2026-01-20Draft
The vision pipeline on the line: from dataset to Jetson
Training a missing-part detector that has to survive a real, messy dataset and run at line speed on edge hardware.
TODO: scaffold only. Write the post.
The problem on the line
TODO: what missing-part detection has to do, and why late is expensive.
The dataset was the real adversary
TODO: why the class taxonomy had to be redesigned against real data, not a clean benchmark.
From training to TensorRT on a Jetson Nano
TODO: the export path (ONNX → TensorRT), what it bought in latency, what it cost in portability.
Closing the loop with traceability
TODO: how detections feed back into the traceability system.