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Bootstrap is an HTML, CSS and JS library that focuses on simplifying the development of informative web pages (as opposed to web applications). The primary purpose of adding it to a web project is to apply Bootstrap's choices of color, size, font and layout to that project.
An example of an image blurred using a box blur. A box blur (also known as a box linear filter) is a spatial domain linear filter in which each pixel in the resulting image has a value equal to the average value of its neighboring pixels in the input image. It is a form of low-pass ("blurring") filter.
Tailwind CSS is an open-source CSS framework.Unlike other frameworks, like Bootstrap, it does not provide a series of predefined classes for elements such as buttons or tables.
The term comes from the Japanese word boke (暈け/ボケ), which means "blur" or "haze", resulting in boke-aji (ボケ味), the "blur quality".This is derived as a noun form of the verb bokeru, which is written in several ways, [7] with additional meanings and nuances: 暈ける refers to being blurry, hazy or out-of-focus, whereas the 惚ける and 呆ける spellings refer to being mentally ...
The difference between a small and large Gaussian blur. In image processing, a Gaussian blur (also known as Gaussian smoothing) is the result of blurring an image by a Gaussian function (named after mathematician and scientist Carl Friedrich Gauss). It is a widely used effect in graphics software, typically to reduce image noise and reduce detail.
A typical button is a rectangle or rounded rectangle, wider than it is tall, with a descriptive caption in its center. [2] Other buttons may be square or round, with simple icons . The most common method of pressing a button is clicking it with a pointer controlled by a mouse , or a touchpad , but other input such as keystroke can be used to ...
Image credits: historycoolkids The History Cool Kids Instagram account has amassed an impressive 1.5 million followers since its creation in 2016. But the page’s success will come as no surprise ...
The other entries would be similarly weighted, where we position the center of the kernel on each of the boundary points of the image, and compute a weighted sum. The values of a given pixel in the output image are calculated by multiplying each kernel value by the corresponding input image pixel values.