Being interested in bird watching, I attached a bird feeder to a window of my flat and within a few days various species of bird started visiting the feeder. I decided it would be fun to rig up a motion triggered camera to capture images of the birds, and I used Home-Assistant and a £10 USB webcam to capture images via motion trigger, and setup Home-Assistant to send an image notification to my phone when an image was captured.
However I quickly discovered that all kinds of motion could trigger an image capture. The result was hundreds of images of all kinds of motion, such as planes flying in the distance or even funky light effects. Approximately less than half the images actually contained a bird, so I decided it was necessary to filter out the non-bird images. I have been interested in image classification for a while, and whilst searching online I came across this article on Classificationbox, which looked ideal for this project. This write-up will first present the image classification work using Classificationbox, then describe the practical implementation within an automated system
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