This week, I started working on fine-tuning the latest YOLOv11 model for our card detection task. I’m still familiarizing myself with all the APIs and researching how I could start off smart to later integrate and deploy easily on Raspberry Pi 8GB. Since we have 8GB of memory, I think I’ll have to wisely choose the model that would be the most efficient in terms of its size. My plan was to validate the model working and achieving validation accuracy ~100% by digging and incorporating more dataset. However, I didn’t get to train the model yet, since I didn’t have any Colab compute units. I’ll have to make sure if we are able to include the compute units for the given $600 stipend. By next week, I should have trained and tested the model, and just start thinking and learning about how I would deploy it on raspberry pi. Also, I’ll have to allow the model to receive input video/image from the camera module later.
