Azure Cognitive Computer Vision

Azure Cognitive Computer Vision

Azure Cognitive Computer Vision

What is Image Analysis?


Transport Layer Security (TLS) 1.2 is now enforced for all HTTP requests to this service. For more information, see Azure Cognitive Services security.

The Computer Vision Image Analysis service can extract a wide variety of visual features from your images. For example, it can determine whether an image contains adult content, find specific brands or objects, or find human faces.

You can use Image Analysis through a client library SDK or by calling the REST API directly. Follow the quickstart to get started.

This documentation contains the following types of articles:

  • The quickstarts are step-by-step instructions that let you make calls to the service and get results in a short period of time.
  • The how-to guides contain instructions for using the service in more specific or customized ways.
  • The conceptual articles provide in-depth explanations of the service’s functionality and features.
  • The tutorials are longer guides that show you how to use this service as a component in broader business solutions.

Image Analysis features

You can analyze images to provide insights about their visual features and characteristics. All of the features in the list below are provided by the Analyze Image API. Follow a quickstart to get started.

Tag visual features

Identify and tag visual features in an image, from a set of thousands of recognizable objects, living things, scenery, and actions. When the tags are ambiguous or not common knowledge, the API response provides hints to clarify the context of the tag. Tagging isn’t limited to the main subject, such as a person in the foreground, but also includes the setting (indoor or outdoor), furniture, tools, plants, animals, accessories, gadgets, and so on. Tag visual features

Detect objects

Object detection is similar to tagging, but the API returns the bounding box coordinates for each tag applied. For example, if an image contains a dog, cat and person, the Detect operation will list those objects together with their coordinates in the image. You can use this functionality to process further relationships between the objects in an image. It also lets you know when there are multiple instances of the same tag in an image. Detect objects

Detect brands

Identify commercial brands in images or videos from a database of thousands of global logos. You can use this feature, for example, to discover which brands are most popular on social media or most prevalent in media product placement. Detect brands

Categorize an image

Identify and categorize an entire image, using a category taxonomy with parent/child hereditary hierarchies. Categories can be used alone, or with our new tagging models.
Currently, English is the only supported language for tagging and categorizing images. Categorize an image

Describe an image

Generate a description of an entire image in human-readable language, using complete sentences. Computer Vision’s algorithms generate various descriptions based on the objects identified in the image. The descriptions are each evaluated and a confidence score generated. A list is then returned ordered from highest confidence score to lowest. Describe an image

Detect faces

Detect faces in an image and provide information about each detected face. Computer Vision returns the coordinates, rectangle, gender, and age for each detected face.
Computer Vision provides a subset of the Face service functionality. You can use the Face service for more detailed analysis, such as facial identification and pose detection. Detect faces

Detect image types

Detect characteristics about an image, such as whether an image is a line drawing or the likelihood of whether an image is clip art. Detect image types

Detect domain-specific content

Use domain models to detect and identify domain-specific content in an image, such as celebrities and landmarks. For example, if an image contains people, Computer Vision can use a domain model for celebrities to determine if the people detected in the image are known celebrities. Detect domain-specific content

Detect the color scheme

Analyze color usage within an image. Computer Vision can determine whether an image is black & white or color and, for color images, identify the dominant and accent colors. Detect the color scheme

Generate a thumbnail

Analyze the contents of an image to generate an appropriate thumbnail for that image. Computer Vision first generates a high-quality thumbnail and then analyzes the objects within the image to determine the area of interest. Computer Vision then crops the image to fit the requirements of the area of interest. The generated thumbnail can be presented using an aspect ratio that is different from the aspect ratio of the original image, depending on your needs. Generate a thumbnail

Get the area of interest

Analyze the contents of an image to return the coordinates of the area of interest. Instead of cropping the image and generating a thumbnail, Computer Vision returns the bounding box coordinates of the region, so the calling application can modify the original image as desired. Get the area of interest

Moderate content in images

You can use Computer Vision to detect adult content in an image and return confidence scores for different classifications. The threshold for flagging content can be set on a sliding scale to accommodate your preferences.

Image requirements

Image Analysis works on images that meet the following requirements:

  • The image must be presented in JPEG, PNG, GIF, or BMP format
  • The file size of the image must be less than 4 megabytes (MB)
  • The dimensions of the image must be greater than 50 x 50 pixels

Data privacy and security

As with all of the Cognitive Services, developers using the Computer Vision service should be aware of Microsoft’s policies on customer data. See the Cognitive Services page on the Microsoft Trust Center to learn more.

