Inspiration
When looking through the Microsoft API's we came across the Computer Vision API and immediately thought this would be useful to help people learn new languages.
What it does
Currently, it allows people to create an account, submit URL of an image that contains the object they want to learn the meaning of in English, and finally create a set of flashcards that will facilitate the learning process.
How I built it
The front end is built with html, css, javascript, and less. The Computer Vision process is done using the Microsoft Computer Vision API. The back end is built with node.js and mongodb.
Challenges I ran into
The initial goal of our project was to make a mobile application, in which users would be able to take pictures and be presented with the word associated with the object in real-time.
Although we were able to get most aspects of the mobile application running using swift and firebase, unfortunately, we were unable to make the actual call on the image captured due to an unexplainable assembly level register error.
Accomplishments that I'm proud of
None of us had ever made an application using swift, and we were able to develop ios skills that we plan to advance in the future.
What I learned
In terms of technical skills, we learned how to develop ios applications. In other terms, we learned that things don't always go to plan and sometimes redirecting efforts can be beneficial to the overall project.
What's next for FamWords
We hope to eventually go mobile! We would also like to expand to more languages and possibly incorporating audio for the seeing impaired as this can help them know whats in front of them.
Built With
- css3
- express.js
- html5
- javascript
- less
- microsoft-computer-vision-api
- mongodb
- node.js
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