For this week, I continued with developing my core image processing pipeline. I conducted tests on object classification using the YOLOv5x model with some sample fridge images, and I collaborated with my team to finalize the list of our target food items for model training. I always begun with integrating the CV pipeline with the Raspberry Pi to validate real-time image capture.
For my progress, I am currently on track with my project timeline. Preliminary object detection is functioning, and I continuing to work on improving the model frequency. I am beginning on integrating my model with the edge processor.
For my goals for next week, I aim to continue improving the performance of my YOLOv5 model, as well as integrating the model with our Raspberry Pi.