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Source channel @githubtrending · Post #14930 · Jul 8
#other This resource is a huge, well-organized collection of computer vision materials including books, courses, papers, software, datasets, tutorials, and tools. It covers everything from beginner to advanced topics like image processing, object detection, 3D vision, deep learning, and more. You can find free and paid courses from top universities, open-source libraries like OpenCV, pre-trained models, and datasets for practice. This helps you learn computer vision efficiently, find the right tools, and stay updated with the latest research and applications, saving you time and effort in your learning or project development. It’s great for students, researchers, and developers. https://github.com/jbhuang0604/awesome-computer-vision
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@djangoproject · Post #98 · 07/11/2016, 12:22 PM
https://docs.python.org/3/library/asyncio.html #asyncio #Asynchronous programming is more complex than classical “#sequential” programming: see the Develop with asyncio page which lists common traps and explains how to avoid them. Enable the debug mode during development to detect common issues.
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@djangoproject · Post #153 · 09/03/2016, 08:20 PM
http://wla.berkeley.edu/~cs61a/fa11/lectures/streams.html In this chapter, we continue our discussion of real-world applications by developing new tools to process #sequential#data. In Chapter 2, we introduced a sequence interface, implemented in Python by built-in data types such as #tuple and #list. #Sequences supported two operations: querying their length and accessing an element by index. In Chapter 3, we developed a user-defined implementations of the sequence interface, the Rlist class for representing recursive lists. These sequence types proved effective for representing and accessing a wide variety of sequential #datasets.