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2. Optical character recognition - Wikipedia

   en.wikipedia.org/wiki/Optical_character_recognition

   Video of the process of scanning and real-time optical character recognition (OCR) with a portable scanner. 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 ...

3. 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.

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. Google’s new AI tool uses image prompts instead of text

   www.aol.com/google-ai-tool-uses-image-214855525.html

   Since OpenAI initially launched its text-to-image creation tool, Dall-E, in 2021, the concept of AI-generated artwork has swamped social media and become a focus of consumer products. Google’s ...

6. Affinity Photo - Wikipedia

   en.wikipedia.org/wiki/Affinity_Photo

   Affinity Photo has been described as an Adobe Photoshop alternative, and is compatible with common file formats such as Adobe's PSD (including Photoshop Smart Objects). [9] [10] [11] Functionality includes RAW processing, color space options, live preview of effects, image stitching, alpha compositing, black point compensation, and optical aberration corrections. [2]

7. 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.