Missing Item Inspection with Computer Vision

James Gallagher's guide on using computer vision for product counting details a step-by-step process to build a missing item inspection system, particularly useful for ensuring accurate counts in food and drink packaging. The system utilizes computer vision to verify the number of bottles in a package before sealing, employing a model trained to recognize bottle tops from collected and labeled images. The guide walks through creating a project on Roboflow, uploading and labeling images, generating a dataset, and training a model using transfer learning from pre-trained weights. Once trained, the model can be deployed using Roboflow Inference to run on any camera connected to a computer, enabling real-time detection and reporting errors if the detected count is incorrect. The system integrates into business logic to alert and rectify discrepancies in packaging, ensuring quality control in manufacturing and logistics.