This week, I finished setting up the PI. I was able to ssh into it and started setting up the python environment. I installed the necessary packages and troubleshooted some installations. I started running some benchmarks of the base yolo model we want to get an idea of any inference time issues. I also set up the github for the fine-tuning, proof-of-concept, and final code. I will be working on the fine tuning code on Sunday. I set up sshing and internet on the Pi as well. Once I finish the benchmarking, I will try different serving frameworks to see if the inference time can be further reduced. While doing fine-tuning, I will be writing boilerplate code for the logging, so we can see how the ML model influences the pipeline. I also looked into manipulating GPIO on the Pi.
In addition, I worked on the circuit to test the amplifier. We wanted to make sure the amplifier worked at lower wattage, because we don’t believe we can power it at full spec. However, if it runs at lower spec, we can hit the wattage requirements of the speaker, which is the important part. I helped diagram the circuit, and use the signal generator, DC-power supply, and oscilliscope. Ultimately, we were able to boost a 60Hz wave from 100mV to 600mV. We used a very conservative amount of amps, 200mA instead of the ~2-3A we expect to be running at full power. We need to perform further testing once we are more confident about this circuit, but it should be fine because our ESP outputs 3V, so we should hit our required ~80W into the speaker.