u/Grouchy_Signal139

I’m building a vision system to count parts in a JEDEC tray (fixed grid, fixed camera, controlled lighting). Different products may have different package sizes, but the tray layout is known.

Is deep learning (YOLO/CNN) actually better here, or is traditional CV (ROI + threshold/contours) usually enough?

So as a beginner in this field, what i try just basic prepocessing and bunch of morphological operation (erode/dilate). It was successful for big ic, but for small it doesnt work as the morphological operation tends to close the contour. Ive also try YOLO, but it is giving false positive when there empty pocket as it detect it as an ic unit

Any recommendation so that i could learn?