One of our teammates talked to Google and found their API would be ideal for facial recognition and analytics. After discussing that with her friends, she came to the realization that we could use the API to track the emotional sentiment of a large crowd of people presented with a demonstration or a teacher presenting to his or her class.
Sentimentality tracker takes data from a video stream exported by a camera and uses Google's API to image tag each of the faces in the particular frame of the said stream. It then returns that data back to our function which maps the data to a numerical value and then graphs it as a function of time, giving the presenter real-time information on how well the audience is receiving the information given.
We started with a basic python function that interfaces with Google's given API and then we plot that data in a graphical setting using the module matplotlib
Technical difficulties with downloading modules and finding directories proved the most challenging; a person's code on one computer often failed to load on a second, even when the same modules were included
We are proud of the product that we made and the Proof of Concept that we have created
We have learned how to use new modules, how to track iterations of our code using Git and GitHub, and how to better identify and solve problems using Computer Science concepts
We hope to make a more aesthetically pleasing graphical interface and improving the UI. We also want to provide better data processing and more helpful returned data to help the presenters in their lectures.
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