REPSY -The Ai gym
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REPSY - AI Gym Trainer Problem Statement REPSY addresses several common challenges faced by individuals pursuing fitness goals: Difficulty in Tracking Progress: Users often struggle to monitor their progress effectively. REPSY integrates with wearable technology and tracks achievements, making it ...learn more
Project status: Published/In Market
Intel Technologies
Intel® Core™ Processors
Overview / Usage
Problem Statement REPSY addresses several common challenges faced by individuals pursuing fitness goals:
Difficulty in Tracking Progress: Users often struggle to monitor their progress effectively. REPSY integrates with wearable technology and tracks achievements, making it easier for users to see their improvements. Inaccessibility of Professional Guidance: Many users lack access to professional trainers. REPSY acts as a virtual trainer, providing guidance, motivation, and support anytime and anywhere. Lack of Inclusivity: Fitness solutions are not always inclusive. REPSY ensures that fitness is accessible to a broader range of people, accommodating various needs and capabilities. Proposed Solution REPSY is an AI/ML-based fitness trainer that utilizes OpenCV and pose estimation to deliver the following featur
Methodology / Approach
Exercise Repetition Counting: Automatically counts the number of repetitions performed during exercises. Technique Evaluation: Measures angles to assess exercise technique and ensure correct form. Form Checking: Provides feedback on the user’s exercise form to prevent injuries and improve effectiveness. Abstract REPSY is an AI-driven gym instructor leveraging TensorFlow and MediaPipe to perform tasks such as:
Pose Recognition: Instantly recognizes and analyzes the user's pose. Custom Diet Plans: Generates personalized diet plans based on user data. Tailored Workout Routines: Creates workout routines tailored to individual fitness goals and progress. Form Feedback: Offers real-time feedback on exercise form. Progress Monitoring: Keeps track of user progress and achievements. The system directs users through exercises, refines techniques, monitors advancements, and maintains enthusiasm. REPSY features an interactive user interface (UI) developed using HTML, CSS, and JavaScript.
Technologies Used
Tech Stack Frontend:
HTML CSS JavaScript Backend:
Flask (for serving the ML model) UI/UX:
Designed using Figma AI/ML:
TensorFlow (for ML model) MediaPipe (for pose estimation) OpenCV (for video processing)