id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_6qacatlyhvbifcttz5bojghhhu	Oleksandr Semeniuta	EPypes: a framework for building event-driven data processing pipelines	2019	20	.pdf	application/pdf	8130	993	53	architecture and Python-based software framework for developing vision algorithms Keywords Computer vision, Computational graph, Publish-subscribe, Robotics, Python, Pipeline, overview of computational systems based on DAGs, the Python data science/computer pool of community-contributed image processing and computer vision algorithms. It allows to develop data processing pipelines, the behavior of algorithm as a computational graph, that is, as a network of functions and data tokens. For example, to visualize the blurred image from the computational graph in Fig. 4 To introduce additional functionality to algorithms expressed as computational graphs and comprise vision processing time sp, overhead from orchestrating the computational graph ocg, 2. EPypes overhead is computed as an excess time in the vision pipeline in addition to the EPypes: a framework for building event-driven data processing pipelines EPypes: a framework for building event-driven data processing pipelines EPypes: a framework for building event-driven data processing pipelines	./cache/work_6qacatlyhvbifcttz5bojghhhu.pdf	./txt/work_6qacatlyhvbifcttz5bojghhhu.txt