Being able to analyze factory default in real time is a critical task to increase production line quality and reducing defaults.
Implementing such a use case with deep learning for computer vision can be challenging at scale, especially when it comes to data preprocessing and building production-grade pipelines.
Databricks simplifies this process end to end, making all the operational tasks simple so that you can focus on improving the model performance.
In this demo, we will cover how to implement a complete deep learning pipeline to detect printed circuit board (PCB) defaults, from the image ingestion to real-time inferences (over REST API):