The implementation of our project changed slightly again this week and some more details were figured out. Instead of using a NVIDIA Jetson TX2, we will use a NVIDIA Jetson Nano. The TX2 was much larger in its form factor than we expected and the Nano has enough compute power for our use case. We have also decided on using YOLOv5 for object detection after doing some testing on preliminary images. There is some risk that we won’t be able to detect chairs when people are sitting on them, and in this case we may just ignore those objects and only identify empty chairs as it still will meet our use case requirements. Identifying chairs which are occluded also may be difficult and we may try and preprocess the image by filtering by known colors of chairs in the room. We have changed the delegation of tasks slightly, and Chen (instead of Mehar) will be working on counting the number of chairs and interpolating the middle of each of the bounding boxes outputted from Yolov5.
Here is a picture of Yolov5 working on an image we took of a study room we hope to use for MVP:
