pascalx/pathloss-predictor

Pathloss App

A web application for predicting path loss using various machine learning models (ANN, CNN, DNN). The app provides a user-friendly interface for inputting parameters and visualizing results.

## Features

• —Predict path loss using pre-trained models (ANN, CNN, DNN)
• —Simple web interface for user input and result display
• —Model and data pre-processing handled automatically
• —Docker support for easy deployment

## Project Structure

 app.py                # Main Flask application
 Dockerfile            # Docker configuration
 requirements.txt      # Python dependencies
 models/               # Pre-trained models and preprocessor
 static/style.css      # Custom styles
 templates/            # HTML templates

## Getting Started

### Prerequisites

• —Python 3.8+
• —pip

### Installation

1. 1.Clone the repository:

	 git clone <repo-url>
	 cd pathloss-app

1. 1.Install dependencies:

	 pip install -r requirements.txt

1. 1.Run the application:

	 python app.py

1. 1.Open your browser and go to http://localhost:5000

### Docker

To run with Docker:

 docker build -t pathloss-app .
 docker run -p 5000:5000 pathloss-app

## Usage

• —Enter the required parameters in the web form.
• —Select the desired model (ANN, CNN, DNN).
• —View the predicted path loss and related results.

## File Descriptions

• —app.py: Main Flask application logic.
• —models/: Contains pre-trained models (.h5) and preprocessor (.pkl).
• —static/style.css: Custom CSS for the app.
• —templates/: HTML templates for UI.

## License

This project is licensed under the MIT License. See the LICENSE file for details.