Cognex Deep Learning calculates the number of mouthpieces housed within large shipping cartons entirely, tackling this demanding application head-on. Merging positional instruments located overhead with million-pixel cameras and parallel placements of strong external linear lights, this approach counts transport containers holding over four thousand mouthpieces. Trained using a modest group of sample images, Cognex Deep Learning distinguishes among various mouthpiece defect categories, including white carbon, activated charcoal, concave structures, and others, ensuring accurate enumeration regardless of mouthpiece dimension, hue, or form.