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International Space Station Position Prediction Project

The goal of the project is to develop a system for predicting the position of the International Space Station (ISS) in geographical coordinate space. To achieve this goal, a set of tools and scripts has been prepared to collect data, train the model and visualize the actual and predicted position of the ISS.

Installation

  1. Clone the repository:

    git clone https://github.com/Dawidemm/iss-position-prediction
cd iss-position-prediction

  2. Python Version:

    This project is developed using Python version 3.10.13.

  3. Virtual Environment:

    It is recommended to use a virtual environment to manage dependencies and isolate the project environment.

  4. Install the project:

    After activating the virtual environment, navigate to the project directory and install the project using the following command:

    pip install .

Alternative Installation from Docker Hub

Alternatively, you can install and run the project using Docker. The project is available as a pre-built Docker container image on Docker Hub.

To pull the image from Docker Hub, use the following command:

docker pull dawidem/iss-position-prediction-project:v1.0

After pulling the image, you can run a container based on it using the following command:

docker run -it -p 3000:3000 dawidem/iss-position-prediction-project:v1.0 /bin/bash

Documentation

The docs folder contains documentation for the executable files that are part of this project.

1. generate_dataset.py

  • Description: The generate_dataset.py file contains a script for generating a dataset.
  • Instructions: To generate a dataset, run this script and provide the appropriate parameters.

2. train_pipeline.py

  • Description: The train_pipeline.py file contains a script for processing and training the model.
  • Instructions: To run the model training process, execute this script, providing the appropriate input data.

3. visualization.py

  • Description: The visualization.py file contains a script for visualizing data and results.
  • Instructions: Run this script to generate plots and visualizations of data.

4. app.py

  • Description: The app.py file contains a script for running the application.
  • Instructions: Run this script to start the application in interactive mode.

Real-time Visualization