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使用 OpenCL™ 2.0 读写图片

While Image convolution is not as effective with the new Read-Write images functionality, any image processing technique that needs be done in place may benefit from the Read-Write images. One example of a process that could be used effectively is image composition. In OpenCL 1.2 and earlier, images were qualified with the “__read_only” and __write_only” qualifiers. In the OpenCL 2.0, images can...
Authored by Last updated on 05/31/2019 - 14:20
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 适用于 OpenCL 内核的并行噪声和随机函数

This article describes and links to the Noise code sample. The sample includes an implementation of Perlin noise, which is useful for generating natural-looking textures, such as marble and clouds, for 3D graphics. It also includes a set of pseudo-random number generator functions that are sufficient to make a generated image visually appear random.
Authored by Last updated on 05/17/2019 - 12:00
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使用 LibRealSense 和 OpenCV 流传输 RGB 和深度数据

This article shows you how you can use LibRealSense and OpenCV to stream RGB and depth data. In the end you will have a nice starting point where you use this code base to build upon to create your own LibRealSense / OpenCV applications.
Authored by Rick Blacker (Intel) Last updated on 01/18/2018 - 16:13
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开始使用面向 OpenCL™ 应用的英特尔® SDK 2019:核心概念

了解面向 OpenCL™ 应用的英特尔® SDK 2019 的核心概念并开始构建您的首个应用。
Authored by MICHAEL C. (Intel) Last updated on 07/06/2019 - 19:40