Absolutely 👍 Here’s a professional and ATS-friendly README.md for your Face Recognition project — written in clean Markdown format, ready to upload directly to your GitHub repository (Face_Recognition).

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# 👤 Face Recognition Web Application

## 📌 Overview
The **Face Recognition Web App** is a Python-based application built with **Flask** and **OpenCV** that identifies and recognizes human faces from uploaded images.  
It leverages **deep learning-based facial recognition algorithms** to achieve over **95% accuracy** in matching and identifying faces.  
The project features a responsive and user-friendly web interface and can even run seamlessly on **mobile browsers** for cross-platform accessibility.

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## 🧠 Features
- 🧍 Detect and recognize faces from uploaded images  
- ⚡ High accuracy using deep learning-based facial feature extraction  
- 🌐 Built with Flask for lightweight web deployment  
- 🖼️ Interactive and responsive frontend using HTML, CSS, and JavaScript  
- 📱 Compatible with both desktop and mobile browsers  
- 🗂️ Organized file handling and image preprocessing pipeline  
- 🔁 Version control and collaboration managed via GitHub  

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## 🧰 Tech Stack

| Category | Technologies |
|-----------|---------------|
| **Programming Language** | Python |
| **Framework** | Flask |
| **Libraries** | OpenCV, NumPy, face_recognition |
| **Frontend** | HTML5, CSS3, JavaScript |
| **Version Control** | Git, GitHub |
| **Deployment** | Localhost / Mobile Browser |

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## ⚙️ Installation & Setup

### 1. Clone the Repository
```bash
git clone https://github.com/7Lion10/Face_Recognition.git
cd Face_Recognition

2. Create a Virtual Environment (optional but recommended)

python -m venv venv
venv\Scripts\activate   # On Windows
# or
source venv/bin/activate   # On macOS/Linux

3. Install Dependencies

pip install -r requirements.txt

4. Run the Application

python app.py

5. Access the Web App

Open your browser and go to: 👉 http://127.0.0.1:5000/

You can now upload an image and test face recognition directly from your PC or mobile device!

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📁 Project Structure

Face_Recognition/
│
├── static/
│   ├── css/
│   ├── js/
│   └── uploads/
│
├── templates/
│   ├── index.html
│   └── result.html
│
├── app.py
├── requirements.txt
└── README.md

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🚀 Future Enhancements

• ✅ Integrate database to store user faces and recognition history
• ✅ Deploy on a cloud platform (e.g., AWS, Render, or Heroku)
• ✅ Implement authentication for secure access

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🧾 Key Learnings

• Hands-on experience with Flask web development and REST APIs
• Applied computer vision and deep learning concepts using OpenCV
• Enhanced understanding of frontend-backend integration
• Optimized the app for mobile compatibility

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👨‍💻 Author

Sudeep Sandeep Puskar 📍 Hubli, India 🎓 MCA Student at MIT Manipal 🔗 GitHub Profile

Would you like me to also create a requirements.txt file (with all the correct Python dependencies like Flask, OpenCV, face_recognition, etc.) to go with this README?