How to Build an iOS App with Visual AI Capabilities

This guide authored by Aryan Vasudevan details the process of creating an iOS app with real-time object detection capabilities to locate glasses using a custom machine learning model. It begins with training an object detection model through Roboflow, specifically using the RF-DETR Nano model for its low latency, despite a slight reduction in accuracy. The guide then outlines setting up the development environment in Xcode and integrating the roboflow-swift package to utilize the trained model within the app. The implementation involves creating a user interface with SwiftUI, embedding a live camera feed, and using Core ML for efficient on-device inference without relying on hosted APIs. The app leverages real-time predictions from the Roboflow model, displaying bounding boxes over detected objects by converting image coordinates to the screen’s coordinate system, ensuring minimal latency and seamless functionality. This comprehensive walkthrough provides insights into deploying visual AI capabilities on iOS, emphasizing the importance of model efficiency for real-time applications.