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  2. Copyfish - Wikipedia

    en.wikipedia.org/wiki/Copyfish

    After a user marks the text in an image, Copyfish extracts it from a website, video or PDF document. [3] [4] Copyfish was first published in October 2015. [5] [6] Copyfish is not only used in Western countries but despite being available only with an English user interface, is used by many Chinese and Hindi-speaking Chrome users.

  3. OCRopus - Wikipedia

    en.wikipedia.org/wiki/OCRopus

    By default, OCRopus comes with a model for English texts and a model for text in Fraktur. These models refer to the script and are largely independent of the actual language. [ 3 ] New characters or language variants can be trained either from the start, or addeded later.

  4. Flux (text-to-image model) - Wikipedia

    en.wikipedia.org/wiki/Flux_(text-to-image_model)

    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.

  5. Ideogram (text-to-image model) - Wikipedia

    en.wikipedia.org/wiki/Ideogram_(text-to-image_model)

    Ideogram is a freemium text-to-image model developed by Ideogram, Inc. using deep learning methodologies to generate digital images from natural language descriptions known as prompts. The model is capable of generating legible text in the images compared to other text-to-image models. [1] [2]

  6. Text-to-image personalization - Wikipedia

    en.wikipedia.org/wiki/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.

  7. Text-to-image model - Wikipedia

    en.wikipedia.org/wiki/Text-to-image_model

    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.

  8. Contrastive Language-Image Pre-training - Wikipedia

    en.wikipedia.org/wiki/Contrastive_Language-Image...

    In text-to-image retrieval, users input descriptive text, and CLIP retrieves images with matching embeddings. In image-to-text retrieval , images are used to find related text content. CLIP’s ability to connect visual and textual data has found applications in multimedia search, content discovery, and recommendation systems.

  9. Text watermarking - Wikipedia

    en.wikipedia.org/wiki/Text_watermarking

    Text watermarking is a technique for embedding hidden information within textual content to verify its authenticity, origin, or ownership. [1] With the rise of generative AI systems using large language models (LLM), there has been significant development focused on watermarking AI-generated text . [ 2 ]

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