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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. In 2022, the output of state-of-the-art text-to ...
Image conversion. A large number of image file formats are available for storing graphical data, and, consequently, there are a number of issues associated with converting from one image format to another, most notably loss of image detail.
Optical character recognition or optical character reader ( OCR) is the electronic or mechanical conversion of images of typed, handwritten or printed text into machine-encoded text, whether from a scanned document, a photo of a document, a scene photo (for example the text on signs and billboards in a landscape photo) or from subtitle text ...
Text-to-image personalization. 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.
ImageMagick. ImageMagick, invoked from the command line as magick, is a free and open-source [3] cross-platform software suite for displaying, creating, converting, modifying, and editing raster images. ImageMagick was created by John Cristy in 1987, it can read and write over 200 image file formats.
The bitmap image is composed of a fixed set of pixels, while the vector image is composed of a fixed set of shapes. In the picture, scaling the bitmap reveals the pixels while scaling the vector image preserves the shapes. An image does not have any structure: it is just a collection of marks on paper, grains in film, or pixels in a bitmap ...
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