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  2. Python Imaging Library - Wikipedia

    en.wikipedia.org/wiki/Python_Imaging_Library

    Python Imaging Library is a free and open-source additional library for the Python programming language that adds support for opening, manipulating, and saving many different image file formats. It is available for Windows, Mac OS X and Linux. The latest version of PIL is 1.1.7, was released in September 2009 and supports Python 1.5.2–2.7. [3]

  3. Image retrieval - Wikipedia

    en.wikipedia.org/wiki/Image_retrieval

    Image search is a specialized data search used to find images. To search for images, a user may provide query terms such as keyword, image file/link, or click on some image, and the system will return images "similar" to the query. The similarity used for search criteria could be meta tags, color distribution in images, region/shape attributes ...

  4. Astropy - Wikipedia

    en.wikipedia.org/wiki/Astropy

    Astropy is a collection of software packages written in the Python programming language and designed for use in astronomy. [2] The software is a single, free, core package for astronomical utilities due to the increasingly widespread usage of Python by astronomers, and to foster interoperability between various extant Python astronomy packages. [3]

  5. Python (programming language) - Wikipedia

    en.wikipedia.org/wiki/Python_(programming_language)

    Python 3.0, released in 2008, was a major revision not completely backward-compatible with earlier versions. Python 2.7.18, released in 2020, was the last release of Python 2. [37] Python consistently ranks as one of the most popular programming languages, and has gained widespread use in the machine learning community. [38] [39] [40] [41]

  6. Content-based image retrieval - Wikipedia

    en.wikipedia.org/wiki/Content-based_image_retrieval

    General scheme of content-based image retrieval. Content-based image retrieval, also known as query by image content and content-based visual information retrieval (CBVIR), is the application of computer vision techniques to the image retrieval problem, that is, the problem of searching for digital images in large databases (see this survey [1] for a scientific overview of the CBIR field).

  7. IDLE - Wikipedia

    en.wikipedia.org/wiki/IDLE

    IDLE is intended to be a simple IDE and suitable for beginners, especially in an educational environment. To that end, it is cross-platform, and avoids feature clutter. According to the included README, its main features are: Multi-window text editor with syntax highlighting, autocompletion, smart indent and other features.

  8. List of datasets in computer vision and image processing

    en.wikipedia.org/wiki/List_of_datasets_in...

    Images, Text Classification, object detection 2007 [29] [30] G. Griffin et al. COYO-700M Imagetext-pair dataset 10 billion pairs of alt-text and image sources in HTML documents in CommonCrawl 746,972,269 Images, Text Classification, Image-Language 2022 [31] SIFT10M Dataset SIFT features of Caltech-256 dataset. Extensive SIFT feature extraction.

  9. reStructuredText - Wikipedia

    en.wikipedia.org/wiki/ReStructuredText

    reStructuredText (RST, ReST, or reST) is a file format for textual data used primarily in the Python programming language community for technical documentation.. It is part of the Docutils project of the Python Doc-SIG (Documentation Special Interest Group), aimed at creating a set of tools for Python similar to Javadoc for Java or Plain Old Documentation (POD) for Perl.