We were interested in using modern day technology to assist the general public in emergency situations.
What it does
Our application allows the user to enter medical information and take an img folder of their faces. With this information, the application recognizes the faces and assigns it to the information that the user inputted.
How we built it
We used opencv, pyqt 4 and python to create a desktop application.
Challenges we ran into
Our group ended up using different versions of python when programming their portion of the project. By the morning, we realized that we did not have sufficient time to fix the issues that arose when trying to merge our portions into one large project.
Accomplishments that we're proud of
We managed to: detect the face, recognize the face, apply attributes to the face, use face classifications and apply multi-object tracking.
What we learned
We learned a considerable amount from how to use opencv.
What's next for DataFace
We hope to merge our work to have the application to work as intended. Hopefully, we can allow the user to enter health information that you would put on a card for life threatening scenarios. For example, the user can enter whether he or she chooses to be an organ donor, has allegies, or if the user chooses not to consent to CPR. Therefore, when another user of the application finds this individual in a life threatening situation, the user can immediately identify how to deal with the situation.