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Designed and implemented a posture corrector that delivers real-time feedback on user posture, achieving an improvement of 32% in posture alignment. • Leveraged Mediapipe for precise real-time detection of 32 key human body joints. Established precise joint angle threshold to further refine posture correction, tailored to specific exercises.
Knee bend exercise detector that counts the successful rep count only if the user bends the knee for more than 8 seconds by using Mediapipe and OpenCV . The condition for the knee to be in a bent stage is that the angle between the hip, knee, and ankle should be smaller than 140 degree.
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.
The SQUAT-SHOULDER-AND-BICEP-DETECTOR is an innovative application developed to assist users in monitoring their exercise form, specifically focusing on squats, shoulder exercises, and bicep curls. This project utilizes Mediapipe, a versatile library in Python, to detect and analyze human poses and movements accurately
Исходные файлы приложения "Трекинг упражнений", разработанного для курсовой работы по курсу 01.03.04 - "Методы искуственного интеллекта", кафедры КИК, НИТУ МИСиС, 2021-2022 уч. год.
Uses Mediapipe to extract key joints and the angle between these joints is analyzed to give real-time feedback about a user's posture while performing an exercise, namely bicep curls, plank and push ups.