Accomplishments
This week, I managed to finish training my model after some delay (5000 images in a dataset quickly led to me being booted off Google Colab for hitting GPU usage limits). I trained it for 100 epochs total, but I had to split it into 50 epoch sessions because of GPU usage limits, so I trained for 50 epochs and then trained the resulting model for another 50 epochs. The resulting model seems to have serviceable precision, reaching about 75%-80%, and the validation batches seem to detect grocery items relatively well.
Now the implementation for the throughput calculation module is complete with the updated module. Simon and I will go to a grocery store tomorrow (Giant Eagle/Aldis), take a video of items moving on a conveyor belt, and test the throughput module.
Progress
I am still behind schedule, but I am currently working with Simon to fully flesh out the line detection module. This next week, we will try to implement this fully and test it for the interim demo, and start helping out with the relative fullness module since that is very important.