Our project aims to address critical challenges in geospatial analysis by developing an advanced automated system. This system integrates state-of-the-art object detection algorithms with precise geographic coordinate calculations to achieve the following key objectives:

1. Automate Object Detection: By leveraging cutting-edge object detection algorithms like YOLO (You Only Look Once), our system identifies and localizes objects within high-resolution satellite or aerial imagery. This automation significantly reduces the time and effort required for manual object detection, ensuring scalability for large datasets.

2. Calculate Geographic Coordinates: Our project develops robust algorithms to accurately compute the geographic coordinates (latitude and longitude) of detected objects. These calculations are performed relative to a specified bounding polygon, converting pixel-based detections into precise geospatial data.

3. Integrate and Visualize Data: The results of object detection are seamlessly integrated with calculated geographic coordinates to create a comprehensive geospatial dataset. This dataset enables the visualization of detected objects and their exact geographic locations on interactive maps, providing actionable insights for further analysis.

Scientific Contribution: This approach not only streamlines the process of object identification and geographic referencing but also enhances the capability to derive insights from complex spatial data. By addressing limitations in traditional methods, our project enables efficient, accurate, and scalable geospatial analysis for diverse applications.