r/computervision • u/AnyFace430 • 14h ago
Commercial From image masks to CNC coordinates: a configurable vision workflow for rotated workpieces
https://www.youtube.com/watch?v=RX5qv1N1FqwDisclosure: I'm developing Screph, the application shown in this demo.
This example connects an editable computer-vision pipeline to a CNC job preview. It separates the work surface, five rotated wooden workpieces, clamps and excluded regions, then uses the detected positions to transform existing toolpaths. The operator reviews the overlays before approving the prepared job.
The demonstration uses color segmentation. Intermediate masks are exposed in the interface so detection can be inspected and adjusted. A differently colored knot illustrates an excluded region; this is an example-specific rule, not a general wood-defect detector. Camera calibration and table-plane calibration are separate steps, and stock height is a user setting.
The recording uses a synthetic scene and an internal machining simulator. It demonstrates the software workflow, not measured real-world accuracy or proven robustness under changing lighting, dust or occlusion. Narration and some scene assets are AI-assisted.
I'm interested in feedback on the diagnostic interface: which intermediate results would you want visible before trusting the pose estimate on a real camera feed?
Project: https://screph.com/en/
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u/Most-Vehicle-7825 10h ago
I once built a demo for a hackathon where we calibrated a projector to a 2.5D Cad and projected tool paths on it.
That would be a great extension here.
You could first find the objects, then project their outline back to them and also project screw holes so you can fix them without running through the screws later.