Engage & Persist

Collaborate

Coding

Image 1

Image 2

Image 3

Physical fabrication

Creature Count is a bird-identifying computer vision project aimed at enhancing birdwatching and aiding scientific research on bird populations. Focusing on Boston's avian diversity, it employs a continuously operating ESP32 camera, encased in durable outdoor housing, to capture detailed data on bird appearances and behaviors. This data is vital for research into bird population trends, migration patterns, and environmental effects. Designed for use in residential backyards, the project serves a dual purpose: enriching birdwatching experiences and providing valuable insights for ecological studies, while being accessible to those unable to venture outdoors.

In this studio, my skills in various areas, particularly software development and team collaboration, saw marked improvement. The project fostered an ideal environment for refining my delegation, communication, and leadership skills. Leveraging my background in computer vision, I provided valuable assistance to team members, enhancing our group's efficiency and knowledge base.

The project's core involved developing a refined YOLO model, programming for camera functionality, and creating a website and database for data visualization. This experience deepened my understanding of training computer vision models using the ultralytics library, managing databases, and preparing datasets. The tech stack for this project included YOLOv8 for computer vision, and a combination of SvelteKit, shadcn-ui svelte, tailwindcss, prisma, lucia auth, planetscale, and cloudflare pages for the web development aspect.