The dataset and model are both being utilized from TACO (Trash Annotations in Context). The dataset is a collection of images of trash on different backgrounds including sand, gravel, and concrete which are then annotated with the trash detected in the image as well as their positions. TACO additionally trained a mask R-CNN classification model that is capable of taking any image and returning the location and type of trash.

We plan on using this model on data captured by our drone to classify all the types of garbage on each section of the beach. Once this is done, we will be able to count every individual piece of trash on any subsection of a beach to create a heatmap of where the dirtiest beaches are in any region. The drone will act as a sliding window to collect data and we will then process this into an array of trash quantities which will feed our website visuals.