Bird watching is an enjoyable passtime that millions of people in the U.S. partake in each year. My project is oreinted towards bird watchers who are just getting into the hobby, or someone who is just genuinely intrested in bird watching.
|Engineer||School||Area of Interest||Grade|
|Martin||The Calhoun School||Electrical Engineering||Incoming Senior|
In demo night, I presented my project in front of a live audiance.
In my final milestone, I implemented a UI so my device can be used remotely. This UI made it posible to fully run the program, as well as operate the zoom function without a keyboard and mouse.
In my second milestone, I moved over from a TensorFlow model to a Nanonetsmodel. Because of this switch, there is no longer a 2 second lag behind the live feed, and there is a greater level of accuracy with the Nanonets model as it goes to a server for all of its processes. In this milestone I have also trained my own dataset of birds, so my model can correctly identify each type.
My first milestone was setting up the Raspberry Pi as well as making sure the computer vision worked. However, my endeavors were fraught with technical errors, displaying Open CV error messages. After some time debugging, I installed the correct version of Open CV. I also enabled the camera on the Raspberry Pi.