Abstract
This project presents an object-detection-based surveillance system applying YOLOv3 engine and streaming the detection result on a web browser with 2 cameras (2 channels), simultaneously the detection information is stored in a database. The application consists of three main components: (1) YOLOv3 object detection module, (2) a database for storing detection results including images and information, and (3) a web template for observation and querying data from the database. This application applied Django, an open-source and flexible web framework written in Python, for communicating between the object detection module, the database, and the web browser. The experimental results proved that the application can work stably and can be applied to surveillance system at companies, factories, or public locations such as bus station or airport.
The code of this work is publicly available at https://github.com/tranleanh/yolo-django-streaming.
Email: tranleanh.nt@gmail.com
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