Deep-Framework ============== Introduction ------------ The DEEP-Framework is a Python-based distributed and scalable framework for analyzing a real-time video stream. At its core, the framework provides a modular Docker-based pipeline that allows to distribute and parallelize all tasks from video capturing, to object detection, to information extraction, to results collection, to output streaming. The current version includes an implementation of following pipelines: * A face detector and various algorithms that extract information from faces like: - Age estimation - Gender estimation - Face recognition - Glasses detection - Yaw estimation - Pitch estimation * A person detector and an algorithm that extract information about clothing. * A vehicle detector and an algorithm that performs a flux analysis of the scene. It's possible to run multiple pipeline at the same time. A demo web app is also included. Content Index ------------- .. toctree:: :maxdepth: 3 :includehidden: features architecture start run usage References ---------- This work was published in the journal Sensors in the Special Issue "Applications of Video Processing and Computer Vision Sensors". The article is available in open access at this `link `__. License ------- This project is licensed under the GPL3 License - see the `LICENSE `__ file for details.