Image Processing with AutoML
Quick short explanation about the implementation more focused on the customer part. I use Google Vision & AutoML by Google Cloud Platform. The main goal is the system able to differentiate which parts are factory default (original) and which parts are customized (non-original). And I expect the machine learning able to detect the brand and the type of the motorcycles too. Therefore, I trained various customized motorcycles and original motorcycles with different types and brands.
Labels were made to differentiate the parts and brands/types of the bike. There are 300++ photos trained, and the results are quite amazing. The system itself able to detect the labels correctly. However, since the system trained with 300++ photos only, the confidence prediction level might be low sometimes. And even resulted positive false, or negative true.
So that's why more datasets needed, and more training needed.