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Text-to-Image personalization is a task in deep learning for computer graphics that augments pre-trained text-to-image generative models. In this task, a generative model that was trained on large-scale data (usually a foundation model ), is adapted such that it can generate images of novel, user-provided concepts.
An image conditioned on the prompt an astronaut riding a horse, by Hiroshige, generated by Stable Diffusion 3.5, a large-scale text-to-image model first released in 2022. A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description.
An example of prompt usage for text-to-image generation, using Fooocus. Prompts for some text-to-image models can also include images and keywords and configurable parameters, such as artistic style, which is often used via keyphrases like "in the style of [name of an artist]" in the prompt [91] and/or selection of a broad aesthetic/art style.
In October of that year, Canva announced that it had raised an additional A$85 million at a valuation of A$3.2 billion and launched an enterprise product. [20] In December 2019, Canva announced Canva for Education, a free product for schools and other educational institutions intended to facilitate collaboration between students and teachers. [21]
A caricature is a rendered image showing the features of its subject in a simplified or exaggerated way through sketching, pencil strokes, or other artistic drawings (compare to: cartoon). Caricatures can be either insulting or complimentary, and can serve a political purpose, be drawn solely for entertainment, or for a combination of both.
Comic Sans Pro is an updated version of Comic Sans created by Terrance Weinzierl from Monotype Imaging. While retaining the original designs of the core characters, it expands the typeface by adding new italic variants, in addition to swashes, small capitals, extra ornaments and symbols including speech bubbles, onomatopoeia and dingbats, as well as text figures and other stylistic alternatives.