QuickThumbs

Inspiration

Creating custom thumbnails for videos or other types of content can be time-consuming, especially for creators who need to produce a large volume of content. QuickThumbs can help speed up the process and make it more efficient.

What it does

It takes Images and Texts for thumbnails as inputs from the user and gives thumbnail as output.

How we built it

We built the UI using HTML, CSS and Javascript, and the back-end using Python, openCV and Pillow for image processing, FastAPI for request handling. we also used some pretrained machine learning model like in2net for background removal, and LapSRN for image super resolution.

Challenges we ran into

Upscaling the input image was a challenge for us.

Accomplishments that we're proud of

We are proud of creating a nice UI and the solution to a major problem of Content creators nowadays.

What we learned

We learned about the new technology of upscaling an image using LapSRN. and also to work together as a team.

Built With

• css
• fastapi
• html
• in2net
• javascript
• lapsrn
• opencv
• pillow
• python