The most significant risks that could jeopardize the success of the project are primarily related to the ML Model: specifically, not having enough data for the ML model and/or not getting accurate results. We saw poor results this last week when training the graph detection model on a very small number of images, so contingency plans involve having the whole group involved in the data collection process as well as augmenting our data with a large number of auto-generated images, which we have already implemented.
Another risk is not being able to find enough testers/not finding visually-impaired people willing to work with us to test the product. Contingency plans involve testing the product heavily on sighted users, and we are managing the other risk by beginning to reach out to try to find visually-impaired testers.
We did not make any changes to the system design, and did not update our schedule.
We were able to connect up our Raspberry Pi, camera, and buttons as shown below.
We were able to get the graph generation and slide generation working this week. See Nithya’s post for images of this. We also got the stop button and the app to communicate by setting up a server on the app side.