PEKAT VISION contains the right set of self-learning tools. These tools can be combined and interwoven with a scripting code. Our experience has shown that exactly these tools together can tackle practically any vision task in manufacturing. For examples check out our github.

Unsupervised anomaly detector can be trained by positive (error-free) examples. It is enough to provide just a few example images. It is able to inspect stable objects or even completely unstable surfaces like deformed textile with pattern.
Supervised surface check is a tool which can be trained to find defects on a completely heterogeneous surfaces. Example of such defects: rust, abrasion, leakage etc.
Object detector and classifier can find objects with unstable shape - e.g. knots on wood. It doesn't even matter if the objects are rotated.
Inspection modules can be combined to a complex flow and even interwoven with custom image preprocessing or scripting code.
Python code gives you high flexibility. You can e.g. preprocess images (e.g. with OpenCV and Numpy), add custom logic or even call external interfaces.
Auto-Trigger can be simply trained to automatically capture images in the right moment without any necessary integration with the machine or assembly line.