# Image-to-text ## Overview Bridging the gap between visual and textual content is a crucial step in unlocking the full potential of digital assets. The Image-to-text ML model is an advanced solution designed to do just that by providing general-purpose visual and language understanding. The model leverages state-of-the-art natural language processing and computer vision techniques to facilitate the understanding of images and textual data. When a user submits an image and an accompanying textual prompt (typically in the form of a question regarding the image), the model processes the visual and textual data, identifying objects, context and relationships within the image, and generates a relevant response. Users can pose a wide range of questions, from object recognition and content analysis to more complex queries related to the image. The output is a properly constructed natural language answer that provides insights or information pertaining to the submitted data. Our Image-to-text functionality is a versatile tool that gives customers the ability to extract insights, enrich content and enhance the overall management of digital assets. ## Typical use cases The Image-to-text functionality is powerful enough to be applied across a spectrum of industries and domains, such as: * **Content tagging** - Customers can automatically generate descriptive metadata for images, simplifying the organization and retrieval of digital assets. * **E-commerce and product catalogs** - E-commerce platforms can utilize the model to answer user queries about product images, providing detailed information and enhancing the shopping experience. * **Media and entertainment** - Media companies can analyze and describe scenes, characters and objects in images, aiding in content categorization and analysis. * **Educational content** - Educational institutions can enhance e-learning platforms by automatically generating explanations and descriptions for visual content in course materials. ## API endpoints Information about the specific API endpoints is available in an always up-to-date documentation, that can be accessed via the following link: {% embed url="" %} There, you can find detailed information about the API endpoints, together with all required request parameters, so you know how to interact with them. ## Example API responses
Input imageInput promptAPI response
{
    "prompt": "Is the car moving fast?"
}

{
  "status": "success",
  "version": "3.0.2",
  "image_to_text": "No, the car is not moving fast. It is parked in a grassy field.",
  "file_downloaded": "it_tesla.jpeg",
  "request_uuid": "5145e03f-78f0-4667-a867-72d955c2d4bd",
  "sha1": "cc9a4427c90ba5881e5be8d3521724cfcfc9f5b8"
}

{
    "prompt": "Describe the picture"
}

{
  "status": "success",
  "version": "3.0.2",
  "image_to_text": "The picture is a black and white photograph of a canal in a city, featuring a bridge with a clock tower in the background. The canal is filled with water, and there are boats floating on it. The scene is set in a European city, with a large building and a clock tower visible in the background. The image captures the charm and beauty of the city's waterways and architecture.",
  "file_downloaded": "it_amsterdam.jpeg",
  "request_uuid": "cb456045-f63f-4b71-9d22-c9b8f9e6eb42",
  "sha1": "00ceb83e817872c6b2ef103478f62af7eac3dc8e"
}