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Azure AI Vision

Discover computer vision insights from image and video analysis with OCR and AI.

Elevate your computer vision projects

Azure AI Vision is a unified service that offers innovative computer vision capabilities. Give your apps the ability to analyze images, read text, and detect faces with prebuilt image tagging, text extraction with optical character recognition (OCR), and responsible facial recognition. Incorporate vision features into your projects with no machine learning experience required.

Try it on Vision Studio

Announcing state-of-the-art computer vision features for developers
Image analysis that pulls from more than 10,000 concepts and objects to detect, classify, caption, and generate insights.
Spatial analysis to understand people's presence and movements within physical areas in real time.
Optical character recognition (OCR) to extract printed and handwritten text from images with varied languages and writing styles.
Facial recognition to create intelligent applications that recognize and verify human identity.

Boost content discoverability with image analysis

Automatically caption images with natural language, use smart crop, and classify images (in preview).

Video container

Stream video in real time with spatial analysis

Track movement and analyze environments in real time using computer vision with image analysis and object detection.

Read text from images with optical character recognition (OCR)

Extract printed and handwritten text from images with mixed languages and writing styles using OCR technology.

Optical character recognition for a nutritional facts label
Video container

Verify identities with facial recognition

Create apps with facial recognition for a seamless and highly secure user experience.

Train custom computer vision models

Customize image classification and object detection to fit your needs with just a handful of images and without compromising accuracy (in preview).

An overview of a Custom Model in Vision Studio

Apply AI responsibly

Get clear guidance on how to use computer AI Vision responsibly to meet your goals and achieve accurate results.

IDC MarketScape Worldwide General-Purpose Computer Vision AI Software Platforms graph with leaders such as Microsoft, Google, AWS, Clarifai and more.

Microsoft is named a Leader in the IDC MarketScape: Worldwide General-Purpose Computer Vision AI Software Platform 2022 Vendor Assessment

The IDC MarketScape report evaluated Microsoft’s strategies and capabilities and positioned Microsoft in the Leaders category. We believe this recognition underscores Microsoft’s commitment to deliver cutting-edge, responsible, and customer-centric AI products to organizations of all sizes and across all verticals.

Cover of Designing Distributed Systems book

Fuel App Innovation with Cloud AI Services

Read this 2022 commissioned study conducted by Forrester Consulting to learn how to help developers of any skill level at your organization deploy AI solutions quickly using prebuilt, production-ready cloud AI services.

Comprehensive security and compliance, built in



  • ITAR

  • CJIS


  • IRS 1075

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Trusted across industries, by companies of all sizes

USA Surfing Joins the AI Wave

“Coaches look at these elements. They look at the compression of the body. They look at various dynamic factors. These machine learning models, by measuring angles between the joints of the body while performing surf manuevers, can actually help coaches to provide feedback.” 

Kevin Schulz: Aerial Phenom and Surfer, Team USA

A surfer riding a wave

KPMG helps banking customers identify financial risk

With AI Vision, KPMG finds and analyzes images and videos and uses optical character recognition (OCR) APIs to identify risk.

Three people having a conversation and walking down a hallway

H&R Block uses Azure AI to transform tax returns

“Give us a shoebox of tax documents, and we’ll use AI and machine learning to put the data in the right places.”

Sameer Agarwal: IT Director, H&R Block

A person working at their desk with a laptop displaying the H&R Block website

Reddit improves accessibility and SEO with image and caption generation

"The newly created image captions make Reddit more accessible and give redditors more opportunities to explore our images, engage in conversations, and ultimately build connections and community."

Tiffany Ong: Product Manager of Guest Experience & SEO, Reddit

Three people sitting in desk chairs between desks having a conversation
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Documentation and resources

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Explore samples

Read the quickstart guide

Browse code samples

Frequently asked questions about Azure AI Vision

  • Azure AI Vision and other Azure AI Services offerings guarantee 99.9 percent availability. No SLA is provided for the Free pricing tier. See SLA details.

  • No. Microsoft automatically deletes your images and videos after processing and does not train on your data to enhance the underlying models. Video data does not leave your premises, and video data is not stored on the edge where the container runs. Learn more about privacy and terms of usage.

  • No, spatial analysis detects and locates human presence in video footage and outputs a bounding box around each person detected. The AI models do not detect faces nor determine individuals’ identities nor demographics.

  • The spatial analysis AI models detect and track movements in the video feed based on algorithms that identify the presence of one or more humans by a body bounding box. For each person and bounding box detected in a zone in the camera field of view, the AI models output event data including bounding box coordinates of a person’s body, event type (for example, zone entry or exit, or directional line crossing), pseudonymous identifiers to track the bounding box, and a detection confidence score. This event data is sent to your own instance of Azure IoT Hub.

  • Yes. Because model customization is designed to be fine-tuned for your scenario, you need to provide the labeled data to train your model.

  • The model customization feature of the service is optimized to quickly recognize major differences between images, so you can start prototyping your model with a small amount of data. You may start with as little as one image per label. If you have more labeled images, you may add more. Depending on the complexity of the problem and degree of accuracy required, you can continue adding additional images per label to improve your model.

  • It’s both. You can use the site to access a graphical interface for managing datasets, training, and evaluation of models for a no-code experience, or, as an alternative, you can use the Computer Vision APIs.

  • You can label the images in Azure Machine Learning Studio, which is integrated with Vision Studio for easy export of labeled data. You can also label the data in the COCO file format and import the COCO file directly in Vision Studio. See documentation for details.

  • The model customization feature for Azure AI Vision is the next generation of Custom Vision, with improved accuracy and few-shot learning capabilities. You may continue to use Custom Vision, or you can migrate your training data to retrain your model with model customization from Azure AI Vision. See documentation for details.

  • After using Azure AI Vision to extract insights and text from images and video, you can use text analytics to analyze sentiment, Translator to translate text into your desired language, or Immersive Reader to read the text aloud, making it more accessible. Related services and capabilities include Azure AI Document Intelligence to extract key-value pairs and tables from documents, Azure AI Video Indexer for extracting advanced metadata from audio and video files, and Content Moderator to detect unwanted text or images.

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