based on mediapipe human Estimation project for pytorch, provide function(face_mesh,iris,pose,hand)

A demo showing how to use dlib and eos to fit a face mesh and project its 3d points as 2d on an image.

This project provides a data set with bounding boxes, body poses, 3D face meshes & captions of people from our LAION-2.2B. Additionally it provides clusters based on the poses and face meshes and pose-related captions based on these cluster assignments.

React PD-Meter App (measures distance between pupils) with MediaPipe Face Mesh - internship project (2023)

In this project, I am creating a facial mesh using opencv and mediapipe. It can detect a face even with a face mask.

A Qt project which build a face mesh with olny one picture

in this project build Face Mesh using python ( opencv_python , Mediapipe )

PennDesign RA project based on WebGL & Three.js - expand half-edge to half-face to find cells in a given .obj mesh

This ray tracer builds from my previous ray tracer (https://github.com/nishantb15/Ray-Tracer---Part-1) which implemented simple shapes, hard shadows, Phong Reflection from a point light source, Multi-Jittered Sampling using n-rooks strategy (Anti-aliasing) and Orthographic and Perspective projection with a moveable camera. This ray tracer adds a Bounding Volume Hierarchy (BVH) which is an accelerated structure, in this case, used to generate an image containing 100,000 spheres which would take days to render without a BVH. More information about the BVH is contained in the BVHTable.pdf file. Support is also included to read a .obj file and import a triangular mesh into the scene. The mesh can then be shaded using per-vertex normals as opposed to per-face (1 normal per face). The pictures generated using BVH are generated using 1 for the number of samples in multi-jittered sampling (essentially no anti-aliasing) and no shadows to save cost. The purpose of this project was to test the efficiency of the BVH in generating an enormous amount of spheres and triangles. Part 3 Can be found at: https://github.com/nishantb15/Ray-Tracer-Part-3-Reflection-Refraction-And-Area-Lights

This project utilizes MediaPipe and OpenCV to perform real-time face mesh detection using a webcam feed. The program captures video frames and processes them using the MediaPipe Face Mesh module to detect facial landmarks and contours.

A collection of advanced computer vision projects using OpenCV and MediaPipe for real-time Face Detection, Face Mesh, Hand Tracking, Pose Estimation, and Image Processing techniques.

This is a project reconstructing 3D face mesh from related RGB image

This Project is a face mesh project and extensively uses opencv-python and mediapipe. This is the perfect way to learn image processing. NO GPU required! Just the CPU would work. Also can track all 468 points on your face. The IDs of each point can be inferred from the mediapipe's page. So what are you waiting for> Code your masks now! Happy Coding

Face Tracker with Eye Detection is a Python computer vision project using OpenCV and MediaPipe Face Mesh to detect and track multiple faces in real time through a webcam. It draws facial mesh connections and highlights eye landmarks, demonstrating real-time AI-based facial tracking and visualization.

Unreal Multiplayer Course - Section 4 - Krazy Karts In follow up to our hugely successful Complete Unreal Engine Developer course we bring you Unreal Multiplayer Mastery - as on featured on Epic's UE4 blog. In this section make your games feel responsive no matter what network conditions your players face. Understand and explain concepts such as lag. Devise mechanism to compensate for lag in your games. You're welcome to download, fork or do whatever else legal with all the files! The real value is in our huge, high-quality online tutorials that accompany this repo. You can check out the course here: Unreal Multiplayer Mastery 0 Introduction to Krazy Karts We overview the sections topics. 1 Creating A Go-Kart Pawn Create the project. Create a pawn. Setup GameMode Spawning. Setup Camera. Attach throttle controls. 2 Understanding Forces And Movement Revision of forces in physics. Calculating movement from force. Providing the driving force. 3 Blocking Movement Without Physics Setting up collision volumes. Sweeping with AddActorWorldOffset. Resetting velocity on collision. Refactoring the Tick function. 4 Rotations With Quaternions Angle axis rotations with FQuat. Adding rotations actors. Rotating our velocity. 5 Simulating Air Resistance Understanding air resistance. Getting the "speed". Calculating force due to air resistance. 6 Simulating Rolling Resistance What is rolling resistance? Finding the gravity in Unreal. Implementing rolling resistance. Example rolling resistance coeffients. 7 Steering And Turning Circles Why we get turning circles. Calculating our rotation geometry. Correcting steering behaviour. 8 Server Functions & Cheat Protection How to change state from the client. Introduction to RPC server functions. What is validation? Implementing validation for input. 9 AutonomousProxy vs SimulatedProxy What are Actor roles? Investigating the network roles. Updating the AutonomousProxy. 10 Sources Of Simulation Error How simulation error effect our game. Overview the different sources of error. Investigate approaches to eliminating them. 11 Replicating Variables From The Server Overview of property replication. Replicating the actor position. Setting and reading the property. Replicating the actor rotation. 12 Triggering Code On Replication Deep dive on property replication. Setting the network update interval. Notify on replicate. Simulate between updates. 13 Smooth Simulated Proxies Replicating velocity. Why is movement jerky? Replicating control input to SimulatedProxy. 14 Simulating Lag And Packet Loss What is lag? Simulating lag and packet loss. Why does lag cause glitching? 15 Replay Autonomous Moves Why do we reset when accelerating? Keeping AutonomousProxy ahead of the Server. What information needs to be sent to the server. Compare our different simulation approaches. 16 Planning Client-Side Prediction Pseudocode for client prediction. Adding structs for synchronisation. 17 Replicating Structs What do we have already? Replicating state via a struct. Sending the Move struct via RPC. 18 Simulating A Move The SimulateMove signature. Updating the canonical state. Implement SimulateMove. 19 Unacknowledged Move Queue TArray for the Move queue. Tidying the move creation code. Printing the queue length. Removing acknowledged moves. 20 Simulating Unacknowledged Moves Simulate all moves. Testing for smoothness. How can we still make it glitch? 21 Fixing SimulatedProxy Prediction Ensuring the Server simulates once. Local prediction on the client. Making smoother predictions. 22 Refactoring Into Components Red-Green-Refactor process. How to spot your "code smells". Identifying a suitable refactor. Planning our refactor. 23 Extracting A Movement Component Create and name the component. Move member declarations across. Move function implementations. Fix build errors. 24 Extracting A Replication Component Creating the component. Enable replication. Move member declarations across. Move function implementations. Fix build errors. 25 Decoupling Movement & Replication What happens if we disable the replicator? Allow the Movement Component to tick. Getting the information to replicate. 26 Linear Interpolation For Position How does linear interpolation work? Overview of client interpolation. Pseudocode for client interpolation. 27 FMath::Lerp For Client Interpolation Ensure movement replication is off. Updating the time variables. FMath::Lerp vs FMath::LerpStable. Implementing the pseudocode. 28 FQuat::Slerp For Rotation Slerp vs Lerp. Store tranform instead of location. Implementing Slerped location. 29 Hermite Cubic Spline Interpolation Understanding jarring movement. How velocity can help or hinder. A brief overview of polynomials. Introducing the Hermite Cubic Spline. 30 FMath::CubicInterp For Velocity Slopes, derivatives and velocity. Using CubicInterp for location. Using CubicInterpDerivative for velocity. 31 Refactoring With Structs Assessing the existing code. Creating a plain C++ struct. Pulling out methods. 32 Client Interpolation Mesh Offset Understanding mesh offseting. Set up the mesh offset root component. Manipulating the offset instead. 33 Advanced Cheat Protection Bounding the inputs. Stressing our DeltaTime. Tracking simulation time. 99 End Of Course Wrap-up Congratulations on making it this far! Why we don't cover dedicated server. How to continue practicing your skills

