Azure-AI-Vision
Azure-AI-Vision
Version: 1
MicrosoftLast updated September 2024

Azure AI Vision

Introduction

The Azure AI Vision service gives you access to advanced algorithms that process images and videos and return insights based on the visual features and content you are interested in. Azure AI Vision can power a diverse set of scenarios, including digital asset management, video content search & summary, identity verification, generating accessible alt-text for images, and many more. The key product categories for Azure AI Vision include Video Analysis, Image Analysis, Face, and Optical Character Recognition.

Core Features

  • Video analysis
    • Description: Video Analysis includes video-related features like Spatial Analysis and Video Retrieval. Spatial Analysis analyzes the presence and movement of people on a video feed and produces events that other systems can respond to. Video Retrieval lets you create an index of videos that you can search in your natural language.
    • Key Features: Video retrieval, spatial analysis, person counting, person in a zone, person crossing a line, person distance
  • Face
    • Description: The Face service provides AI algorithms that detect, recognize, and analyze human faces in images. Facial recognition software is important in many different scenarios, such as identification, touchless access control, and face blurring for privacy.
    • Key Features: Face detection and analysis, face liveness, face identification, face verification
  • Image analysis
    • Description: The Image Analysis service extracts many visual features from images, such as objects, faces, adult content, and auto-generated text descriptions.
    • Key Features: Image tagging, image classification, object detection, image captioning, dense captioning, face detection, optical character recognition, image embeddings, and image search
  • Optical character recognition
    • Description: The Optical Character Recognition (OCR) service extracts text from images. You can use the Read API to extract printed and handwritten text from photos and documents. It uses deep-learning-based models and works with text on various surfaces and backgrounds. These include business documents, invoices, receipts, posters, business cards, letters, and whiteboards. The OCR APIs support extracting printed text in several languages.
    • Key Features: OCR

Use Cases

  • Boost content discovery with image analysis
  • Verify identities with the Face service
  • Search content in videos

Benefits

  • No experience required: Incorporate vision features into your projects with no machine learning experience required.
  • Effortlessly customize your models: Customizing your image classification and object detection models can be done with as little as one image per tag, making it easy to train your own models.
  • State of the art models: Ready to use APIs, constantly enhanced models, and flexible deployment options reduce the need for ongoing manual training or extensive customization.

Technical Details

Pricing

View up-to-date pricing information for the pay-as-you-go pricing model here: Azure AI Vision pricing .
Model Specifications
Last UpdatedSeptember 2024
PublisherMicrosoft