Where computer vision pays off
Vision projects work best when a person currently looks at pictures repeatedly and the decision is reasonably clear. Common examples include surface inspection in manufacturing, reading IDs and invoices with OCR, checking shelf stock, monitoring safety equipment on sites, and analyzing medical or satellite images with expert oversight. We also agree a minimum acceptable recall for the most costly defect, since that figure drives design.
We start by writing down what counts as a correct result, how costly each type of mistake is, and what the camera and lighting will really look like. A model that scores well on tidy samples but fails in dim, dusty or angled conditions is a common reason pilots stall, so we test on honest data. Cameras, lenses and lighting are specified alongside the model, because hardware choices can remove entire classes of error.
