Accomplishments
At the start of the week, Brian and I took videos at Giant Eagle to test our models, and my model for the shopping cart detection works reasonably well on the footage that we have. However, I realized that the accuracy would probably be improved by putting the camera higher up than originally planned.
To improve the accuracy, I also tried to split the larger video into two 640 x 640 videos because the model is trained on image sizes of 640×640, but I couldn’t get the model to predict on two videos without some kind of error despite running the process in separate threads. I don’t think it will be necessary for the interim demo, and there might be better ways to improve accuracy (such as the higher camera angle and simply collecting more data from Salem’s Market, where we plan to implement our system), so I will just put this aside for now and just run inference on the original large video instead.
Lastly, I changed the method for counting carts from a static bounding box that counts when carts enter/leave. Instead, I use a static bounding box to find the first cart, and then look for the next cart in a small region after the first cart, and so on and so forth until the last cart, which should minimize errors due to carts that are passing by the line but not entering.
Progress
I plan to collect some real data from Salem’s Market this week and retraining my model for higher accuracy. If there is any component that’s missing for us to have a complete end-to-end system, I will also work on that (such as if our throughput calculations aren’t quite done).