360PathFinder is a real-time pathfinding algorithm designed specifically for 360-degree image analysis. It takes as input a panoramic image and identifies optimal paths from a given starting point to a designated destination within the image. By leveraging advanced image processing techniques and graph-based algorithms, 360PathFinder offers users a seamless and intuitive way to navigate through immersive visual environments.
My inspiration for 360PathFinder stemmed from the need for efficient pathfinding solutions in 360-degree environments. I was intrigued by the challenges posed in navigating complex spatial layouts captured in panoramic images and sought to develop a solution that could facilitate efficient route planning in such environments. The spark for this project ignited during the 418 Hackathon, where I encountered the problem statement addressing the complexities of pathfinding in immersive visual environments. I found the problem statement to be very interesting and saw it as an opportunity to delve into the realm of panoramic image analysis and develop a novel solution to address this challenge.
- Efficient pathfinding in 360-degree environments
- Real-time performance
- Support for dynamic route planning
- Integration of machine learning algorithms for obstacle detection
- Seamless integration with virtual reality, gaming, and architectural visualization applications
- Python
- OpenCV
- Image processing libraries
- Graph-based algorithms
- Object-oriented programming principles
To use 360PathFinder, simply provide a panoramic image as input along with the starting and destination points. The algorithm will then analyze the image and generate an optimal path from the start to the end point.
# Example usage
Just input hte image file location in the main and run the program
# Load panoramic image
image = "example_image.jpg"