(Mobile) Home screen
(Mobile) Example of search
(Mobile) Users are prompted with option to take picture or select from camera roll
(Mobile) Users are presented with gif based on input; Has options to regenerate or share
(Mobile) Share menu
(Web) Home page
(Web) Gif has been generated for users
Simple texts and messages are so dull. We've all been in conversations and thought to ourselves, "Hey, I need a gif!" All of us had used gif keyboards before but saw lots of places for improvement. We wanted to stop playing the losing roulette game with poorly organized gifs.
"Dank It!" makes the experience better!
What it does
"Dank It!" quickly helps you identify the perfect gif for any moment through the use of facial recognition (analyzes face to discover emotions) and key words inputted by the user.
How we built it
We decided to make this app as accessible as possible by creating both a web interface and a mobile app. We interfaced with Microsoft's Project Oxford, Parse, and Giphy's API with Python, HTML, CSS, and Lua.
Challenges we ran into
We found it difficult to perfect user experience, optimize the search for the ideal gif, and connecting all of the different API's.
Accomplishments that we're proud of
We developed both a clean user interface as well as a fully functioning application. Not only is our product relevant to our generation, but more importantly it's an app that will add some fun and happiness to everyday lives.
What we learned
Each person in the team went out of her individual comfort zone. Some of us had never hacked and some of us had never done backend development. We were able to grow as female programmers in the tech industry!
What's next for Dank It!
In the future, we hope to expand beyond emotion and facial recognition; We want to be able to analyze pictures of the environment and objects to find appropriate memes and gifs for that as well.