Identifying Chocolates With Computer Vision

Karen Weiss, a visual designer at Roboflow, embarked on a project to identify chocolates using computer vision as part of her onboarding process at the company. Inspired by the mystery fillings of See's Candies, Weiss aimed to create a model capable of identifying specific chocolates without cutting into them. She gathered a dataset by taking photos of a See's 1lb Classic Red Heart - Assorted Chocolates, meticulously labeling each type, and applying various augmentations to simulate different conditions. Weiss utilized Roboflow tools to train her model, which eventually achieved a 96.4% mean Average Precision (mAP) and 97.6% recall after adding more data. Despite some limitations, such as a limited image source and the uniformity of the chocolates, Weiss found the experience empowering and accessible, transitioning her perception of computer vision from daunting to manageable. The project serves as a testament to her newfound ability to use computer vision tools effectively, and she encourages others to explore the dataset and model on Roboflow Universe.