We are self-inspired because being masters students, we have realized the importance of course notes. Hence we came up with the idea of note sharing which will help students to share the course content as well as keep their own notes digitized and organized online.
What it does
The application takes the image of the hand written notes and uses Microsoft vision API to convert it in to text. This text will help student to understand the course content. The mobile application takes the image of the notes and this image is processed using Microsoft Vision API. The result of the API call is stored in the text form in the database, which can be simultaneously updated and corrected on the web application. The application also allows students to follow other students and topics, and will get a feed of updates for the same on their home page. Students can also like notes to share appreciation.
How we built it
Challenges we ran into
The challenges we faced were mostly related to integrating the Microsoft Computer Vision API with the the application. The most difficult challenge was to send image from mobile application to web application for the further processing. A crucial decision involved moving the Microsoft Computer Vision API call from Android device to the Server, as a result of missing/badly configured libraries in Android.
Accomplishments that we're proud of
We are successful in implementing the application and integrating the developed application with Microsoft Vision API. We are glad that we are able to accept of the challenges we faced and successfully implemented it.
What we learned
Integration of the APIs with other applications. We learned about Java Spring Framework. The development of mobile application is one more thing which we learned. The most important thing which we understood is that the collaboration of team members will help to solve the software problem efficiently and implement the solution effectively.
What's next for Handwritten Note Sharing WebApp
The complete integration of the application with the mobile application will be really convenient for the the students. A dashboard can be implemented to do textual analysis on the dataset, with the user simultaneously updating the dataset and improving it with continued use of the application. Some minor UI tweaks are left, but the back-end queries are fixed and tested.