Azure’s Computer Vision service gives you access to advanced algorithms that process images and return information based on the visual project.

Create a custom computer vision model in minutes

Customize and embed state-of-the-art computer vision image analysis for specific domains with Custom Vision, part of Azure Cognitive Services. Build frictionless customer experiences, optimize manufacturing processes, accelerate digital marketing campaigns, and more. No machine learning expertise is required.

My Coding Studio


What is Azure Cognitive Services – Computer Vision?

Azure Cognitive Computer Vision
Azure Cognitive Computer Vision

What is Azure Cognitive Services – Computer Vision?

What is Azure Cognitive Services – Computer Vision?
Azure Cognitive Services makes AI project development to be simpler, and faster!

 What Cognitive Services can do?
1. OCR
– Read text from image, pdf

2. Face Detection
– Detect how many human face in a photo
– gender and age analysis

3. Image descriptions
– If you upload a swimming photo, AI will tell you there is a male or female swimming

4. Spatial Analysis(link to CCTV or surveillance cameras)
– Detect how long the person appears in the cctv
– Detect the person wears mask or not
– Measure the distance between people

What is Computer Vision?

Computer Vision for digital asset management

Computer Vision can power many digital asset management (DAM) scenarios. DAM is the business process of organizing, storing, and retrieving rich media assets and managing digital rights and permissions. For example, a company may want to group and identify images based on visible logos, faces, objects, colors, and so on. Or, you might want to automatically generate captions for images and attach keywords so they’re searchable. For an all-in-one DAM solution using Cognitive Services, Azure Cognitive Search, and intelligent reporting, see the Knowledge Mining Solution Accelerator Guide on GitHub. For other DAM examples, see the Computer Vision Solution Templates repository.

Image requirements

Computer Vision can analyze images that meet the following requirements:
  • • The image must be presented in JPEG, PNG, GIF, or BMP format
  • • The file size of the image must be less than 4 megabytes (MB)
  • • The dimensions of the image must be greater than 50 x 50 pixels
    •     • For the Read API, the dimensions of the image must be between 50 x 50 and 10000 x 10000 pixels.

Optical Character Recognition (OCR)

Computer Vision’s OCR APIs support several languages. They do not require you to specify a language code. See the Optical Character Recognition (OCR) overview for more information.
Optical Character Recognition (OCR)
Language Language code Read 3.2 OCR API Read 3.0/3.1
Afrikaans af
Albanian sq
Arabic ar
Asturian ast
Basque eu
Bislama bi
Breton br
Catalan ca
Cebuano ceb
Chamorro ch
Chinese Simplified zh-Hans
Chinese Traditional zh-Hant
Cornish kw
Corsican co
Crimean Tatar Latin crh
Czech cs
Danish da
Dutch nl
English (incl. handwritten) en ✔ (print only)
Estonian et
Fijian fj
Filipino fil
Finnish fi
French fr
Friulian fur
Galician gl
German de
Gilbertese gil
Greek el
Greenlandic kl
Haitian Creole ht
Hani hni
Hmong Daw Latin mww
Hungarian hu
Indonesian id
Interlingua ia
Inuktitut Latin iu
Irish ga
Italian it
Japanese ja
Javanese jv
K'iche' quc
Kabuverdianu kea
Kachin Latin kac
Kara-Kalpak kaa
Kashubian csb
Khasi kha
Korean ko
Kurdish Latin kur
Luxembourgish lb
Malay Latin ms
Manx gv
Neapolitan nap
Norwegian nb
Norwegian no
Occitan oc
Polish pl
Portuguese pt
Romanian ro
Romansh rm
Russian ru
Scots sco
Scottish Gaelic gd
Serbian Cyrillic sr-Cyrl
Serbian Latin sr-Latn
Slovak sk
Slovenian slv
Spanish es
Swahili Latin sw
Swedish sv
Tatar Latin tat
Tetum tet
Turkish tr
Upper Sorbian hsb
Uzbek Latin uz
Volapük vo
Walser wae
Western Frisian fy
Yucatec Maya yua
Zhuang za
Zulu zu