By Lorin Hochstein

ISBN-10: 1491915323

ISBN-13: 9781491915325

One of several configuration administration instruments on hand, Ansible has a few particular advantages—it’s minimum in nature, you don’t have to set up whatever in your nodes, and it has a simple studying curve. This functional consultant indicates you ways to be efficient with this instrument speedy, no matter if you’re a developer deploying code to creation or a approach administrator searching for a greater automation solution.

Author Lorin Hochstein exhibits you ways to put in writing playbooks (Ansible’s configuration administration scripts), deal with distant servers, and discover the tool’s actual strength: integrated declarative modules. You’ll realize that Ansible has the performance you wish and the simplicity you desire.

* know the way Ansible differs from different configuration administration systems
* Use the YAML dossier structure to jot down your individual playbooks
* study Ansible’s help for variables and facts
* paintings with a whole instance to install a non-trivial application
* Use roles to simplify and reuse playbooks
* Make playbooks run swifter with ssh multiplexing, pipelining, and parallelism
* set up functions to Amazon EC2 and different cloud platforms
* Use Ansible to create Docker pictures and set up Docker bins

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3 Image Capture The processing of still photos or scientific images can be done quite effectively using scanned image or data from digital cameras. The availability of digital image data has increased many-fold over the past decade, and it is no longer unusual to find a digital camera, a scanner, and a video camera in a typical household or small college laboratory. Other kinds of data and other devices can be quite valuable sources of images for a vision system, key among these the webcam. These are digital cameras, almost always USB powered, having image sizes of 640x480 or larger.

Depth An integer specifying the number of bits per pixel. origin The origin of the coordinate system. An integer: 0=upper left, 1=lower left. widthStep An integer specifying, in bytes, the size of one row of the image. imageSize An integer specifying, in bytes, the size of the image ( = widthStep * height). imageDataOrigin A pointer to the origin (root, base) of the image. roi A pointer to a structure that defines a region of interest within this image that is being processed. When an image is created or read in from a file, an instance of an IplImage is created for it, and the appropriate fields are given values.

8: Standard test images for edge-detector evaluation. There are three step edges and two stairs, plus a real sampled image; all have been subjected to normally distributed zero mean noise with known standard deviations of 3, 9, and 18. Chapter 2 ■ Edge-Detection Techniques In addition, it would be nice to have a numerical measure of how successful an edge-detection scheme is in an absolute sense. There is no such measure in general, but something usable can be constructed by thinking about the ways in which an edge detector can fail or be wrong.

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Ansible: Up and Running by Lorin Hochstein


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