Updated `README.md`. Added project setup documentation

README.md

@@ -1,4 +1,114 @@
-# Pneumono_Detect
-link to the [CNN model](https://drive.google.com/file/d/1-4L-8HJ79W5k-0l8FchG4HH1SI2dLi2W/view?usp=sharing) 
+# Pneumonia Detection System
 
-link to the [Dataset](https://drive.google.com/drive/folders/1BhxsscDaVBamuyUv1HoyXsixeGvTWHt5?usp=sharing)
+A Flask-based web application that uses a fine-tuned VGG19 model to detect pneumonia from chest X-ray images.
+
+## Model Links
+- [CNN Model](https://drive.google.com/file/d/1-4L-8HJ79W5k-0l8FchG4HH1SI2dLi2W/view?usp=sharing)
+<!-- - [Dataset](https://drive.google.com/drive/folders/1BhxsscDaVBamuyUv1HoyXsixeGvTWHt5?usp=sharing) -->
+
+## Setup Instructions
+
+### Prerequisites
+- Python 3.8 or higher
+
+### Installation
+
+1. Clone the repository:
+
+```bash
+git clone https://github.com/yourusername/Pneumono_Detect.git
+cd Pneumono_Detect
+```
+
+2. Set up the environment:
+
+#### Windows:
+
+```bash
+setup.bat
+```
+
+#### Linux/Mac:
+
+```bash
+chmod +x setup.sh
+./setup.sh
+```
+
+### Activating the Environment
+
+#### Windows:
+
+```bash
+tf_test_env\Scripts\activate
+```
+
+#### Linux/Mac:
+
+```bash
+source tf_test_env/bin/activate
+```
+
+## Running the Application
+
+1. Ensure your virtual environment is activated
+2. Run the Flask application:
+
+```bash
+python app.py
+```
+3. Open a web browser and navigate to `http://localhost:5000`
+
+## Usage
+
+1. Upload a chest X-ray image through the web interface
+2. Click "Predict" to get the classification result
+3. View the prediction result and confidence score
+
+## Project Structure
+```
+Pneumono_Detect/
+├── app.py                  # Flask application
+├── requirements.txt        # Python dependencies
+├── setup.bat              # Windows setup script
+├── setup.sh               # Linux/Mac setup script
+├── static/
+│   └── uploads/           # Folder for uploaded images
+└── templates/
+    ├── index.html         # Upload page
+    └── result.html        # Results page
+```
+
+## Model Information
+- Architecture: VGG19 (fine-tuned)
+- Input Size: 128x128x3
+- Classes: NORMAL, PNEUMONIA
+- Confidence Threshold: 0.7
+
+## Dependencies
+- Flask 3.1.0
+- TensorFlow 2.12.0
+- Pillow 10.2.0
+- NumPy 1.23.5
+
+## License
+[Your chosen license]
+
+## Acknowledgments
+- Dataset source: [Add source]
+- Base VGG19 model: [Reference]
+```
+
+This README provides:
+1. Clear setup instructions for both Windows and Linux/Mac
+2. Project structure overview
+3. Usage instructions
+4. Model information
+5. Dependencies list
+6. Placeholders for license and acknowledgments
+
+Remember to:
+1. Replace `yourusername` with your actual GitHub username
+2. Add appropriate license information
+3. Fill in the acknowledgments section
+4. Update any specific details about your implementation