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#pyresearch 📌 Tutorial on Python Face Mesh (python OpenCV & MediaPipe package). In this video, we will do face detection and we will add face mesh to our face detection using OpenCV and MediaPipe package in a python programming language with StreamLit. MediaPipe Face Mesh is a solution that estimates 468 3D face landmarks in real-time even on mobile devices. It employs machine learning (ML) to infer the 3D facial surface, requiring only a single camera input without the need for a dedicated depth sensor. Utilizing lightweight model architectures together with GPU acceleration throughout the pipeline, the solution delivers real-time performance critical for live experiences. Please let me know your valuable feedback on the video by means of comments. Please like and share the video. Do not forget to subscribe to my channel for more educational videos. Any type of problem you can comment down. Want more education? Connect with me here: Twitter: / noorkhokhar10 Github:https://github.com/noorkhokhar99 Subscribe: / @pyresearch Organizations: / pyresearch Youtube: / pyresearch Related searches streamlit-webrtc streamlit yolov5 streamlit face recognition streamlit webcam object detection using streamlit webrtc computer vision yolor tutorial streamlit video #MediaPipe #FaceMesh #facedetection #computervision @Google @GoogleDevelopers @LearnOpenCV #computervision #trews #trending #trendingshorts #trend #travel #new #yolov7vsmediapipe #python #tags Search tags Python Face Detection and Face Mesh (python OpenCV & MediaPipe package) Face Mesh In Python | MediaPipe Series Detect 468 Face Landmarks in Real-time | OpenCV Python | Computer Vision Facial Landmarks Detection | with Opencv, Mediapipe and Python Face Detection, Face Mesh, OpenPose, Holisitic, Hand Detection Using MediaPipe On Live Stream Video Face Mesh using MediaPipe and OpenCV Custom Face Mesh Mediapipe tutorial | Landmarks AI Face Body and Hand Pose Detection with Python and Mediapipe