PixelPerfect

Inspiration

"As we sifted through countless photos on our phones, fatigue setting in, inspiration sparked. Fueled by the desire for quick and effortless Instagram-worthy posts, our idea was born....PixelPerfect"

What it does

It is an image sorting script that efficiently employs advanced analysis to sort images (we used cases such as very blurry pictures and very high quality pictures to set as the base standard) and that returns images it deems are the highest quality amongst each other

How we built it

We skillfully wielded the vast arrays of OpenCV and dlib to craft our facial recognition and image quality assessment feature. We set up an AWS EC2 server creating an Instance, allowing remote access and setting up SSH, continuously expanding our knowledge of AWS services and troubleshooting common issues as well as optimizing our server for efficiency.

Challenges we ran into

-Implementing the python script into the AWS ec2 server -Determining API's we needed to use -Connecting Back-End of our python script to the Front end of a website

Accomplishments that we're proud of

We successfully integrated it into an AWS EC2 web server, incorporating facial recognition to identify faces, smiles, and assess image quality, including blurry pictures. -Used Grayscale filter on each RGB to which filtered out irrelevant information to our analysis of intensity of each RGB thus making it uniform for us to apply the Laplacian Filter -Used the Laplacian filter for edge detection and provides a measure of the rate of change of intensity/brightness in an image. This determined if an image was blurry or not.

What we learned

Our journey involved learning AWS EC2, refining time management, and building strong team dynamics. We learned to harness cloud technology for projects, efficiently manage time, and collaborate effectively with each other. These skills have not only empowered us to deliver successful projects but also enriched our ability to work harmoniously in any setting.

What's next for PixelPerfect

-To assess video quality, we analyze frames per second, audio quality, and video resolution. -Additionally, we are planning to implement an innovative feature that, after a night out, automatically detects and saves faces in photos. It then scans your contacts to find matching faces and suggests sending those photos to the respective contacts.