Interview Buster is an AI-powered tool designed to help job seekers enhance their non-verbal communication skills. By leveraging advanced computer vision techniques, it provides personalized feedback on body language, including facial expressions, head posture, eye contact, hand gestures, and body poses, ultimately boosting interview success rates.
Real-time face mesh detection project using OpenCV and MediaPipe in Python, providing detailed 3D facial landmark tracking and visualization capabilities.
The app for the bachelor's thesis topic - "Real-time computer vision solution for Latvian sign language recognition".
The main objective of this project is to move the cursor through the eyeballs. Library used: OpenCV, MediaPipe, PyautoGUI Language used: Python
Gesture Recognition with Google MediaPipe in ROS
Zooting: 내 얼굴과 닮은 동물 가면을 쓰고 미팅하자! 동물상 가면 미팅 서비스 -🏆SSAFY 10기 공통프로젝트 최우수상(1등)
Face Scanner for OPAD 2024. Partnered work with NHS clinical practitioners, first steps in development of image segmentation application that scans and allocates the correctly sized NIV masks for pediatric care.
Detectors World... See the World Through Code. Build Computer Vision applications in easy and handy way.
Gaze tracking
2023-2 Medical Image Processing Project : Short-term Muscular Tic-Patients Detector : Half-Automated Extracted Model based Algorithms using Google MediaPipe to Analysis Tic Region of Interest
Using Mediapipe to create an OBJ of a face from a source image
Emotion based music recommender system
Trying different model,
A Driver conscious detection project that helps to improve driver awareness
Обнаружение точек лица, рук и всего тела с использованием DL алгоритмов
Computer keyboard controlled by eyes with speech synthesis for people with disabilities
Semester 2 mini project: Drowsiness Detection with EAR and Mediapipe
Facial detection is used to extract skin color, lipstick color, blush color, eyeshadow color, and foundation color. This feature can categorize your makeup and provide makeup recommendations based on user occasions. The feature is built using YOLO V8 for Object Detection, OpenCV, and Flask API in essence.
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