The Aerial Scan Sentinel is a machine learning (ML) project aimed at developing a system for assessing landing safety on Earth's surface using satellite imagery and computational methods. The project's objective is to determine suitable landing spots for drones, helicopters, or similar aerial vehicles by analyzing terrain features.
- Analyzes satellite imagery to assess landing safety.
- Clone the repository:
git clone https://github.com/your-username/aerial-landing-safety.git- Install the required dependencies:
pip install -r requirements.txt-
Prepare your aerial images for assessment.
-
Run the main script to assess landing safety:
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The script will output the input image with safe landing spots labeled.
Contributions are welcome! If you'd like to contribute to this project, please follow these steps:
- Fork the repository.
- Create a new branch (
git checkout -b feature/your-feature). - Make your changes.
- Commit your changes (
git commit -am 'Add new feature'). - Push to the branch (
git push origin feature/your-feature). - Create a new pull request.
This project is licensed under the MIT License.
For questions or inquiries, please contact one of our members:
👉🏼 arindal1
👉🏼 ShBack
👉🏼 trisha-RC
👉🏼 Shubhayan29
👉🏼 Immortal10
-> Project Outline
-> Google Collab
Note
This project was developed by 5 computer science students as part of their semester exams. While efforts have been made to ensure its functionality and accuracy, it might not be perfectly polished. We plan to continue improving it over time.