The manufacturing of products often requires careful quality control, especially when health and safety depend on the quality of the product. For example, in the case of medical pills, small physical defects may not only impact the appearance of the product, but can result in incorrect dosages. To help automate the detection of such defects, we set out to build an image recognition model in PerceptiLabs that could identify defective pills by analyzing images. A model like this could potentially help pharmaceutical companies, pharmacists, or medical practitioners identify physically defective pill products. To train our model, we used the images from the Pill defect dataset.