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The Three Layers That Made My 0.844 mAP Shelf Detector Useful on a Pi 3

This story is from 2026-09-01. It is preserved in the archive; the latest stories are on the live feed.

The model I trained for empty-shelf detection got 0.844 mAP50 on a held-out test set. That number looks useful. In practice, the raw model output was nearly unusable on the actual installation until I added three post-processing layers in code — none of which required touching the model weights. Th…

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  1. 2026-09-01 10:39 · DEV Community — Machine Learning
    The Three Layers That Made My 0.844 mAP Shelf Detector Useful on a Pi 3

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