Solder Defect Detection

In this example, we showcase a real-world use case: detecting soldering defects on SMD components using an OAK4-CS edge AI camera mounted on a microscope. The OAK4-S features a 48MP IMX586 rolling shutter sensor, making it ideal for high-resolution, real-time PCB inspection.The goal is to demonstrate how easy it is to go from an idea to an initial working prototype for edge-based defect detection, using tools like Roboflow, LuxonisTrain, and the DepthAI platform—with minimal setup and no machine learning expertise required.

Materials used

AMScope (SM-7 series)
OAK4-CS
3D printed camera mount

The Process in a Nutshell

Find a baseline dataset We started with a public Roboflow dataset on PCB defects. First evaluation of its performance was done on Roboflow’s web UI.
Capture and annotate our own data to add to baseline dataset Took ~50 microscope photos with the OAK4-S and labeled defects.
Retrain the model Combined public + custom data and trained using LuxonisTrain.
Deploy to the OAK4-S Loaded the model onto the camera for real-time solder inspection.