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Learn about machine learning models that generate images from natural language descriptions. Explore the history, architecture, datasets, and quality evaluation of text-to-image models, such as DALL-E, Imagen, and Stable Diffusion.
Stable Diffusion is a deep learning model that generates images based on text descriptions, using a latent diffusion technique. It is developed by Stability AI and other researchers, and runs on consumer hardware with a GPU or CPU.
Digitization is the conversion of information into a digital format that can be processed by computers. Learn about the history, challenges, and applications of digitization in various fields, such as libraries, archives, museums, and 3D scanning.
DALL-E, DALL-E 2, and DALL-E 3 are deep learning models that generate images from natural language descriptions. They are based on GPT-3 and CLIP, and can create various styles, manipulate objects, and generate watermarks.
GIF is a lossless image format that can contain up to 256 colors and multiple images in a file. It was developed by CompuServe in 1987 and is widely used on the web for simple graphics and animations.
A binary image is one that consists of pixels that can have one of exactly two colors, usually black and white. Learn about the types, properties, operations and applications of binary images in digital image processing, document scanning, digital art and more.
Learn how to create 3D models from a set of 2D images using various methods and algorithms. Explore the concepts of camera calibration, depth determination, correspondence, stratification and Euclidean reconstruction.
ImageMagick is a free and open-source software suite for displaying, creating, converting, modifying, and editing raster images. It can read and write over 200 image file formats, and supports various features such as color quantization, dithering, liquid rescaling, and artistic effects.
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