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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]
This template is a software fork of {{Annotated image}} that was made for annotating generic images, like the thumbnail below, and page-spanning diagrams (e.g., many of the these image insertion templates) with a more normal appearance, a heading, and more alignment options than Template:Annotated image.
Smarty-based templates (1.x), Twig-based templates (2+) class inheritance diagrams cross reference to generated documentation, and to php.net function reference Yes pydoc: RDoc: ROBODoc: Sphinx: 10 themes; Jinja2 templating; Python plugins several in sphinx-contrib, e.g. using aafigure, actdiag, Google Chart, or gnuplot
A navigational box that can be placed at the bottom of articles. Template parameters [Edit template data] Parameter Description Type Status State state The initial visibility of the navbox Suggested values collapsed expanded autocollapse String suggested Template transclusions Transclusion maintenance Check completeness of transclusions The above documentation is transcluded from Template ...
Template matching [1] is a technique in digital image processing for finding small parts of an image which match a template image. It can be used for quality control in manufacturing, [ 2 ] navigation of mobile robots , [ 3 ] or edge detection in images.
JBIG2 is an image compression standard for bi-level images, developed by the Joint Bi-level Image Experts Group.It is suitable for both lossless and lossy compression. . According to a press release [1] from the Group, in its lossless mode JBIG2 typically generates files 3–5 times smaller than Fax Group 4 and 2–4 times smaller than JBIG, the previous bi-level compression standard released by
To provide attribution use {{Cc-by-4.0|Attribution details}}. Those who reproduce the work must attribute it in the manner specified by the author or licensor (as the parameter "Attribution details"). Other Creative Commons templates are available at Wikipedia:Image copyright tags. Please be sure to use the right one.
Grayscale images have many shades of gray in between. Grayscale images can be the result of measuring the intensity of light at each pixel according to a particular weighted combination of frequencies (or wavelengths), and in such cases they are monochromatic proper when only a single frequency (in practice, a narrow band of frequencies) is ...