Using Computer Vision to Detect Package Deliveries

Brian Egge's personal project, detailed in a guest post on the Roboflow Blog, explores using computer vision technology to detect package deliveries at home, addressing concerns like package theft and curious pets. Utilizing a Jetson Nano and an IP camera, Egge developed a local solution that avoids the need for commercial subscription services. He trained an AI model to recognize packages using images labeled through Azure’s Custom Vision and Roboflow, employing data augmentation techniques to enhance detection accuracy. Despite initial challenges, including overfitting issues caused by seasonal changes like Christmas decorations, Egge experimented with different object detection models like YOLOv2-tiny and YOLOv4-tiny to improve accuracy and scalability across varying package sizes and locations. Deployment hurdles involved converting models to ONNX and TensorRT formats, but Egge succeeded in achieving a reliable system that balances processing speed with detection precision. Future goals include implementing transfer learning and model size adjustments to further enhance performance on the Jetson Nano platform.