Emojiverse

Inspiration

We wanted to find a fun and cool way similar to Snapchat to show off recent advances in computer vision such as face tracking and emotion analysis.

What it does

It tracks human faces in an image and replaces them with emojis that match the emotions on their face.

How we built it

• Android User Interface
• Flask/python computer vision processing backend with OpenCV
• Azure cloud storage
• Microsoft Cognitive Services to recognize faces and emotions
• AWS mysql database to hold all photos

Challenges we ran into

SERVERS AND NETWORK CONNECTION. CAN'T GET ENOUGH OF THEM.

Accomplishments that we're proud of

First time using so many API's and integrating them. We were able to complete our main goal and wrap it up nicely in a fairly well designed interface that allows you to save and share your photos on social media.

What we learned

We learned how much setup many of these various components involved, especially when using new API's and their dependencies. Also, we learned how to set up and communicate with a server.

What's next for Emojiverse

• Video Tracking
• Object recognition and replacement to create the ultimate Emojiverse

Built With

• amazon-web-services
• android
• azure
• flask
• microsoft-cognitive-services
• opencv