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---
title: Pneumonia Detection System
emoji: 🩺
colorFrom: blue
colorTo: green
sdk: gradio
sdk_version: "3.1.4"
app_file: app.py
pinned: false
---
# Pneumonia Detection System
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)
## 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
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