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.