I'm working on a few mini-projects that I'll post about over the next few weeks:
👟 Product Type Classification
As part of SYDE522 Machine Intelligence, I trained a ResNet-18 convolutional neural network (CNN) using the UT Zappos50K data set to classify footwear as sandals, boots, slippers, or shoes. The model has an accuracy of 96%.
📷 3D Models from 2D Photos
Last week Apple released the Object Capture API, which makes it pretty easy to turn 2D photos into 3D models via photogrammetry. I'm synching the sample capture app with the RendAR turntable over BLE and testing it out.
✨ 3D Models from LiDAR
I'm super grateful to have received the Apple Award for Overall Presentation Quality at my capstone symposium. The prize was an iPad Pro, which is equipped with a LiDAR sensor. This gives me another way to capture 3D models.
🪛 3D Printer
I was also honoured to receive the Quansar People's Choice Award as voted on by my classmates 🙏 and put the cash prize toward a Prusa i3 MK3S+ 3D printer. First step is assembling it.