I started the week off by attaching the panel to the drawer slides.
Then, Prof. Nace helped me out with the band saw to create two rectangular prisms for the other side of the drawer slides. I secured the drawer slides to the rectangular prisms and attached them to the indoor side of the door.
It’s a little lopsided, but it works.
Unfortunately, devices are not mounted on the door because I was waiting on parts. However, I made up for that by spending time getting ahead on the motion detection script. I prepared testing data by downloading videos of raccoons and editing ten clips of raccoons that will be used as input to the system. For the motion detection, when a large enough change is detected between the current frame and the reference frame, the program saves a JPEG file, which is the file type that Jing is working with for the ML model. The current frame is set as the new reference frame. This allows the program to output a series of images spaced out in time. The images are noticeably different from each other such that our ML model is not wasting time computing on redundant images. This script does not do any image cropping. To demonstrate the program functionality, I have strung together the image outputs from the program as GIFs:
Deliverables for next week are to have the rotating servo that lifts the panel and image cropping implemented in the motion detection script.