Transforming the Raspberry Pi into a Squirrel Sentry with Computer Vision

Combining computer vision with a Raspberry Pi, this article guides readers through creating a "squirrel sentry" system capable of detecting and responding to squirrels' movements. The process involves setting up a Raspberry Pi, training a custom computer vision model using Roboflow, and deploying it on a local inference server. The article details the setup of the Raspberry Pi with a fresh operating system and the installation of necessary software, including Docker and the Roboflow API library, to run an inference server locally. Using Visual Studio Code, users can connect to the Raspberry Pi and write code to send images to the server and receive predictions. The article further demonstrates creating a live video feed with Python and Flask to detect squirrels through video analysis and trigger actions, such as activating a relay. The project showcases the Raspberry Pi's capabilities in handling computer vision tasks and highlights Roboflow's tools for deploying such solutions efficiently.

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