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  2. Flux (text-to-image model) - Wikipedia

    en.wikipedia.org/wiki/Flux_(text-to-image_model)

    Flux (also known as FLUX.1) is a text-to-image model developed by Black Forest Labs, based in Freiburg im Breisgau, Germany. Black Forest Labs were founded by former employees of Stability AI. As with other text-to-image models, Flux generates images from natural language descriptions, called prompts.

  3. Template:Linear-gradient background - Wikipedia

    en.wikipedia.org/wiki/Template:Linear-gradient...

    Displays a background using multiple colors which gradually phases from one color to another. Template parameters [Edit template data] Parameter Description Type Status Background color 1 1 First background color Suggested values #000000 Line optional Background color 2 2 Second background color Suggested values #000000 Line optional Background color 3 3 Third background color Suggested values ...

  4. Image gradient - Wikipedia

    en.wikipedia.org/wiki/Image_gradient

    Gradient images are created from the original image (generally by convolving with a filter, one of the simplest being the Sobel filter) for this purpose. Each pixel of a gradient image measures the change in intensity of that same point in the original image, in a given direction. To get the full range of direction, gradient images in the x and ...

  5. LightGBM - Wikipedia

    en.wikipedia.org/wiki/LightGBM

    LightGBM, short for Light Gradient-Boosting Machine, is a free and open-source distributed gradient-boosting framework for machine learning, originally developed by Microsoft. [ 4 ] [ 5 ] It is based on decision tree algorithms and used for ranking , classification and other machine learning tasks.

  6. Color wheel - Wikipedia

    en.wikipedia.org/wiki/Color_wheel

    Gradient RGB/CMY color wheel Seven-color and twelve-color color circles from 1708 (attributed to Claude Boutet) Wilhelm von Bezold's 1874 Farbentafel. A color wheel or color circle [1] is an abstract illustrative organization of color hues around a circle, which shows the relationships between primary colors, secondary colors, tertiary colors etc.

  7. Perlin noise - Wikipedia

    en.wikipedia.org/wiki/Perlin_noise

    Two-dimensional slice through 3D Perlin noise at z = 0. Perlin noise is a type of gradient noise developed by Ken Perlin in 1983. It has many uses, including but not limited to: procedurally generating terrain, applying pseudo-random changes to a variable, and assisting in the creation of image textures.