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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.
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.
Artificially intelligent computer-aided design (CAD) can use text-to-3D, image-to-3D, and video-to-3D to automate 3D modeling. [80] AI-based CAD libraries could also be developed using linked open data of schematics and diagrams. [81] AI CAD assistants are used as tools to help streamline workflow. [82]
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 [97] and/or selection of a broad aesthetic/art style.
A single image random text ASCII stereogram is an alternative to SIRDS using random ASCII text instead of dots to produce a 3D form of ASCII art. Map textured stereogram In a map textured stereogram, "a fitted texture is mapped onto the depth image and repeated a number of times" resulting in a pattern where the resulting 3D image is often ...
A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description. Text-to-image models began to be developed in the mid-2010s during the beginnings of the AI boom, as a result of advances in deep neural networks.
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