Accomplished
This week I looked at how much of our detection we get for free from a pretrained model. I went through the classes it covers and wrote a short script to run it over gym images and count what it finds. People, backpacks, handbags, and bottles are all classes it already knows, which covers most of what gets left at a rack. Weight plates are not, and neither are towels, so the bench check will need training on our own labeled images rather than working out of the box. That is what we expected, but it is good to have it confirmed early. I also started looking into whether any public datasets include gym plates so we do not have to label everything from scratch.
I started on camera placement as well. The main issue is that people and equipment block the view, so I have been working through mounting height and angle for each check and what each camera has to be able to see. The bench camera is the tricky one, since it needs both the bar and the plate storage area in frame so we can tell plates that were put away from plates left on the bar.
Progress
Mostly on schedule. The detector work is done and the plate result was not a surprise, since time to collect and label images is already in our schedule. The camera placement plan is started but not finished, and I will finish it Sunday.
Deliverables
Finish the camera placement plan and take photos of the candidate positions. Record a first round of footage, at the gym if permission comes through and at a mock setup otherwise, and start labeling plate images. Help with the design presentation slides.