A project to implement the work of "High-Quality Single-Shot Capture of Facial Geometry" for creating High Quality Face Mesh

Computer vision project for extracting numerical facial features from images using MediaPipe Face Mesh.

This Project Detects and Marks the Face Mesh also used in making AR Emojis, And This Projects Uses Camera!

Hand Tracking, Pose Estimation, Face Detection and Face Mesh basics and module projects are included in this repository. Also, there will be related projects based on these modules

In this Project Holistic Detection, it detect Left and Right Hand, Face Mesh, and Pose Detection using Libraries Opencv and Mediapipe in Python.

This repository contains a Python project that can be used to detect facial emotions. The project uses the MediaPipe face mesh API to detect face landmarks, and a simple multilayer perceptron to recognize facial emotions from the detected landmarks.

This project allows you to control your computer mouse using your eyes and head movements. By leveraging MediaPipe Face Mesh, it tracks facial landmarks in real-time and enables hands-free interaction with your PC.

**Meshify** is a Python application for real-time face mesh detection using OpenCV, Mediapipe, and CVZone. This tool provides accurate facial landmark mapping, making it easy to customize and integrate into various projects. 🐙💻

Modular computer vision project using OpenCV and MediaPipe. Includes hand tracking, pose estimation, and face mesh detection modules, plus a universal wrapper to run them individually or together. Supports webcam and video input for real-time CV experimentation.

This is a hackathon project(for Gemini3 hackathon|Google DeepMind)The ultimate AI career copilot powered by Google Gemini 3 Pro. Features multimodal Video Interview Coaching with real-time face mesh analysis, smart Resume Review, and tailored Cover Letter generation. 🚀

This project uses OpenCV and MediaPipe to detect facial landmarks and estimate head pose in real-time. The extracted data is processed by a neural network model to determine if a person is attentive. Features include real-time face mesh detection, pose estimation, and attention analysis.

This repository contains code for a teeth detection project using MediaPipe Face Mesh. The code utilizes facial landmark detection to determine whether the teeth are visible in images. It includes functions for image resizing, tooth detection, and supports image inputs from either a local folder or URLs.

This project performs real-time facial analysis using MediaPipe FaceMesh and OpenCV. It detects: Head pose (Up, Down, Left, Right, Forward) Mouth state (Closed, Slightly Open, Wide Open) Face mesh visualization with annotated landmarks The system runs on a standard webcam and processes frames in real time.

Majik Blender Edu is a submission integrity and student activity tracking addon for Blender designed to help educators verify a student's work. It records Blender-specific actions such as editing meshes, adding modifiers, importing assets, and scene statistics (vertices, faces, etc.), ensuring that submitted projects are authentic and untampered.

This project is a Drowsiness Detection Dashboard that uses computer vision and AI to monitor a driver’s alertness in real time. It employs OpenCV and MediaPipe Face Mesh to analyze eye and mouth movements, calculating EAR (Eye Aspect Ratio) and MAR (Mouth Aspect Ratio) to detect signs of sleepiness or yawning.