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Computer Vision

An AI service that analyzes content in images and video

Extract rich information from images and video

Boost content discoverability, automate text extraction, analyze video in real time, and create products that more people can use by embedding cloud vision capabilities in your apps with Computer Vision, part of Azure Cognitive Services. Use visual data processing to label content with objects and concepts, extract text, generate image descriptions, moderate content, and understand people's movement in physical spaces. No machine learning expertise is required.

Text extraction (OCR)

Extract printed and handwritten text from images and documents with mixed languages and writing styles.

Image understanding

Pull from a rich ontology of more than 10,000 concepts and objects to generate value from your visual assets.

Spatial analysis

Analyze how people move in a space in real time for occupancy count, social distancing and face mask detection.

Flexible deployment

Run Computer Vision in the cloud or on the edge, in containers.

Easily apply breakthrough computer vision

Add leading-edge video- and photo-recognition technology to your own apps with a simple API call.

See it in action

person
person
subway train
Feature Name: Value
Objects [ { "rectangle": { "x": 93, "y": 178, "w": 115, "h": 237 }, "object": "person", "confidence": 0.764 }, { "rectangle": { "x": 0, "y": 229, "w": 101, "h": 206 }, "object": "person", "confidence": 0.624 }, { "rectangle": { "x": 161, "y": 31, "w": 439, "h": 423 }, "object": "subway train", "parent": { "object": "train", "parent": { "object": "Land vehicle", "parent": { "object": "Vehicle", "confidence": 0.926 }, "confidence": 0.923 }, "confidence": 0.917 }, "confidence": 0.801 } ]
Tags [ { "name": "train", "confidence": 0.9974923 }, { "name": "platform", "confidence": 0.9955776 }, { "name": "station", "confidence": 0.979665935 }, { "name": "indoor", "confidence": 0.9272351 }, { "name": "subway", "confidence": 0.83886826 }, { "name": "clothing", "confidence": 0.5561272 }, { "name": "person", "confidence": 0.505803 }, { "name": "pulling", "confidence": 0.431911618 } ]
Description { "tags": [ "train", "platform", "station", "building", "indoor", "subway", "track", "walking", "waiting", "pulling", "board", "people", "man", "luggage", "standing", "holding", "large", "woman", "suitcase" ], "captions": [ { "text": "people waiting at a train station", "confidence": 0.833144665 } ] }
Image format "Jpeg"
Image dimensions 462 x 600
Black and white false
Adult content false
Adult score 0.009112843
Gory false
Gore Score 0.0461505651
Racy false
Racy score 0.0143244732
Categories [ { "name": "trans_trainstation", "score": 0.98828125 } ]
Faces []
Dominant color background
"Black"
Dominant color foreground
"Black"
Accent Color
#484C83
{
  "categories": [
    {
      "name": "trans_trainstation",
      "score": 0.98828125
    }
  ],
  "adult": {
    "isAdultContent": false,
    "isGoryContent": false,
    "isRacyContent": false,
    "adultScore": 0.009112843,
    "goreScore": 0.0461505651,
    "racyScore": 0.0143244732
  },
  "tags": [
    {
      "name": "train",
      "confidence": 0.9974923
    },
    {
      "name": "platform",
      "confidence": 0.9955776
    },
    {
      "name": "station",
      "confidence": 0.979665935
    },
    {
      "name": "indoor",
      "confidence": 0.9272351
    },
    {
      "name": "subway",
      "confidence": 0.83886826
    },
    {
      "name": "clothing",
      "confidence": 0.5561272
    },
    {
      "name": "person",
      "confidence": 0.505803
    },
    {
      "name": "pulling",
      "confidence": 0.431911618
    }
  ],
  "description": {
    "tags": [
      "train",
      "platform",
      "station",
      "building",
      "indoor",
      "subway",
      "track",
      "walking",
      "waiting",
      "pulling",
      "board",
      "people",
      "man",
      "luggage",
      "standing",
      "holding",
      "large",
      "woman",
      "suitcase"
    ],
    "captions": [
      {
        "text": "people waiting at a train station",
        "confidence": 0.833144665
      }
    ]
  },
  "requestId": "b045f147-283a-4703-b2e1-0e3ed77b743b",
  "metadata": {
    "width": 600,
    "height": 462,
    "format": "Jpeg"
  },
  "faces": [],
  "color": {
    "dominantColorForeground": "Black",
    "dominantColorBackground": "Black",
    "accentColor": "484C83",
    "isBWImg": false
  },
  "objects": [
    {
      "rectangle": {
        "x": 93,
        "y": 178,
        "w": 115,
        "h": 237
      },
      "object": "person",
      "confidence": 0.764
    },
    {
      "rectangle": {
        "x": 0,
        "y": 229,
        "w": 101,
        "h": 206
      },
      "object": "person",
      "confidence": 0.624
    },
    {
      "rectangle": {
        "x": 161,
        "y": 31,
        "w": 439,
        "h": 423
      },
      "object": "subway train",
      "parent": {
        "object": "train",
        "parent": {
          "object": "Land vehicle",
          "parent": {
            "object": "Vehicle",
            "confidence": 0.926
          },
          "confidence": 0.923
        },
        "confidence": 0.917
      },
      "confidence": 0.801
    }
  ]
}