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Brandon’s Status Report for 2/11/2023

During class, I presented our proposal and did peer reviews of other proposal presentations. Outside of class, our team met to have an initial discussion of the design review for the project. We fleshed out the specific tasks that we each need to complete based on our role for the project, and we figured out how we could integrate all parts of the project together. Personally, this helped me have a greater understanding of what I specifically needed to do for the web application and what data I needed to send to or receive from the Raspberry Pi. After the meeting, I created a block diagram for the Web Application side of the project (as shown in the diagram below). Specifically, I listed the tasks that the user is able to complete on the frontend, and design Django models on the backend that would be used to store data in the database. Finally, I updated the schedule based on what we discussed in the meeting for the design review.

Based on the schedule we created, my progress is on schedule. For next week, the main priority is to finish the design review presentation, specifically finishing the block diagram and discussing testing, verification, and validation. In terms of the web application, I hope to set up a React application integrated with Django. Also, I hope to work on letting users upload images for pet classification, which I have prior experience doing.

 

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Max’s Status Report for 2/11/2023

Our group has had meetings to further flesh out our design implementation. One main topic that came up was the possibility of using an FPGA over a Raspberry Pi. This was inspired by witnessing other presentations that were performing computation on live video (rotoscoping, multiple object tracking) that is similar to our projects in terms of the level of computation on live video. Due to this, I have been researching the viability of an FPGA in our solution to improve classification speed of our classifier while still allowing easy video feed input to the FPGA and the ability to communicate with the web application. In addition, I have been researching existing cat/dog breed classifiers and working with InceptionV3 (our currently chosen ML architecture) to see if the current architecture will work.

Due to some major personal setbacks this week I am behind schedule, specifically on evaluating our current ML architecture choice. In addition, as of writing this, I am still unsure as to the viability of using an FPGA and am meeting with my group to further discuss this design change. The main priority for this week is to finish our design review presentation, which will first require a final decision as to whether or not we move forward with an FPGA, Raspberry Pi, or something else as our hardware. In addition, a complete evaluation of the InceptionV3 architecture as it compares to other existing architectures is to be completed soon. This should kick off work on implementing a animal classifier on the chosen architecture, which should be available this week.