https://github.com/anubagre/humanposeestimation
This is a real-time pose estimation project that detects 33 human body landmarks in images, videos, and live webcam streams. Built using MediaPipe, OpenCV, and Streamlit, this project provides an interactive and efficient way to analyze human movements using Blaze Pose detection method.
https://github.com/anubagre/humanposeestimation
blazepose humanposeestimation mediapipe opencv python streamlit streamlit-webapp
Last synced: 2 months ago
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This is a real-time pose estimation project that detects 33 human body landmarks in images, videos, and live webcam streams. Built using MediaPipe, OpenCV, and Streamlit, this project provides an interactive and efficient way to analyze human movements using Blaze Pose detection method.
- Host: GitHub
- URL: https://github.com/anubagre/humanposeestimation
- Owner: anubagre
- Created: 2025-01-29T09:00:30.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-01-29T11:00:27.000Z (over 1 year ago)
- Last Synced: 2025-03-24T11:14:07.334Z (about 1 year ago)
- Topics: blazepose, humanposeestimation, mediapipe, opencv, python, streamlit, streamlit-webapp
- Language: Python
- Homepage:
- Size: 8.99 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Human Pose Detection using MediaPipe
This project detects **human poses** in **images, videos, and live webcam streams** using **MediaPipe** that makes use of **Blaze Pose** detection method and is deployed with **Streamlit**.
---
## 📌 Features
✅ Detects **33 body landmarks** using **BlazePose**
✅ Works on **images, videos, and live webcam streams**
✅ **Streamlit UI** for easy interaction
✅ Real-time **pose tracking** with OpenCV
✅ Simple deployment & lightweight inference
---
## 🛠️ Files Structure
📂 Human-Pose-Detection │── 📂 Images/ # Stores sample images │── 📂 Videos/ # Stores sample videos │── 📜 HME_live.py # Pose detection on live webcam feed │── 📜 HME_onimage.py # Pose detection on images │── 📜 HME_onvid.py # Pose detection on videos │── 📜 app.py # Streamlit app to run the project │── 📜 requirements.txt # Required dependencies │── 📜 README.md # Project documentation
---
## ⚙️ Installation & Setup
🔹 **1. Clone the Repository**
git clone [https://github.com/your-repo/Human-Pose-Detection.git](https://github.com/anubagre/HumanPoseEstimation.git)
cd Human-Pose-Detection
🔹 **2. Install Dependencies**
pip install -r requirements.txt
🔹 **3. Run the Streamlit App**
streamlit run app.py
---
## 📷 How It Works
🔹 BlazePose is used for real-time pose detection.
🔹 OpenCV processes frames from images/videos/webcam.
🔹 Streamlit provides an interactive UI for users.
---
## 🛠️ Future Enhancements
🚀 Add pose classification for exercises (e.g., Yoga, Workouts)
🚀 Deploy as a Web App
🚀 Integrate gesture recognition