This week, Ethan and Jeremy spent time integrating the hardware trigger with the imaging scripts. We now have a card shoe prototype that triggers the captures with and ADC the bridges the analog trigger with the python scripts on the Jetson Nano. We collected a small dataset by imaging a 52-card deck exactly once. While this is clearly not enough for ML training, we’re using that to explore preprocessing. Sid has been finalizing details of the web app and preparing some ML scripts for training.
Next week, we will finish the PCB design and obtain a larger dataset with the prototype. The team is about one-week behind schedule because the card trigger took longer than expected to bring-up. For the interim demo, we expect to be prepared with a working prototype where one member pulls a card, and a remote display will show the raw and preprocessed capture used for classification. We will definitely include a trained ML model for classification in the demo, but that may not be ready in time.