The realization that photographs alone lack descriptive context inspired us to bridge the gap between images and their unwritten stories. Our online app transforms photo interaction by allowing users to submit photos, define positions, and write descriptions, allowing them to extract the essence of cherished experiences. The program generates appropriate tags using Azure ML, improving discoverability. The profile page features an eye-catching Google Map with markers marking the locations of the images, constructing a narrative of personal trips.

The web app we built is a tool that improves the experience of engaging with photos. It enables users to submit images and connect them with accurate coordinates, allowing for a visual representation of the locations where the photos were shot. Users can also add context and storytelling aspects to their preserved moments by providing brief captions for their photographs. The program also makes use of Azure ML to produce relevant tags for the photos. Users can explore a charming Google Map on their profile page, which shows the exact locations where their images were collected, creating a rich tapestry of unique adventures and experiences.

Node.js was used for server-side development, and HTML, CSS, and JavaScript were used for the user interface. Passport.js was used for authentication, Azure Storage was utilized to store user photographs in the cloud, and Azure Computer Vision was used to generate image tags using machine learning. The Google Maps API was used to create an interactive mapping feature that displays markers based on user-supplied coordinates. The combination of these technologies yielded a strong web application that manages authentication, allows for cloud storage, employs advanced picture analysis for tag generation, and provides an immersive mapping experience.

The biggest challenge was to collect the user coordinates and to plot them on the Google Map on the Profile Page. It was also my first time using tailwind CSS.

The hack successfully combines several technologies, including Microsoft Azure and Google Maps. It was my first experience with Azure image analysis services. The program uploads an image via file upload and renders the coordinates via Google Maps.

I learned how to utilize Google Maps to create marker clusters and how to use Microsoft Azure Image Analysis Service.

We intend to improve the UI of the application and employ search feature using the generated tags.