🏃‍♂️ AI Running Coach

A live demo of AI Running Coach in action! Using advanced pose estimation with Google MediaPipe, this tool analyzes running form in real-time, classifies running styles, and provides useful insights to help runners optimize their technique.

🔗 Try it live: AI Running Coach

🎯 Key Features

✅ Real-time body tracking Detects 33+ key body points to analyze posture and movement.

✅ Running style classification Categorizes runners into different styles based on form and efficiency (Eco Sprinter, Quick Stepper, etc.)

✅ Insights on running economy parameters Provides feedback and data-analysis

🖼️ Project Dashboard and Snapshot

🛠️ Tech Stack

• Pose Estimation: Google MediaPipe
• Languages: Python
• Frameworks: Streamlit, OpenCV, NumPy
• Data Visualization: Matplotlib, Pandas
• Deployment: Streamlit Cloud

📸 Live Demo

🎥 Watch AI Running Coach in Action! 👉 YouTube Demo

🔧 Installation & Running the Code

🔗 Try AI Running Coach live: https://airunningcoach.streamlit.app/

-> Or follow the 3 steps below to run it locally.

1️⃣ Clone the Repository

git clone https://github.com/yourusername/ai_running_coach.git
cd ai_running_coach

2️⃣ Install Dependencies

pip install -r requirements.txt

3️⃣ Run the App with Streamlit

streamlit run app.py