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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

@djangoproject · Post #316 · 04/28/2017, 06:09 AM

https://github.com/blissnd/easyxls Convert any #spreadsheet into a Python internal #dict/#array data structure, for easy processing. Can also handle pivot tables. For pivot table usage, header_row_start & header_col_start need to be set equal to the top left corner of the pivot table => header_row_start=8, header_col_start='c' in the included example. Column IDs must always be lowercase chars in quotes, e.g. 'a'.

djangoproject

@djangoproject · Post #129 · 08/31/2016, 03:36 PM

https://pypi.python.org/pypi/numpy #NumPy is a general-purpose #array-processing package designed to efficiently manipulate large #multi-dimensional arrays of arbitrary records without sacrificing too much speed for small multi-dimensional #arrays. NumPy is built on the #Numeric code base and adds features introduced by #numarray as well as an extended #C-API and the ability to create arrays of arbitrary type which also makes NumPy suitable for interfacing with general-purpose #data-base applications.