageitgey/face_recognition
* OpenCV Python Documentation: https://opencv.org/
Video Details:
* Original Publish Date: April 24, 2024
* Focus: Python / OpenCV / Facial Recognition / Computer Vision
* Test Environment: Python 3.9 on Windows 11
Follow lordcaocao2025 on Dailymotion for more deep dives into computer vision, AI-driven automation, and technical Python tutorials!
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Connect with me:
📺 YouTube: https://www.youtube.com/@CaoCao2025
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💎 Patreon: https://www.patreon.com/cw/Caocao2025
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