Ad
related to: random generator for drawing names based on picture
Search results
Results From The WOW.Com Content Network
Lavarand, also known as the Wall of Entropy, is a hardware random number generator designed by Silicon Graphics that worked by taking pictures of the patterns made by the floating material in lava lamps, extracting random data from the pictures, and using the result to seed a pseudorandom number generator. [1]
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.
Rochette was the artist for the graphic novel the film was based on John Romita Jr. [40] "Wall of Villains" portraits Kick-Ass: Romita Jr. was one of the creators of the Kick-Ass comic series the film was based on Julian Schnabel [6] paintings in the style of Jean-Michel Basquiat: Basquiat: Schnabel also wrote, directed and composed music for ...
It is a very fast sub-type of LFSR generators. Marsaglia also suggested as an improvement the xorwow generator, in which the output of a xorshift generator is added with a Weyl sequence. The xorwow generator is the default generator in the CURAND library of the nVidia CUDA application programming interface for graphics processing units.
Later, in 2017, a conditional GAN learned to generate 1000 image classes of ImageNet, a large visual database designed for use in visual object recognition software research. [37] [38] By conditioning the GAN on both random noise and a specific class label, this approach enhanced the quality of image synthesis for class-conditional models. [39]
An image generated by Flux using the prompt an astronaut riding a horse, by Picasso and Juan Gris. Generative image models are adept at imitating the visual style of particular artists in their training set, prompting a backlash from some artists who object to having imitations of their style generated on a massive scale without their permission.
Similarly, an image model prompted with the text "a photo of a CEO" might disproportionately generate images of white male CEOs, [128] if trained on a racially biased data set. A number of methods for mitigating bias have been attempted, such as altering input prompts [ 129 ] and reweighting training data.
DALL-E, DALL-E 2, and DALL-E 3 (stylised DALL·E, and pronounced DOLL-E) are text-to-image models developed by OpenAI using deep learning methodologies to generate digital images from natural language descriptions known as prompts. The first version of DALL-E was announced in January 2021. In the following year, its successor DALL-E 2 was released.