Traditional methods of geospatial analysis often rely on manual identification and mapping of objects within geographical regions. However, these methods are time-consuming, labor-intensive, and prone to errors. Moreover, they may lack the scalability required for large-scale analyses. Therefore, there is a need for automated solutions that can accurately detect and locate objects within geographic areas, enabling efficient and scalable geospatial analysis.
Our project addresses significant challenges through the development of an automated system. This system combines advanced object detection algorithms with precise geographic coordinate calculations. The integration of these components aims to achieve several key objectives:
Firstly, leveraging state-of-the-art object detection algorithms like YOLO (You Only Look Once), our system automatically identifies and locates objects within satellite or aerial imagery.
Secondly, we are developing algorithms to accurately calculate the geographic coordinates (latitude and longitude) of detected objects in relation to a specified bounding polygon.
Lastly, integrating the results of object detection with calculated geographic coordinates forms a comprehensive geospatial dataset. This dataset allows for the visualization of detected objects and their precise geographic locations on maps. Such visual representations facilitate further analysis and interpretation of the data.
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.
In this section, we outline the methodology employed for deriving geographic coordinates from input data within the InferenceVision framework. This methodological approach combines advanced techniques in satellite image analysis, object detection, and geographic coordinate calculation to enable precise geospatial analysis and visualization.
Automation and Efficiency: By automating the process of object detection and geographic coordinate calculation, our system significantly reduces the time and effort required for geospatial analysis, thereby enhancing efficiency and scalability.
Accuracy and Precision: Through the integration of advanced algorithms, our system ensures high accuracy and precision in object detection and geographic coordinate calculation, leading to reliable and trustworthy results.
Versatility and Adaptability: The developed system is versatile and adaptable to various applications, including environmental monitoring, urban planning, agriculture, and disaster response. It provides researchers and practitioners with a powerful tool for analyzing geospatial data in diverse contexts.
git clone https://github.com/doguilmak/InferenceVision.gitcd InferenceVisionpip install -r requirements.txtfrom inference_vision import InferenceVisioninference = InferenceVision()inference.process_image()