We were inspired by a portrait photo by conceptual artist Phil Toledano, who sought to capture the emotion of gaming. When a gamer is on the verge of something called an epic win, they will have slightly bulging eyes that exude a little bit of fear, but also intense concentration and deep focus on tackling a really difficult problem. Their puckered lips curving slightly upwards also evoke a sense of both optimism and urgency.
Images have one shot, one impression to evoke feelings. And when you're on the verge of an epic win, you're probably feeling amazing. While many players may capture their screen gameplay, how many players actually capture themselves in an image in these glorious moments?
That's why we created Instawin—
What it does
we created an app that instantly captures your look when you’re on the verge of an epic win. Our app then allows you to upload media to a gallery where you can wax nostalgic about these fleeting yet powerful moments. Here, nostalgia “acts as an antidote to sadness and feelings of loss and elevates one’s mood, and people who tend to get nostalgic easily tend to have higher self esteem, find it easy to trust others, and suffer from depression less.”.(https://www.psychologyofgames.com/2013/11/the-psychology-of-video-game-nostalgia/)
How we built it
We built our project using Python Flask and OpenCV.
Challenges we ran into
We were all new to using computer vision and machine learning, and for some of us this is the first time we coded in Python! Setting up the environment was quite a challenge, as there were permission issues potentially related to hardware or our ability to download the correct library or components. We also had to coordinate different timezones.
Refining the epic win smile face detection model was tricky because this was our first time working with machine learning. Additionally, even when our code was able to capture images when the camera detected a specific epic win face smile, we had to find ways to not generate hundreds of images, since it can be a quick process and our computers process commands very quickly.
Unfortunately, one of our teammates was raring to contribute but then did not contact us afterwards. This person was tasked with the image gallery, and we were able to quickly make this happen even with limited Flask web development experience!
Accomplishments that we're proud of
With one member who has never worked with python, we stretched our technical knowledge and boundaries and helped each other out in pair-programming sessions! We went through the motions of creating a project, working together and delegating tasks, and are now well equipped for our next hackathon!
We were also able to figure out how to create an image gallery that outputs images from a folder, and we created the mechanism to manually upload our own images to the folder.
What we learned
We learned so much about computer vision and how back end code can interact with front end code with a framework like Flask! We also learned about the art of presenting our hack.
What's next for Instawin
We would love to create a network where people can share their epic wins and photos— imagine profile pics where everyone shows their epic win face!
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