Microsoft Vision

Microsoft Vision

by UiPath

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0

Integration Service Connector

Runs

<100

Summary

Summary

Microsoft product using pre-built algorithms to process images and return information.

Overview

Overview

Microsoft Computer Vision offers state-of-the-art algorithms for analyzing images and retrieving information. With this technology, it becomes possible to detect inappropriate content in images, identify faces, estimate colors, categorize content, and describe images using complete English sentences.

Moreover, Microsoft Computer Vision can intelligently generate image thumbnails, which can help optimize the display of large images.

To begin utilizing these capabilities, establishing a connection with your Microsoft Vision instance is necessary before automating any processes. Detailed step-by-step instructions are available on the .

You can use the connection to enable the in and build automations that interact with your Microsoft Vision data. These activities allow you to execute create, read, update, and delete operations on your Microsoft Vision objects.

The UiPath connector for Microsoft Vision is compatible with the REST API v3.2, which ensures seamless integration with your existing infrastructure.

currently does not support events and is in preview.

Features

Features

Microsoft Computer Vision is a cloud-based service that provides advanced image processing algorithms for extracting information from images. Some of its key capabilities are:

  • detecting and flagging mature content in an image.
  • identifying all the faces in an image.
  • estimating the dominant and accent colors in an image.
  • categorizing the content of an image, such as identifying whether it contains people, animals, or landmarks.
  • describing an image with complete English sentences. This is achieved using natural language processing techniques, which analyze the visual features of the image and generate a textual description that is accurate and meaningful.
  • intelligently generating image thumbnails that effectively display large images. This is achieved using image resizing techniques that maintain the aspect ratio and visual content of the image while reducing its size, allowing it to be displayed more efficiently on different devices and platforms.

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